diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..1d64f502eb507da47d59b6b1fc4ca67c9574938a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"education_level": "Graduate", "total_rows": 11598, "missing_rows": 0, "missing_rate": 0.0}, {"education_level": "Masters", "total_rows": 4361, "missing_rows": 0, "missing_rate": 0.0}, {"education_level": "High School", "total_rows": 2017, "missing_rows": 0, "missing_rate": 0.0}, {"education_level": "", "total_rows": 460, "missing_rows": 0, "missing_rate": 0.0}, {"education_level": "Phd", "total_rows": 414, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..6a821640af7181783232bb8df16f17e67758eed2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: co_missingness_pattern_consistency +-- intended_facet_id: missing_rate_by_subgroup +-- variant_semantic_role: missing_rate_by_subgroup +-- template_id: tpl_missing_rate_by_subgroup +-- query_record_id: v2q_m9_0022744f06488758 +-- problem_id: v2p_m9_db5978a95a78fdcd +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "education_level", + COUNT(*) AS total_rows, + SUM(CASE WHEN "enrolled_university" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "enrolled_university" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9" +GROUP BY "education_level" +ORDER BY missing_rate DESC, total_rows DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..dd60ef6218d867c7611774fb1fd1c80a349a05a7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: co_missingness_pattern_consistency\n-- intended_facet_id: missing_rate_by_subgroup\n-- variant_semantic_role: missing_rate_by_subgroup\n-- template_id: tpl_missing_rate_by_subgroup\n-- query_record_id: v2q_m9_0022744f06488758\n-- problem_id: v2p_m9_db5978a95a78fdcd\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"education_level\",\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"enrolled_university\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"enrolled_university\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\"\nGROUP BY \"education_level\"\nORDER BY missing_rate DESC, total_rows DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: co_missingness_pattern_consistency\\n-- intended_facet_id: missing_rate_by_subgroup\\n-- variant_semantic_role: missing_rate_by_subgroup\\n-- template_id: tpl_missing_rate_by_subgroup\\n-- query_record_id: v2q_m9_0022744f06488758\\n-- problem_id: v2p_m9_db5978a95a78fdcd\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"education_level\\\",\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"enrolled_university\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"enrolled_university\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"education_level\\\"\\nORDER BY missing_rate DESC, total_rows DESC;\", \"columns\": [\"education_level\", \"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"education_level\": \"Graduate\", \"total_rows\": 11598, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"education_level\": \"Masters\", \"total_rows\": 4361, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"education_level\": \"High School\", \"total_rows\": 2017, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"education_level\": \"\", \"total_rows\": 460, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"education_level\": \"Phd\", \"total_rows\": 414, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"education_level\": \"Primary School\", \"total_rows\": 308, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 6, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 8.29}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..f9db774dfce3f302e60bfbdc5928e1249914c7a1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/run_manifest.json @@ -0,0 +1,59 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:55.955969+00:00", + "ended_at": "2026-05-19T16:08:55.964952+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_0022744f06488758", + "problem_id": "v2p_m9_db5978a95a78fdcd", + "dataset_id": "m9", + "template_id": "tpl_missing_rate_by_subgroup", + "template_name": "Missing Rate by Subgroup", + "family_id": "missingness_structure", + "canonical_subitem_id": "co_missingness_pattern_consistency", + "intended_facet_id": "missing_rate_by_subgroup", + "variant_semantic_role": "missing_rate_by_subgroup", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Missing Rate by Subgroup to probe co_missingness_pattern_consistency with semantic role missing_rate_by_subgroup. Focus on group_col=education_level, missing_col=enrolled_university.", + "bindings": { + "missing_col": "enrolled_university", + "group_col": "education_level" + }, + "binding_roles": [ + "missing_col", + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY missing_rate DESC, total_rows DESC;", + "notes": [ + "default_facets=missing_rate_by_subgroup,missing_target_interaction", + "template_selection_mode=deterministic", + "problem_index_within_template=3", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_0022744f06488758.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0022744f06488758/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..91a925fc6f4472fd6a48f4219a19f241aa67b206 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=experience, group_col_2=last_new_job. +Result preview: [{"experience": ">20", "last_new_job": "4", "row_count": 220}, {"experience": "10", "last_new_job": "4", "row_count": 79}, {"experience": "9", "last_new_job": "4", "row_count": 79}, {"experience": "7", "last_new_job": "4", "row_count": 68}, {"experience": "4", "last_new_job": "4", "row_count": 67}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..719b0c44d65956d026b508ab3dae6faea7d02cb9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: count_distribution +-- template_id: tpl_c2_filtered_group_count_2d +-- query_record_id: v2q_m9_0143799233bedfc5 +-- problem_id: v2p_m9_892a5278cf8db423 +-- realization_mode: agent +-- source_kind: agent +SELECT "experience", "last_new_job", COUNT(*) AS "row_count" +FROM "m9" +WHERE "last_new_job" = '4' +GROUP BY "experience", "last_new_job" +ORDER BY "row_count" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a3493e29763ea4c3a3d202e2dc4444ea76e6e155 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"experience\", \"last_new_job\", COUNT(*) AS \"row_count\"\nFROM \"m9\"\nWHERE \"last_new_job\" = '4'\nGROUP BY \"experience\", \"last_new_job\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"experience\\\", \\\"last_new_job\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m9\\\"\\nWHERE \\\"last_new_job\\\" = '4'\\nGROUP BY \\\"experience\\\", \\\"last_new_job\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"experience\", \"last_new_job\", \"row_count\"], \"rows\": [{\"experience\": \">20\", \"last_new_job\": \"4\", \"row_count\": 220}, {\"experience\": \"10\", \"last_new_job\": \"4\", \"row_count\": 79}, {\"experience\": \"9\", \"last_new_job\": \"4\", \"row_count\": 79}, {\"experience\": \"7\", \"last_new_job\": \"4\", \"row_count\": 68}, {\"experience\": \"4\", \"last_new_job\": \"4\", \"row_count\": 67}, {\"experience\": \"5\", \"last_new_job\": \"4\", \"row_count\": 64}, {\"experience\": \"6\", \"last_new_job\": \"4\", \"row_count\": 64}, {\"experience\": \"14\", \"last_new_job\": \"4\", \"row_count\": 54}, {\"experience\": \"8\", \"last_new_job\": \"4\", \"row_count\": 45}, {\"experience\": \"12\", \"last_new_job\": \"4\", \"row_count\": 44}, {\"experience\": \"15\", \"last_new_job\": \"4\", \"row_count\": 42}, {\"experience\": \"16\", \"last_new_job\": \"4\", \"row_count\": 41}, {\"experience\": \"11\", \"last_new_job\": \"4\", \"row_count\": 38}, {\"experience\": \"13\", \"last_new_job\": \"4\", \"row_count\": 34}, {\"experience\": \"17\", \"last_new_job\": \"4\", \"row_count\": 26}, {\"experience\": \"19\", \"last_new_job\": \"4\", \"row_count\": 25}, {\"experience\": \"18\", \"last_new_job\": \"4\", \"row_count\": 24}, {\"experience\": \"<1\", \"last_new_job\": \"4\", \"row_count\": 8}, {\"experience\": \"20\", \"last_new_job\": \"4\", \"row_count\": 6}, {\"experience\": \"\", \"last_new_job\": \"4\", \"row_count\": 1}], \"row_count_returned\": 20, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 6.62}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..8b5402a804bda36b0a59cbda2433ef6e57d32761 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/run_manifest.json @@ -0,0 +1,93 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:43:07.128711+00:00", + "ended_at": "2026-05-19T15:43:19.667743+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_0143799233bedfc5", + "problem_id": "v2p_m9_892a5278cf8db423", + "dataset_id": "m9", + "template_id": "tpl_c2_filtered_group_count_2d", + "template_name": "Filtered Two-Dimensional Group Count", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=experience, group_col_2=last_new_job.", + "bindings": { + "group_col": "experience", + "group_col_2": "last_new_job", + "predicate_col": "last_new_job", + "predicate_op": "=", + "predicate_value": "4", + "top_k": 13, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "group_col_2", + "predicate_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/1", + "binding_index=53" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_0143799233bedfc5.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_0143799233bedfc5", + "api_calls": 0, + "input_tokens": 14739, + "cached_input_tokens": 13696, + "output_tokens": 485, + "total_tokens": 15224, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12525.53, + "sql_execution_elapsed_ms_total": 6.62, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..de349f6fc3c5727dd51907eed3aedccfa4a0fc27 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:43:19.657999+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 12525.53, "started_at": "2026-05-19T15:43:07.130754+00:00", "ended_at": "2026-05-19T15:43:19.656321+00:00", "prompt_metrics": {"chars": 9605, "bytes_utf8": 9605, "lines": 268, "estimated_tokens": null}, "response_metrics": {"chars": 428, "bytes_utf8": 428, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14739, "cached_input_tokens": 13696, "output_tokens": 485, "reasoning_output_tokens": 367}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"experience\\\", \\\"last_new_job\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m9\\\"\\nWHERE \\\"last_new_job\\\" = '4'\\nGROUP BY \\\"experience\\\", \\\"last_new_job\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Uses the planned filtered two-dimensional group count template with \\\"experience\\\" and \\\"last_new_job\\\" as the grouping columns, restricted to rows where \\\"last_new_job\\\" = '4'.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..360d210f585b902e2950bbbe15a044c0ae8e333d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_0143799233bedfc5", + "api_calls": 0, + "input_tokens": 14739, + "cached_input_tokens": 13696, + "output_tokens": 485, + "total_tokens": 15224, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12525.53, + "sql_execution_elapsed_ms_total": 6.62, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0143799233bedfc5/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3c1fbbfc502ce3527f253e3a3e071a2157c198f3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"total_rows": 19158, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..6e51246dfe41170df095428d417e3cb83922a799 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: marginal_missing_rate_consistency +-- intended_facet_id: missing_indicator_distribution +-- variant_semantic_role: missing_indicator_view +-- template_id: tpl_missing_marginal_rate_profile +-- query_record_id: v2q_m9_03be4dfac16fff45 +-- problem_id: v2p_m9_a19ccf07f79d1f5d +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + COUNT(*) AS total_rows, + SUM(CASE WHEN "major_discipline" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "major_discipline" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3d8cbca6984d40f343990174e73665b627de1f30 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: marginal_missing_rate_consistency\n-- intended_facet_id: missing_indicator_distribution\n-- variant_semantic_role: missing_indicator_view\n-- template_id: tpl_missing_marginal_rate_profile\n-- query_record_id: v2q_m9_03be4dfac16fff45\n-- problem_id: v2p_m9_a19ccf07f79d1f5d\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"major_discipline\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"major_discipline\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\";", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: marginal_missing_rate_consistency\\n-- intended_facet_id: missing_indicator_distribution\\n-- variant_semantic_role: missing_indicator_view\\n-- template_id: tpl_missing_marginal_rate_profile\\n-- query_record_id: v2q_m9_03be4dfac16fff45\\n-- problem_id: v2p_m9_a19ccf07f79d1f5d\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"major_discipline\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"major_discipline\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\";\", \"columns\": [\"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"total_rows\": 19158, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.83}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..b20f24f8723938eadd527bba86615de225178146 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:55.914895+00:00", + "ended_at": "2026-05-19T16:08:55.918374+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_03be4dfac16fff45", + "problem_id": "v2p_m9_a19ccf07f79d1f5d", + "dataset_id": "m9", + "template_id": "tpl_missing_marginal_rate_profile", + "template_name": "Marginal Missing Rate Profile", + "family_id": "missingness_structure", + "canonical_subitem_id": "marginal_missing_rate_consistency", + "intended_facet_id": "missing_indicator_distribution", + "variant_semantic_role": "missing_indicator_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Marginal Missing Rate Profile to probe marginal_missing_rate_consistency with semantic role missing_indicator_view. Focus on missing_col=major_discipline.", + "bindings": { + "missing_col": "major_discipline" + }, + "binding_roles": [ + "missing_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table};", + "notes": [ + "default_facets=missing_indicator_distribution", + "template_selection_mode=deterministic", + "problem_index_within_template=4", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_03be4dfac16fff45.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03be4dfac16fff45/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..56f7bb857a876f3acdddbb2e043b446a2d026cf4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=experience, measure_col=enrollee_id. +Result preview: [{"experience": "1", "avg_measure": 18137.92349726776}, {"experience": "<1", "avg_measure": 17797.287356321838}, {"experience": "16", "avg_measure": 17638.716535433072}, {"experience": "2", "avg_measure": 17625.831410825198}, {"experience": "3", "avg_measure": 17480.977104874448}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..76dc83981456a7aec3b1e59ec487b8b9c3c3f76c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_m9_03d55ad136bfea10 +-- problem_id: v2p_m9_f4ae55ba1e5d9a37 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT + "experience", + AVG(CAST("enrollee_id" AS REAL)) OVER (PARTITION BY "experience") AS avg_measure +FROM "m9" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..4fd8c9dfb8de598060d20cf0a10b4f1b45d08713 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT\n \"experience\",\n AVG(CAST(\"enrollee_id\" AS REAL)) OVER (PARTITION BY \"experience\") AS avg_measure\nFROM \"m9\"\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT\\n \\\"experience\\\",\\n AVG(CAST(\\\"enrollee_id\\\" AS REAL)) OVER (PARTITION BY \\\"experience\\\") AS avg_measure\\nFROM \\\"m9\\\"\\nORDER BY avg_measure DESC;\", \"columns\": [\"experience\", \"avg_measure\"], \"rows\": [{\"experience\": \"1\", \"avg_measure\": 18137.92349726776}, {\"experience\": \"<1\", \"avg_measure\": 17797.287356321838}, {\"experience\": \"16\", \"avg_measure\": 17638.716535433072}, {\"experience\": \"2\", \"avg_measure\": 17625.831410825198}, {\"experience\": \"3\", \"avg_measure\": 17480.977104874448}, {\"experience\": \"5\", \"avg_measure\": 17176.090909090908}, {\"experience\": \"4\", \"avg_measure\": 17058.07127583749}, {\"experience\": \"6\", \"avg_measure\": 17007.901315789473}, {\"experience\": \"18\", \"avg_measure\": 16880.589285714286}, {\"experience\": \"7\", \"avg_measure\": 16865.820038910504}, {\"experience\": \"9\", \"avg_measure\": 16793.230612244897}, {\"experience\": \"19\", \"avg_measure\": 16733.092105263157}, {\"experience\": \"13\", \"avg_measure\": 16720.471177944863}, {\"experience\": \"11\", \"avg_measure\": 16635.213855421687}, {\"experience\": \"10\", \"avg_measure\": 16590.42233502538}, {\"experience\": \">20\", \"avg_measure\": 16572.157029823495}, {\"experience\": \"17\", \"avg_measure\": 16564.698830409357}, {\"experience\": \"20\", \"avg_measure\": 16232.743243243243}, {\"experience\": \"8\", \"avg_measure\": 16212.034912718205}, {\"experience\": \"12\", \"avg_measure\": 16102.467611336033}, {\"experience\": \"15\", \"avg_measure\": 15911.322157434402}, {\"experience\": \"14\", \"avg_measure\": 15869.032423208191}, {\"experience\": \"\", \"avg_measure\": 15659.246153846154}], \"row_count_returned\": 23, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 32.73}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..b3cb08299805fd9a93349540dff9031ab37fe5eb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:33.108047+00:00", + "ended_at": "2026-05-19T16:08:41.538283+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_03d55ad136bfea10", + "problem_id": "v2p_m9_f4ae55ba1e5d9a37", + "dataset_id": "m9", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=experience, measure_col=enrollee_id.", + "bindings": { + "group_col": "experience", + "measure_col": "enrollee_id", + "top_k": 18, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=2/2", + "binding_index=138" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 7, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_03d55ad136bfea10.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_03d55ad136bfea10", + "api_calls": 0, + "input_tokens": 14659, + "cached_input_tokens": 12032, + "output_tokens": 311, + "total_tokens": 14970, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8392.9, + "sql_execution_elapsed_ms_total": 32.73, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c78275d2881694e860266a52b95dd7ab66690d54 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:08:41.503880+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8392.9, "started_at": "2026-05-19T16:08:33.110209+00:00", "ended_at": "2026-05-19T16:08:41.503135+00:00", "prompt_metrics": {"chars": 9380, "bytes_utf8": 9380, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 440, "bytes_utf8": 440, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14659, "cached_input_tokens": 12032, "output_tokens": 311, "reasoning_output_tokens": 197}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT\\n \\\"experience\\\",\\n AVG(CAST(\\\"enrollee_id\\\" AS REAL)) OVER (PARTITION BY \\\"experience\\\") AS avg_measure\\nFROM \\\"m9\\\"\\nORDER BY avg_measure DESC;\",\"notes\":\"Applied the Window Partition Average template with group_col=\\\"experience\\\" and measure_col=\\\"enrollee_id\\\". CAST is used because \\\"enrollee_id\\\" is stored as TEXT in the schema but contains numeric-like values.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..e6e1d8159d4fde996e84e0f9ada163819291060b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_03d55ad136bfea10", + "api_calls": 0, + "input_tokens": 14659, + "cached_input_tokens": 12032, + "output_tokens": 311, + "total_tokens": 14970, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8392.9, + "sql_execution_elapsed_ms_total": 32.73, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_03d55ad136bfea10/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..775a6def31ebe9a85e7c0f3d1f3d88468fed00ca --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9304, "bytes_utf8": 9304, "lines": 264, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 397, "bytes_utf8": 397, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14648, "cached_input_tokens": 12032, "output_tokens": 340, "reasoning_output_tokens": 236}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..33f8dc996d4fb2c9f2b33b6c0a30e3cb3fdd562b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_0759b6e47d5c437d", + "api_calls": 0, + "input_tokens": 14648, + "cached_input_tokens": 12032, + "output_tokens": 340, + "total_tokens": 14988, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9428.85, + "sql_execution_elapsed_ms_total": 11.91, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..2f021358940c53b688317e15c31a37bbda66feb8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:28:42.804089+00:00", + "ended_at": "2026-05-19T15:28:52.232972+00:00", + "elapsed_ms": 9428.85, + "prompt_metrics": { + "chars": 9304, + "bytes_utf8": 9304, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 751, + "bytes_utf8": 751, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 397, + "bytes_utf8": 397, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14648, + "cached_input_tokens": 12032, + "output_tokens": 340, + "reasoning_output_tokens": 236 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..c327ec4d04557085af748ff36e53abbd32beb43e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "primary_family": "subgroup_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=gender, measure_col=city_development_index.", + "planned_template_id": "tpl_h2o_group_sum", + "bindings": { + "group_col": "gender", + "measure_col": "city_development_index", + "top_k": 11, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..a3d12ac50920504d6be278917a79aa2cb3f5a54b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40da-844f-7c81-ba76-68943f57226c"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"gender\\\", SUM(CAST(NULLIF(\\\"city_development_index\\\", '') AS REAL)) AS total_measure\\nFROM \\\"m9\\\"\\nGROUP BY \\\"gender\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the planned grouped-sum template with group_col=\\\"gender\\\" and measure_col=\\\"city_development_index\\\". CAST/NULLIF makes the TEXT measure SQLite-numeric and ignores empty strings.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14648,"cached_input_tokens":12032,"output_tokens":340,"reasoning_output_tokens":236}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..a9b923a63643dee601d75d768ff80d899176beb0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"gender\", SUM(CAST(NULLIF(\"city_development_index\", '') AS REAL)) AS total_measure\nFROM \"m9\"\nGROUP BY \"gender\"\nORDER BY total_measure DESC;","notes":"Used the planned grouped-sum template with group_col=\"gender\" and measure_col=\"city_development_index\". CAST/NULLIF makes the TEXT measure SQLite-numeric and ignores empty strings."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0759b6e47d5c437d/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..8eec05bcd0f305e81e8b1dfc2f76d59c9be8f318 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"training_hours": "28", "support": 329, "avg_response": 16998.531914893618}, {"training_hours": "12", "support": 292, "avg_response": 15239.982876712329}, {"training_hours": "18", "support": 291, "avg_response": 16395.494845360823}, {"training_hours": "22", "support": 282, "avg_response": 15771.663120567377}, {"training_hours": "50", "support": 279, "avg_response": 16534.26164874552}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..938b53687fd29eed4dcf826668e6ddb6d586e262 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_m9_07c06a61109b6393 +-- problem_id: v2p_m9_b6c283cdec13a42d +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "training_hours", + COUNT(*) AS support, + AVG("enrollee_id") AS avg_response +FROM "m9" +GROUP BY "training_hours" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6b9dbdd115dfee473720a0cbf6984cd657aeaeed --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_m9_07c06a61109b6393\n-- problem_id: v2p_m9_b6c283cdec13a42d\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"training_hours\",\n COUNT(*) AS support,\n AVG(\"enrollee_id\") AS avg_response\nFROM \"m9\"\nGROUP BY \"training_hours\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_m9_07c06a61109b6393\\n-- problem_id: v2p_m9_b6c283cdec13a42d\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"training_hours\\\",\\n COUNT(*) AS support,\\n AVG(\\\"enrollee_id\\\") AS avg_response\\nFROM \\\"m9\\\"\\nGROUP BY \\\"training_hours\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"training_hours\", \"support\", \"avg_response\"], \"rows\": [{\"training_hours\": \"28\", \"support\": 329, \"avg_response\": 16998.531914893618}, {\"training_hours\": \"12\", \"support\": 292, \"avg_response\": 15239.982876712329}, {\"training_hours\": \"18\", \"support\": 291, \"avg_response\": 16395.494845360823}, {\"training_hours\": \"22\", \"support\": 282, \"avg_response\": 15771.663120567377}, {\"training_hours\": \"50\", \"support\": 279, \"avg_response\": 16534.26164874552}, {\"training_hours\": \"20\", \"support\": 278, \"avg_response\": 17199.413669064747}, {\"training_hours\": \"17\", \"support\": 273, \"avg_response\": 17023.69230769231}, {\"training_hours\": \"24\", \"support\": 273, \"avg_response\": 16606.249084249084}, {\"training_hours\": \"6\", \"support\": 261, \"avg_response\": 17252.011494252874}, {\"training_hours\": \"34\", \"support\": 261, \"avg_response\": 17098.429118773947}, {\"training_hours\": \"23\", \"support\": 258, \"avg_response\": 16658.352713178294}, {\"training_hours\": \"21\", \"support\": 256, \"avg_response\": 17862.7890625}, {\"training_hours\": \"26\", \"support\": 254, \"avg_response\": 15706.094488188977}, {\"training_hours\": \"56\", \"support\": 250, \"avg_response\": 16029.5}, {\"training_hours\": \"42\", \"support\": 242, \"avg_response\": 16903.76446280992}, {\"training_hours\": \"10\", \"support\": 241, \"avg_response\": 16508.091286307055}, {\"training_hours\": \"48\", \"support\": 237, \"avg_response\": 17051.459915611813}, {\"training_hours\": \"11\", \"support\": 237, \"avg_response\": 16218.978902953586}, {\"training_hours\": \"9\", \"support\": 234, \"avg_response\": 17340.62393162393}, {\"training_hours\": \"14\", \"support\": 231, \"avg_response\": 16808.017316017314}, {\"training_hours\": \"15\", \"support\": 230, \"avg_response\": 16908.28695652174}, {\"training_hours\": \"8\", \"support\": 227, \"avg_response\": 16655.629955947137}, {\"training_hours\": \"4\", \"support\": 224, \"avg_response\": 16271.89732142857}, {\"training_hours\": \"46\", \"support\": 223, \"avg_response\": 16739.57399103139}, {\"training_hours\": \"13\", \"support\": 213, \"avg_response\": 17539.19248826291}, {\"training_hours\": \"36\", \"support\": 211, \"avg_response\": 18747.336492890994}, {\"training_hours\": \"7\", \"support\": 209, \"avg_response\": 17742.205741626793}, {\"training_hours\": \"32\", \"support\": 207, \"avg_response\": 16404.00966183575}, {\"training_hours\": \"44\", \"support\": 205, \"avg_response\": 16765.224390243904}, {\"training_hours\": \"25\", \"support\": 199, \"avg_response\": 17172.015075376883}, {\"training_hours\": \"43\", \"support\": 199, \"avg_response\": 17134.56783919598}, {\"training_hours\": \"52\", \"support\": 196, \"avg_response\": 16121.566326530612}, {\"training_hours\": \"40\", \"support\": 192, \"avg_response\": 17611.916666666668}, {\"training_hours\": \"16\", \"support\": 192, \"avg_response\": 16491.8125}, {\"training_hours\": \"30\", \"support\": 187, \"avg_response\": 16995.13368983957}, {\"training_hours\": \"31\", \"support\": 184, \"avg_response\": 16147.255434782608}, {\"training_hours\": \"29\", \"support\": 179, \"avg_response\": 15110.005586592179}, {\"training_hours\": \"39\", \"support\": 178, \"avg_response\": 17306.634831460673}, {\"training_hours\": \"51\", \"support\": 176, \"avg_response\": 15955.52840909091}, {\"training_hours\": \"45\", \"support\": 175, \"avg_response\": 16845.605714285713}, {\"training_hours\": \"55\", \"support\": 171, \"avg_response\": 17884.081871345028}, {\"training_hours\": \"78\", \"support\": 165, \"avg_response\": 15367.648484848485}, {\"training_hours\": \"19\", \"support\": 163, \"avg_response\": 16698.12883435583}, {\"training_hours\": \"37\", \"support\": 163, \"avg_response\": 16025.98773006135}, {\"training_hours\": \"35\", \"support\": 162, \"avg_response\": 17942.41975308642}, {\"training_hours\": \"54\", \"support\": 161, \"avg_response\": 17212.639751552793}, {\"training_hours\": \"47\", \"support\": 157, \"avg_response\": 16763.140127388535}, {\"training_hours\": \"72\", \"support\": 153, \"avg_response\": 16837.849673202614}, {\"training_hours\": \"33\", \"support\": 150, \"avg_response\": 17273.5}, {\"training_hours\": \"41\", \"support\": 145, \"avg_response\": 16840.406896551725}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 10.09}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e836269f0b52b56f1fbaa1ddb1247dfbab2c3082 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.490534+00:00", + "ended_at": "2026-05-19T16:08:56.501450+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_07c06a61109b6393", + "problem_id": "v2p_m9_b6c283cdec13a42d", + "dataset_id": "m9", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=enrollee_id, key_col=training_hours.", + "bindings": { + "key_col": "training_hours", + "measure_col": "enrollee_id", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=11", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 11, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_07c06a61109b6393.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_07c06a61109b6393/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..f2abfcc9f5fd7fa38de2d124a7cb303cad75cf49 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"city_development_index": "0.92", "support": 5200, "avg_response": 66.06134615384616}, {"city_development_index": "0.624", "support": 2702, "avg_response": 65.73723168023686}, {"city_development_index": "0.91", "support": 1533, "avg_response": 66.56425309849968}, {"city_development_index": "0.9259999999999999", "support": 1336, "avg_response": 61.19835329341317}, {"city_development_index": "0.698", "support": 683, "avg_response": 60.58418740849195}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..4b8f92018e7c7334d3fbada62646fa7ebed512ca --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_m9_088d3b25ce027e81 +-- problem_id: v2p_m9_7159a87ac8e5dca0 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "city_development_index", + COUNT(*) AS support, + AVG("training_hours") AS avg_response +FROM "m9" +GROUP BY "city_development_index" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d53ce9af37da2658f486d61fdae9c21466d92fcc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_m9_088d3b25ce027e81\n-- problem_id: v2p_m9_7159a87ac8e5dca0\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"city_development_index\",\n COUNT(*) AS support,\n AVG(\"training_hours\") AS avg_response\nFROM \"m9\"\nGROUP BY \"city_development_index\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_m9_088d3b25ce027e81\\n-- problem_id: v2p_m9_7159a87ac8e5dca0\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"city_development_index\\\",\\n COUNT(*) AS support,\\n AVG(\\\"training_hours\\\") AS avg_response\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city_development_index\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"city_development_index\", \"support\", \"avg_response\"], \"rows\": [{\"city_development_index\": \"0.92\", \"support\": 5200, \"avg_response\": 66.06134615384616}, {\"city_development_index\": \"0.624\", \"support\": 2702, \"avg_response\": 65.73723168023686}, {\"city_development_index\": \"0.91\", \"support\": 1533, \"avg_response\": 66.56425309849968}, {\"city_development_index\": \"0.9259999999999999\", \"support\": 1336, \"avg_response\": 61.19835329341317}, {\"city_development_index\": \"0.698\", \"support\": 683, \"avg_response\": 60.58418740849195}, {\"city_development_index\": \"0.897\", \"support\": 586, \"avg_response\": 63.64505119453925}, {\"city_development_index\": \"0.9390000000000001\", \"support\": 497, \"avg_response\": 64.74647887323944}, {\"city_development_index\": \"0.855\", \"support\": 431, \"avg_response\": 66.50116009280742}, {\"city_development_index\": \"0.804\", \"support\": 304, \"avg_response\": 69.67763157894737}, {\"city_development_index\": \"0.924\", \"support\": 301, \"avg_response\": 65.20930232558139}, {\"city_development_index\": \"0.754\", \"support\": 280, \"avg_response\": 63.80357142857143}, {\"city_development_index\": \"0.887\", \"support\": 275, \"avg_response\": 66.16363636363636}, {\"city_development_index\": \"0.884\", \"support\": 266, \"avg_response\": 68.73684210526316}, {\"city_development_index\": \"0.55\", \"support\": 247, \"avg_response\": 64.61943319838056}, {\"city_development_index\": \"0.9129999999999999\", \"support\": 197, \"avg_response\": 60.055837563451774}, {\"city_development_index\": \"0.899\", \"support\": 182, \"avg_response\": 60.42857142857143}, {\"city_development_index\": \"0.802\", \"support\": 175, \"avg_response\": 67.34285714285714}, {\"city_development_index\": \"0.925\", \"support\": 171, \"avg_response\": 75.01754385964912}, {\"city_development_index\": \"0.893\", \"support\": 160, \"avg_response\": 61.79375}, {\"city_development_index\": \"0.878\", \"support\": 151, \"avg_response\": 60.94701986754967}, {\"city_development_index\": \"0.743\", \"support\": 146, \"avg_response\": 65.47260273972603}, {\"city_development_index\": \"0.9229999999999999\", \"support\": 143, \"avg_response\": 75.83916083916084}, {\"city_development_index\": \"0.8959999999999999\", \"support\": 140, \"avg_response\": 72.38571428571429}, {\"city_development_index\": \"0.8270000000000001\", \"support\": 137, \"avg_response\": 63.77372262773723}, {\"city_development_index\": \"0.579\", \"support\": 135, \"avg_response\": 62.27407407407407}, {\"city_development_index\": \"0.762\", \"support\": 128, \"avg_response\": 58.828125}, {\"city_development_index\": \"0.767\", \"support\": 128, \"avg_response\": 57.3828125}, {\"city_development_index\": \"0.836\", \"support\": 120, \"avg_response\": 56.24166666666667}, {\"city_development_index\": \"0.682\", \"support\": 119, \"avg_response\": 70.56302521008404}, {\"city_development_index\": \"0.6659999999999999\", \"support\": 114, \"avg_response\": 73.05263157894737}, {\"city_development_index\": \"0.89\", \"support\": 113, \"avg_response\": 58.63716814159292}, {\"city_development_index\": \"0.866\", \"support\": 103, \"avg_response\": 70.0}, {\"city_development_index\": \"0.6890000000000001\", \"support\": 102, \"avg_response\": 65.75490196078431}, {\"city_development_index\": \"0.843\", \"support\": 94, \"avg_response\": 67.88297872340425}, {\"city_development_index\": \"0.915\", \"support\": 94, \"avg_response\": 61.734042553191486}, {\"city_development_index\": \"0.794\", \"support\": 93, \"avg_response\": 63.32258064516129}, {\"city_development_index\": \"0.527\", \"support\": 92, \"avg_response\": 68.82608695652173}, {\"city_development_index\": \"0.895\", \"support\": 86, \"avg_response\": 63.41860465116279}, {\"city_development_index\": \"0.903\", \"support\": 82, \"avg_response\": 67.2439024390244}, {\"city_development_index\": \"0.7759999999999999\", \"support\": 82, \"avg_response\": 64.1829268292683}, {\"city_development_index\": \"0.9490000000000001\", \"support\": 79, \"avg_response\": 72.12658227848101}, {\"city_development_index\": \"0.738\", \"support\": 79, \"avg_response\": 53.69620253164557}, {\"city_development_index\": \"0.5579999999999999\", \"support\": 75, \"avg_response\": 88.49333333333334}, {\"city_development_index\": \"0.74\", \"support\": 67, \"avg_response\": 76.38805970149254}, {\"city_development_index\": \"0.555\", \"support\": 63, \"avg_response\": 55.03174603174603}, {\"city_development_index\": \"0.789\", \"support\": 54, \"avg_response\": 64.88888888888889}, {\"city_development_index\": \"0.727\", \"support\": 53, \"avg_response\": 79.67924528301887}, {\"city_development_index\": \"0.7659999999999999\", \"support\": 49, \"avg_response\": 78.77551020408163}, {\"city_development_index\": \"0.848\", \"support\": 47, \"avg_response\": 65.93617021276596}, {\"city_development_index\": \"0.691\", \"support\": 45, \"avg_response\": 58.8}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 9.21}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..b919fce49574beaf93af0f10d9d0b7f3b8fb47fe --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.447763+00:00", + "ended_at": "2026-05-19T16:08:56.457832+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_088d3b25ce027e81", + "problem_id": "v2p_m9_7159a87ac8e5dca0", + "dataset_id": "m9", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=training_hours, key_col=city_development_index.", + "bindings": { + "key_col": "city_development_index", + "measure_col": "training_hours", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=7", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_088d3b25ce027e81.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_088d3b25ce027e81/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..e56db8cd049da777ab03cbca716ce6e855d1719e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=experience, group_col_2=training_hours. +Result preview: [{"experience": ">20", "training_hours": "90", "row_count": 29}, {"experience": ">20", "training_hours": "94", "row_count": 26}, {"experience": ">20", "training_hours": "102", "row_count": 24}, {"experience": ">20", "training_hours": "108", "row_count": 19}, {"experience": ">20", "training_hours": "96", "row_count": 19}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..5fbd9ce63adabf1f7ee6b217eae69e251129e8d6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: count_distribution +-- template_id: tpl_c2_filtered_group_count_2d +-- query_record_id: v2q_m9_0b646637c9fd1427 +-- problem_id: v2p_m9_98456a4def4bddfe +-- realization_mode: agent +-- source_kind: agent +SELECT "experience", "training_hours", COUNT(*) AS "row_count" +FROM "m9" +WHERE CAST("training_hours" AS REAL) >= 88.0 +GROUP BY "experience", "training_hours" +ORDER BY "row_count" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..effa476a0558b4ff0823cf2ed761889352b80a06 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"experience\", \"training_hours\", COUNT(*) AS \"row_count\"\nFROM \"m9\"\nWHERE CAST(\"training_hours\" AS REAL) >= 88.0\nGROUP BY \"experience\", \"training_hours\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"experience\\\", \\\"training_hours\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m9\\\"\\nWHERE CAST(\\\"training_hours\\\" AS REAL) >= 88.0\\nGROUP BY \\\"experience\\\", \\\"training_hours\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"experience\", \"training_hours\", \"row_count\"], \"rows\": [{\"experience\": \">20\", \"training_hours\": \"90\", \"row_count\": 29}, {\"experience\": \">20\", \"training_hours\": \"94\", \"row_count\": 26}, {\"experience\": \">20\", \"training_hours\": \"102\", \"row_count\": 24}, {\"experience\": \">20\", \"training_hours\": \"108\", \"row_count\": 19}, {\"experience\": \">20\", \"training_hours\": \"96\", \"row_count\": 19}, {\"experience\": \">20\", \"training_hours\": \"98\", \"row_count\": 19}, {\"experience\": \">20\", \"training_hours\": \"92\", \"row_count\": 18}, {\"experience\": \">20\", \"training_hours\": \"110\", \"row_count\": 16}, {\"experience\": \"5\", \"training_hours\": \"102\", \"row_count\": 15}, {\"experience\": \"5\", \"training_hours\": \"94\", \"row_count\": 15}, {\"experience\": \">20\", \"training_hours\": \"88\", \"row_count\": 15}, {\"experience\": \">20\", \"training_hours\": \"89\", \"row_count\": 15}, {\"experience\": \">20\", \"training_hours\": \"91\", \"row_count\": 15}, {\"experience\": \">20\", \"training_hours\": \"106\", \"row_count\": 14}, {\"experience\": \"3\", \"training_hours\": \"96\", \"row_count\": 13}, {\"experience\": \"6\", \"training_hours\": \"100\", \"row_count\": 13}, {\"experience\": \">20\", \"training_hours\": \"116\", \"row_count\": 13}, {\"experience\": \">20\", \"training_hours\": \"130\", \"row_count\": 13}, {\"experience\": \"3\", \"training_hours\": \"90\", \"row_count\": 12}, {\"experience\": \"3\", \"training_hours\": \"94\", \"row_count\": 12}, {\"experience\": \"4\", \"training_hours\": \"92\", \"row_count\": 12}, {\"experience\": \"5\", \"training_hours\": \"100\", \"row_count\": 12}, {\"experience\": \">20\", \"training_hours\": \"156\", \"row_count\": 12}, {\"experience\": \"6\", \"training_hours\": \"166\", \"row_count\": 11}, {\"experience\": \"9\", \"training_hours\": \"96\", \"row_count\": 11}, {\"experience\": \">20\", \"training_hours\": \"114\", \"row_count\": 11}, {\"experience\": \">20\", \"training_hours\": \"134\", \"row_count\": 11}, {\"experience\": \"2\", \"training_hours\": \"102\", \"row_count\": 10}, {\"experience\": \"5\", \"training_hours\": \"92\", \"row_count\": 10}, {\"experience\": \"5\", \"training_hours\": \"98\", \"row_count\": 10}, {\"experience\": \"6\", \"training_hours\": \"106\", \"row_count\": 10}, {\"experience\": \"8\", \"training_hours\": \"102\", \"row_count\": 10}, {\"experience\": \"8\", \"training_hours\": \"110\", \"row_count\": 10}, {\"experience\": \"9\", \"training_hours\": \"88\", \"row_count\": 10}, {\"experience\": \">20\", \"training_hours\": \"100\", \"row_count\": 10}, {\"experience\": \">20\", \"training_hours\": \"124\", \"row_count\": 10}, {\"experience\": \">20\", \"training_hours\": \"126\", \"row_count\": 10}, {\"experience\": \">20\", \"training_hours\": \"152\", \"row_count\": 10}, {\"experience\": \">20\", \"training_hours\": \"154\", \"row_count\": 10}, {\"experience\": \">20\", \"training_hours\": \"160\", \"row_count\": 10}, {\"experience\": \">20\", \"training_hours\": \"95\", \"row_count\": 10}, {\"experience\": \"2\", \"training_hours\": \"100\", \"row_count\": 9}, {\"experience\": \"3\", \"training_hours\": \"102\", \"row_count\": 9}, {\"experience\": \"3\", \"training_hours\": \"108\", \"row_count\": 9}, {\"experience\": \"3\", \"training_hours\": \"109\", \"row_count\": 9}, {\"experience\": \"4\", \"training_hours\": \"105\", \"row_count\": 9}, {\"experience\": \"4\", \"training_hours\": \"160\", \"row_count\": 9}, {\"experience\": \"4\", \"training_hours\": \"96\", \"row_count\": 9}, {\"experience\": \"5\", \"training_hours\": \"112\", \"row_count\": 9}, {\"experience\": \"6\", \"training_hours\": \"102\", \"row_count\": 9}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 9.96}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..9a25705f526e5d17920d6a134d439313d952ada9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/run_manifest.json @@ -0,0 +1,93 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:43:19.669001+00:00", + "ended_at": "2026-05-19T15:43:38.723867+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_0b646637c9fd1427", + "problem_id": "v2p_m9_98456a4def4bddfe", + "dataset_id": "m9", + "template_id": "tpl_c2_filtered_group_count_2d", + "template_name": "Filtered Two-Dimensional Group Count", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=experience, group_col_2=training_hours.", + "bindings": { + "group_col": "experience", + "group_col_2": "training_hours", + "predicate_col": "training_hours", + "predicate_op": ">=", + "predicate_value": 88.0, + "top_k": 14, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "group_col_2", + "predicate_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/1", + "binding_index=54" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_0b646637c9fd1427.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_0b646637c9fd1427", + "api_calls": 0, + "input_tokens": 14740, + "cached_input_tokens": 13696, + "output_tokens": 641, + "total_tokens": 15381, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 19037.11, + "sql_execution_elapsed_ms_total": 9.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..52a9fc9b110058ff7eb0da15f8280bdb129aa418 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:43:38.710541+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 19037.11, "started_at": "2026-05-19T15:43:19.672520+00:00", "ended_at": "2026-05-19T15:43:38.709669+00:00", "prompt_metrics": {"chars": 9618, "bytes_utf8": 9618, "lines": 268, "estimated_tokens": null}, "response_metrics": {"chars": 498, "bytes_utf8": 498, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14740, "cached_input_tokens": 13696, "output_tokens": 641, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"experience\\\", \\\"training_hours\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m9\\\"\\nWHERE CAST(\\\"training_hours\\\" AS REAL) >= 88.0\\nGROUP BY \\\"experience\\\", \\\"training_hours\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Used the provided filtered two-dimensional group-count template with \\\"experience\\\" and \\\"training_hours\\\". CAST(\\\"training_hours\\\" AS REAL) is needed because the schema stores it as TEXT while the predicate value is numeric.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..e38fc991899525d810d6f32037ba95eb19e0d99b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_0b646637c9fd1427", + "api_calls": 0, + "input_tokens": 14740, + "cached_input_tokens": 13696, + "output_tokens": 641, + "total_tokens": 15381, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 19037.11, + "sql_execution_elapsed_ms_total": 9.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0b646637c9fd1427/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e68d8b1259ab6b46b466d0f09581b58efda115e8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9552, "bytes_utf8": 9552, "lines": 267, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 448, "bytes_utf8": 448, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14711, "cached_input_tokens": 13696, "output_tokens": 324, "reasoning_output_tokens": 208}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..9ba218aced6585b4d9a194553eb427cf722775f4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_0ba201699a862a68", + "api_calls": 0, + "input_tokens": 14711, + "cached_input_tokens": 13696, + "output_tokens": 324, + "total_tokens": 15035, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12369.35, + "sql_execution_elapsed_ms_total": 11.54, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..0449e2db80bc2c7eb444aa367302bcdda2a41a20 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:01:00.491679+00:00", + "ended_at": "2026-05-19T16:01:12.861063+00:00", + "elapsed_ms": 12369.35, + "prompt_metrics": { + "chars": 9552, + "bytes_utf8": 9552, + "lines": 267, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 803, + "bytes_utf8": 803, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 448, + "bytes_utf8": 448, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14711, + "cached_input_tokens": 13696, + "output_tokens": 324, + "reasoning_output_tokens": 208 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..653a4e7c184c1689c6d40728b758d956da515198 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,267 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=major_discipline, condition_col=company_type.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "major_discipline", + "condition_col": "company_type", + "condition_value": "Pvt Ltd", + "positive_value": "Pvt Ltd", + "negative_value": "", + "top_k": 11, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..4e3265f9144aa83cd3cad4b42efed258ed4cd7c1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f8-155b-7c20-8071-509642920e15"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"major_discipline\\\",\\n AVG(CASE WHEN \\\"company_type\\\" = 'Pvt Ltd' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"major_discipline\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Grouped Condition Rate template applied with group_col=\\\"major_discipline\\\" and condition_col=\\\"company_type\\\", measuring the share of rows in each discipline where company_type is 'Pvt Ltd'.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14711,"cached_input_tokens":13696,"output_tokens":324,"reasoning_output_tokens":208}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..963b0c4734b1ffd6837770987b672a456f0f2477 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT \"major_discipline\",\n AVG(CASE WHEN \"company_type\" = 'Pvt Ltd' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"m9\"\nGROUP BY \"major_discipline\"\nORDER BY condition_rate DESC;","notes":"Grouped Condition Rate template applied with group_col=\"major_discipline\" and condition_col=\"company_type\", measuring the share of rows in each discipline where company_type is 'Pvt Ltd'."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ba201699a862a68/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..810d6270146e4b646f0fdd392866365bde75643f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:04:30.545420+00:00", + "ended_at": "2026-05-19T16:04:34.843793+00:00", + "elapsed_ms": 4298.34, + "returncode": 1, + "prompt_metrics": { + "chars": 9268, + "bytes_utf8": 9268, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..1ed55ee4d669518e5d5a1cd070a477830a45830d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:04:35.847198+00:00", + "ended_at": "2026-05-19T16:04:39.286264+00:00", + "elapsed_ms": 3439.03, + "returncode": 1, + "prompt_metrics": { + "chars": 9268, + "bytes_utf8": 9268, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..b60b194d468c5b7fdb303f03eb20438155ae31ca --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=gender.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "gender", + "top_k": 16, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..b60b194d468c5b7fdb303f03eb20438155ae31ca --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=gender.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "gender", + "top_k": 16, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..05a16b43bbe86bd18d56d2f51f1ae710077a3354 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fb-49c3-7910-b849-2978dc6ab841"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e046d776cf47a82033b4ab0d98d0bf74f30d75f0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fb-49c3-7910-b849-2978dc6ab841"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..fb6dc135ef0375f57968300a7c4126cf3e4332d6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fb-5ea0-7ae1-8ecf-e196bf3855bb"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..faf391fa476f40e291130f21ca793a30bbfc1c8a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fb-5ea0-7ae1-8ecf-e196bf3855bb"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0c4b5053b9c6a406/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1145679a67829fb31587c3881a5382dca14e0afb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9877, "bytes_utf8": 9877, "lines": 264, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 718, "bytes_utf8": 718, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14786, "cached_input_tokens": 13696, "output_tokens": 555, "reasoning_output_tokens": 369}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..92d374fe9b3fe5eebd1294e988ccb69ce0a56e21 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_0ebab9486c912765", + "api_calls": 0, + "input_tokens": 14786, + "cached_input_tokens": 13696, + "output_tokens": 555, + "total_tokens": 15341, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11983.74, + "sql_execution_elapsed_ms_total": 21.2, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..41a1ae15d989ff0e5407cc017cb0377b079a4d98 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:47:57.879769+00:00", + "ended_at": "2026-05-19T15:48:09.863564+00:00", + "elapsed_ms": 11983.74, + "prompt_metrics": { + "chars": 9877, + "bytes_utf8": 9877, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1113, + "bytes_utf8": 1113, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 718, + "bytes_utf8": 718, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14786, + "cached_input_tokens": 13696, + "output_tokens": 555, + "reasoning_output_tokens": 369 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e73b0991229a4ed23bcd562f7a1c222a4cbf77a4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "primary_family": "tail_rarity_structure", + "portability": "partial", + "sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=education_level, measure_col=city_development_index.", + "planned_template_id": "tpl_tpch_relative_total_threshold", + "bindings": { + "group_col": "education_level", + "measure_col": "city_development_index", + "top_k": 11, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..0deca30a7c75db3ef9e4c51da48601bcce21ce96 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40ec-24cd-7de1-b1ac-ee8625f07b3b"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"education_level\\\", SUM(CAST(NULLIF(\\\"city_development_index\\\", '') AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n GROUP BY \\\"education_level\\\"\\n), total AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM grouped\\n)\\nSELECT g.\\\"education_level\\\", g.\\\"group_value\\\"\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Used the planned template with group_col=\\\"education_level\\\" and measure_col=\\\"city_development_index\\\". Casted the measure from TEXT to REAL and treated empty strings as NULL for SQLite-safe aggregation.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14786,"cached_input_tokens":13696,"output_tokens":555,"reasoning_output_tokens":369}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..92bf0d1e86f3d6bd19b5d1927a99be01748da82e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT \"education_level\", SUM(CAST(NULLIF(\"city_development_index\", '') AS REAL)) AS \"group_value\"\n FROM \"m9\"\n GROUP BY \"education_level\"\n), total AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM grouped\n)\nSELECT g.\"education_level\", g.\"group_value\"\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;","notes":"Used the planned template with group_col=\"education_level\" and measure_col=\"city_development_index\". Casted the measure from TEXT to REAL and treated empty strings as NULL for SQLite-safe aggregation."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_0ebab9486c912765/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7502b7e58eb76188ac1c34bb2b8cb485788edab6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9502, "bytes_utf8": 9502, "lines": 264, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 1990, "bytes_utf8": 1990, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14688, "cached_input_tokens": 13696, "output_tokens": 1186, "reasoning_output_tokens": 516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..b98c51e4991ce9c371445f737d9065e5f815e2b2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_102d4ac20150a348", + "api_calls": 0, + "input_tokens": 14688, + "cached_input_tokens": 13696, + "output_tokens": 1186, + "total_tokens": 15874, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18670.69, + "sql_execution_elapsed_ms_total": 72.91, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..35805b26511dc27f68233775790f4afcf074e7c2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:54:57.987400+00:00", + "ended_at": "2026-05-19T15:55:16.658116+00:00", + "elapsed_ms": 18670.69, + "prompt_metrics": { + "chars": 9502, + "bytes_utf8": 9502, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 2637, + "bytes_utf8": 2637, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 1990, + "bytes_utf8": 1990, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14688, + "cached_input_tokens": 13696, + "output_tokens": 1186, + "reasoning_output_tokens": 516 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..2ab72d226c172d071a5db939dcdd4d64c95eefc8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=education_level, measure_col=city_development_index.", + "planned_template_id": "tpl_grouped_percentile_point", + "bindings": { + "group_col": "education_level", + "measure_col": "city_development_index", + "top_k": 18, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..3bc49b2a7b260bca6711ebdbcd2f7a76b60422e4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f2-8d45-7c92-8add-45eb4daf23f4"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"base\\\" AS (\\n SELECT\\n \\\"education_level\\\" AS \\\"group_col\\\",\\n CAST(\\\"city_development_index\\\" AS REAL) AS \\\"measure_col\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"education_level\\\" IS NOT NULL\\n AND \\\"education_level\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n),\\n\\\"ranked\\\" AS (\\n SELECT\\n \\\"group_col\\\",\\n \\\"measure_col\\\",\\n ROW_NUMBER() OVER (PARTITION BY \\\"group_col\\\" ORDER BY \\\"measure_col\\\") AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"group_col\\\") AS \\\"n\\\"\\n FROM \\\"base\\\"\\n),\\n\\\"params\\\" AS (\\n SELECT DISTINCT\\n \\\"group_col\\\",\\n \\\"n\\\",\\n (1.0 + (0.9 * (\\\"n\\\" - 1))) AS \\\"pos\\\",\\n CAST(1.0 + (0.9 * (\\\"n\\\" - 1)) AS INTEGER) AS \\\"lower_rn\\\",\\n CASE\\n WHEN (1.0 + (0.9 * (\\\"n\\\" - 1))) = CAST(1.0 + (0.9 * (\\\"n\\\" - 1)) AS INTEGER)\\n THEN CAST(1.0 + (0.9 * (\\\"n\\\" - 1)) AS INTEGER)\\n ELSE CAST(1.0 + (0.9 * (\\\"n\\\" - 1)) AS INTEGER) + 1\\n END AS \\\"upper_rn\\\"\\n FROM \\\"ranked\\\"\\n),\\n\\\"picked\\\" AS (\\n SELECT\\n p.\\\"group_col\\\",\\n p.\\\"pos\\\",\\n p.\\\"lower_rn\\\",\\n p.\\\"upper_rn\\\",\\n MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"lower_rn\\\" THEN r.\\\"measure_col\\\" END) AS \\\"lower_val\\\",\\n MAX(CASE WHEN r.\\\"rn\\\" = p.\\\"upper_rn\\\" THEN r.\\\"measure_col\\\" END) AS \\\"upper_val\\\"\\n FROM \\\"params\\\" p\\n JOIN \\\"ranked\\\" r\\n ON r.\\\"group_col\\\" = p.\\\"group_col\\\"\\n GROUP BY\\n p.\\\"group_col\\\",\\n p.\\\"pos\\\",\\n p.\\\"lower_rn\\\",\\n p.\\\"upper_rn\\\"\\n)\\nSELECT\\n \\\"group_col\\\" AS \\\"education_level\\\",\\n CASE\\n WHEN \\\"lower_rn\\\" = \\\"upper_rn\\\" THEN \\\"lower_val\\\"\\n ELSE \\\"lower_val\\\" + ((\\\"pos\\\" - \\\"lower_rn\\\") * (\\\"upper_val\\\" - \\\"lower_val\\\"))\\n END AS \\\"percentile_measure\\\"\\nFROM \\\"picked\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite-compatible emulation of PERCENTILE_CONT(0.9) by education_level over city_development_index, casting the TEXT measure to REAL and excluding blank group/measure values.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14688,"cached_input_tokens":13696,"output_tokens":1186,"reasoning_output_tokens":516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..7eeb8c8171257fbfc3bd0e4fb86720dec3e7b84b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_grouped_percentile_point\nWITH \"base\" AS (\n SELECT\n \"education_level\" AS \"group_col\",\n CAST(\"city_development_index\" AS REAL) AS \"measure_col\"\n FROM \"m9\"\n WHERE \"education_level\" IS NOT NULL\n AND \"education_level\" <> ''\n AND \"city_development_index\" IS NOT NULL\n AND \"city_development_index\" <> ''\n),\n\"ranked\" AS (\n SELECT\n \"group_col\",\n \"measure_col\",\n ROW_NUMBER() OVER (PARTITION BY \"group_col\" ORDER BY \"measure_col\") AS \"rn\",\n COUNT(*) OVER (PARTITION BY \"group_col\") AS \"n\"\n FROM \"base\"\n),\n\"params\" AS (\n SELECT DISTINCT\n \"group_col\",\n \"n\",\n (1.0 + (0.9 * (\"n\" - 1))) AS \"pos\",\n CAST(1.0 + (0.9 * (\"n\" - 1)) AS INTEGER) AS \"lower_rn\",\n CASE\n WHEN (1.0 + (0.9 * (\"n\" - 1))) = CAST(1.0 + (0.9 * (\"n\" - 1)) AS INTEGER)\n THEN CAST(1.0 + (0.9 * (\"n\" - 1)) AS INTEGER)\n ELSE CAST(1.0 + (0.9 * (\"n\" - 1)) AS INTEGER) + 1\n END AS \"upper_rn\"\n FROM \"ranked\"\n),\n\"picked\" AS (\n SELECT\n p.\"group_col\",\n p.\"pos\",\n p.\"lower_rn\",\n p.\"upper_rn\",\n MAX(CASE WHEN r.\"rn\" = p.\"lower_rn\" THEN r.\"measure_col\" END) AS \"lower_val\",\n MAX(CASE WHEN r.\"rn\" = p.\"upper_rn\" THEN r.\"measure_col\" END) AS \"upper_val\"\n FROM \"params\" p\n JOIN \"ranked\" r\n ON r.\"group_col\" = p.\"group_col\"\n GROUP BY\n p.\"group_col\",\n p.\"pos\",\n p.\"lower_rn\",\n p.\"upper_rn\"\n)\nSELECT\n \"group_col\" AS \"education_level\",\n CASE\n WHEN \"lower_rn\" = \"upper_rn\" THEN \"lower_val\"\n ELSE \"lower_val\" + ((\"pos\" - \"lower_rn\") * (\"upper_val\" - \"lower_val\"))\n END AS \"percentile_measure\"\nFROM \"picked\"\nORDER BY \"percentile_measure\" DESC;","notes":"SQLite-compatible emulation of PERCENTILE_CONT(0.9) by education_level over city_development_index, casting the TEXT measure to REAL and excluding blank group/measure values."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_102d4ac20150a348/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..8e9e07f5f59cfb5cbdee567d77fd20e3dd7c891a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "0.0", "support": 14381, "support_share": 0.7506524689424784, "support_rank": 1}, {"value_label": "1.0", "support": 4777, "support_share": 0.24934753105752167, "support_rank": 2}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..58ffdd39fabae7fbafc79f5dc485c5158ae76a37 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/generated_sql.sql @@ -0,0 +1,25 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: value_imbalance_profile +-- variant_semantic_role: count_distribution +-- template_id: tpl_cardinality_support_rank_profile +-- query_record_id: v2q_m9_1053c1164ffe9ea3 +-- problem_id: v2p_m9_7ba68fd30abaa0b8 +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "target" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "target" +) +SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank +FROM grouped +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..030968de5a742b3a62e5d982e64fe1b22f554c30 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: value_imbalance_profile\n-- variant_semantic_role: count_distribution\n-- template_id: tpl_cardinality_support_rank_profile\n-- query_record_id: v2q_m9_1053c1164ffe9ea3\n-- problem_id: v2p_m9_7ba68fd30abaa0b8\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"target\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"target\"\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: value_imbalance_profile\\n-- variant_semantic_role: count_distribution\\n-- template_id: tpl_cardinality_support_rank_profile\\n-- query_record_id: v2q_m9_1053c1164ffe9ea3\\n-- problem_id: v2p_m9_7ba68fd30abaa0b8\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"target\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"target\\\"\\n)\\nSELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\\nFROM grouped\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"support_rank\"], \"rows\": [{\"value_label\": \"0.0\", \"support\": 14381, \"support_share\": 0.7506524689424784, \"support_rank\": 1}, {\"value_label\": \"1.0\", \"support\": 4777, \"support_share\": 0.24934753105752167, \"support_rank\": 2}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.74}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..9311e71a443aad1876ddff758223ab1886088104 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.365448+00:00", + "ended_at": "2026-05-19T16:08:56.372052+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_1053c1164ffe9ea3", + "problem_id": "v2p_m9_7ba68fd30abaa0b8", + "dataset_id": "m9", + "template_id": "tpl_cardinality_support_rank_profile", + "template_name": "Cardinality Support Rank Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "value_imbalance_profile", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Support Rank Profile to probe support_rank_profile_consistency with semantic role count_distribution. Focus on group_col=target.", + "bindings": { + "group_col": "target" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=12", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 12, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_1053c1164ffe9ea3.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1053c1164ffe9ea3/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..fb8df980d193c5fb7ead72394c6825203e398947 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=city_development_index. +Result preview: [{"city_development_index": "0.92", "row_count": 5200}, {"city_development_index": "0.624", "row_count": 2702}, {"city_development_index": "0.91", "row_count": 1533}, {"city_development_index": "0.9259999999999999", "row_count": 1336}, {"city_development_index": "0.698", "row_count": 683}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..83eacce3219c201d67dafa75575c021c280f817c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_m9_126d5fc6d858efd2 +-- problem_id: v2p_m9_ab2ed1ee47ce1e48 +-- realization_mode: agent +-- source_kind: agent +SELECT "city_development_index", COUNT(*) AS "row_count" +FROM "m9" +GROUP BY "city_development_index" +ORDER BY "row_count" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..39e24ccf461886854b29373d6517ced70a89d5af --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"city_development_index\", COUNT(*) AS \"row_count\"\nFROM \"m9\"\nGROUP BY \"city_development_index\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"city_development_index\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city_development_index\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"city_development_index\", \"row_count\"], \"rows\": [{\"city_development_index\": \"0.92\", \"row_count\": 5200}, {\"city_development_index\": \"0.624\", \"row_count\": 2702}, {\"city_development_index\": \"0.91\", \"row_count\": 1533}, {\"city_development_index\": \"0.9259999999999999\", \"row_count\": 1336}, {\"city_development_index\": \"0.698\", \"row_count\": 683}, {\"city_development_index\": \"0.897\", \"row_count\": 586}, {\"city_development_index\": \"0.9390000000000001\", \"row_count\": 497}, {\"city_development_index\": \"0.855\", \"row_count\": 431}, {\"city_development_index\": \"0.804\", \"row_count\": 304}, {\"city_development_index\": \"0.924\", \"row_count\": 301}, {\"city_development_index\": \"0.754\", \"row_count\": 280}, {\"city_development_index\": \"0.887\", \"row_count\": 275}, {\"city_development_index\": \"0.884\", \"row_count\": 266}, {\"city_development_index\": \"0.55\", \"row_count\": 247}, {\"city_development_index\": \"0.9129999999999999\", \"row_count\": 197}, {\"city_development_index\": \"0.899\", \"row_count\": 182}, {\"city_development_index\": \"0.802\", \"row_count\": 175}, {\"city_development_index\": \"0.925\", \"row_count\": 171}, {\"city_development_index\": \"0.893\", \"row_count\": 160}, {\"city_development_index\": \"0.878\", \"row_count\": 151}, {\"city_development_index\": \"0.743\", \"row_count\": 146}, {\"city_development_index\": \"0.9229999999999999\", \"row_count\": 143}, {\"city_development_index\": \"0.8959999999999999\", \"row_count\": 140}, {\"city_development_index\": \"0.8270000000000001\", \"row_count\": 137}, {\"city_development_index\": \"0.579\", \"row_count\": 135}, {\"city_development_index\": \"0.767\", \"row_count\": 128}, {\"city_development_index\": \"0.762\", \"row_count\": 128}, {\"city_development_index\": \"0.836\", \"row_count\": 120}, {\"city_development_index\": \"0.682\", \"row_count\": 119}, {\"city_development_index\": \"0.6659999999999999\", \"row_count\": 114}, {\"city_development_index\": \"0.89\", \"row_count\": 113}, {\"city_development_index\": \"0.866\", \"row_count\": 103}, {\"city_development_index\": \"0.6890000000000001\", \"row_count\": 102}, {\"city_development_index\": \"0.915\", \"row_count\": 94}, {\"city_development_index\": \"0.843\", \"row_count\": 94}, {\"city_development_index\": \"0.794\", \"row_count\": 93}, {\"city_development_index\": \"0.527\", \"row_count\": 92}, {\"city_development_index\": \"0.895\", \"row_count\": 86}, {\"city_development_index\": \"0.903\", \"row_count\": 82}, {\"city_development_index\": \"0.7759999999999999\", \"row_count\": 82}, {\"city_development_index\": \"0.9490000000000001\", \"row_count\": 79}, {\"city_development_index\": \"0.738\", \"row_count\": 79}, {\"city_development_index\": \"0.5579999999999999\", \"row_count\": 75}, {\"city_development_index\": \"0.74\", \"row_count\": 67}, {\"city_development_index\": \"0.555\", \"row_count\": 63}, {\"city_development_index\": \"0.789\", \"row_count\": 54}, {\"city_development_index\": \"0.727\", \"row_count\": 53}, {\"city_development_index\": \"0.7659999999999999\", \"row_count\": 49}, {\"city_development_index\": \"0.848\", \"row_count\": 47}, {\"city_development_index\": \"0.691\", \"row_count\": 45}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 8.06}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..d2113353e3e6e08cc7ada910289f49b25580e614 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:32:07.905132+00:00", + "ended_at": "2026-05-19T15:32:19.342145+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_126d5fc6d858efd2", + "problem_id": "v2p_m9_ab2ed1ee47ce1e48", + "dataset_id": "m9", + "template_id": "tpl_clickbench_group_count", + "template_name": "Grouped Count by Category", + "family_id": "subgroup_structure", + "canonical_subitem_id": "subgroup_size_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=city_development_index.", + "bindings": { + "group_col": "city_development_index", + "top_k": 12, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/1", + "binding_index=12" + ], + "template_selection_mode": "rule", + "selected_template_rank": 2, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_126d5fc6d858efd2.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_126d5fc6d858efd2", + "api_calls": 0, + "input_tokens": 14624, + "cached_input_tokens": 13696, + "output_tokens": 327, + "total_tokens": 14951, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11424.96, + "sql_execution_elapsed_ms_total": 8.06, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e5bb860fde87493482c078ababf2818db02c9739 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:32:19.332630+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11424.96, "started_at": "2026-05-19T15:32:07.906876+00:00", "ended_at": "2026-05-19T15:32:19.331865+00:00", "prompt_metrics": {"chars": 9223, "bytes_utf8": 9223, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 315, "bytes_utf8": 315, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14624, "cached_input_tokens": 13696, "output_tokens": 327, "reasoning_output_tokens": 244}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"city_development_index\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city_development_index\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Uses the planned grouped-count template with group_col bound to city_development_index on the single table m9.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..5ddfd9874b88ee23a90d6145d89f7001a54379a8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_126d5fc6d858efd2", + "api_calls": 0, + "input_tokens": 14624, + "cached_input_tokens": 13696, + "output_tokens": 327, + "total_tokens": 14951, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11424.96, + "sql_execution_elapsed_ms_total": 8.06, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_126d5fc6d858efd2/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..b19f28aa8043750f890e0eaa887ecf5caf504049 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "no_enrollment", "support": 13817, "support_share": 0.7212130702578557, "cumulative_support": 13817}, {"value_label": "Full time course", "support": 3757, "support_share": 0.19610606535128927, "cumulative_support": 17574}, {"value_label": "Part time course", "support": 1198, "support_share": 0.06253262344712392, "cumulative_support": 18772}, {"value_label": "", "support": 386, "support_share": 0.020148240943731077, "cumulative_support": 19158}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..f7e844ae0c6dfb4d7ace7f807f72bbe309e795a0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/generated_sql.sql @@ -0,0 +1,28 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: value_imbalance_profile +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_cardinality_distinct_share_profile +-- query_record_id: v2q_m9_12c34fb540176763 +-- problem_id: v2p_m9_b3e4b532fb753d3c +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "enrolled_university" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "enrolled_university" +), ranked AS ( + SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support + FROM grouped +) +SELECT * +FROM ranked +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7d2a7b34be82e92456fd84b81689e7efe84e2500 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: value_imbalance_profile\n-- variant_semantic_role: ranked_signal_view\n-- template_id: tpl_cardinality_distinct_share_profile\n-- query_record_id: v2q_m9_12c34fb540176763\n-- problem_id: v2p_m9_b3e4b532fb753d3c\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"enrolled_university\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"enrolled_university\"\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: value_imbalance_profile\\n-- variant_semantic_role: ranked_signal_view\\n-- template_id: tpl_cardinality_distinct_share_profile\\n-- query_record_id: v2q_m9_12c34fb540176763\\n-- problem_id: v2p_m9_b3e4b532fb753d3c\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"enrolled_university\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"enrolled_university\\\"\\n), ranked AS (\\n SELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\\n FROM grouped\\n)\\nSELECT *\\nFROM ranked\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"cumulative_support\"], \"rows\": [{\"value_label\": \"no_enrollment\", \"support\": 13817, \"support_share\": 0.7212130702578557, \"cumulative_support\": 13817}, {\"value_label\": \"Full time course\", \"support\": 3757, \"support_share\": 0.19610606535128927, \"cumulative_support\": 17574}, {\"value_label\": \"Part time course\", \"support\": 1198, \"support_share\": 0.06253262344712392, \"cumulative_support\": 18772}, {\"value_label\": \"\", \"support\": 386, \"support_share\": 0.020148240943731077, \"cumulative_support\": 19158}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.61}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..c75db9bda646051ecf56021dc8e2be7d166937d1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.197518+00:00", + "ended_at": "2026-05-19T16:08:56.203876+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_12c34fb540176763", + "problem_id": "v2p_m9_b3e4b532fb753d3c", + "dataset_id": "m9", + "template_id": "tpl_cardinality_distinct_share_profile", + "template_name": "Cardinality Distinct Share Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "value_imbalance_profile", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Distinct Share Profile to probe support_rank_profile_consistency with semantic role ranked_signal_view. Focus on group_col=enrolled_university.", + "bindings": { + "group_col": "enrolled_university" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=4", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_12c34fb540176763.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_12c34fb540176763/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..95384b3b6ffe858de8dc3931a52f0eaf6a8222b0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"company_size": "", "total_rows": 5938, "missing_rows": 0, "missing_rate": 0.0}, {"company_size": "50-99", "total_rows": 3083, "missing_rows": 0, "missing_rate": 0.0}, {"company_size": "100-500", "total_rows": 2571, "missing_rows": 0, "missing_rate": 0.0}, {"company_size": "10000+", "total_rows": 2019, "missing_rows": 0, "missing_rate": 0.0}, {"company_size": "10/49", "total_rows": 1471, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..922a8b1340b383c7464591b3a91dcb9cd82151bb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: co_missingness_pattern_consistency +-- intended_facet_id: missing_rate_by_subgroup +-- variant_semantic_role: missing_rate_by_subgroup +-- template_id: tpl_missing_rate_by_subgroup +-- query_record_id: v2q_m9_13f9249ee76c113c +-- problem_id: v2p_m9_2a94b7b211736467 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "company_size", + COUNT(*) AS total_rows, + SUM(CASE WHEN "gender" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "gender" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9" +GROUP BY "company_size" +ORDER BY missing_rate DESC, total_rows DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c99a3eba43e51380999ea8656dd7ba9c0efada79 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: co_missingness_pattern_consistency\n-- intended_facet_id: missing_rate_by_subgroup\n-- variant_semantic_role: missing_rate_by_subgroup\n-- template_id: tpl_missing_rate_by_subgroup\n-- query_record_id: v2q_m9_13f9249ee76c113c\n-- problem_id: v2p_m9_2a94b7b211736467\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"company_size\",\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"gender\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"gender\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\"\nGROUP BY \"company_size\"\nORDER BY missing_rate DESC, total_rows DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: co_missingness_pattern_consistency\\n-- intended_facet_id: missing_rate_by_subgroup\\n-- variant_semantic_role: missing_rate_by_subgroup\\n-- template_id: tpl_missing_rate_by_subgroup\\n-- query_record_id: v2q_m9_13f9249ee76c113c\\n-- problem_id: v2p_m9_2a94b7b211736467\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"company_size\\\",\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"gender\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"gender\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"company_size\\\"\\nORDER BY missing_rate DESC, total_rows DESC;\", \"columns\": [\"company_size\", \"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"company_size\": \"\", \"total_rows\": 5938, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"50-99\", \"total_rows\": 3083, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"100-500\", \"total_rows\": 2571, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"10000+\", \"total_rows\": 2019, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"10/49\", \"total_rows\": 1471, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"1000-4999\", \"total_rows\": 1328, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"<10\", \"total_rows\": 1308, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"500-999\", \"total_rows\": 877, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"5000-9999\", \"total_rows\": 563, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 9, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 8.88}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..02f85008a46bb84ee4fc90db856c3eadb7183e28 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/run_manifest.json @@ -0,0 +1,59 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:55.945844+00:00", + "ended_at": "2026-05-19T16:08:55.955487+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_13f9249ee76c113c", + "problem_id": "v2p_m9_2a94b7b211736467", + "dataset_id": "m9", + "template_id": "tpl_missing_rate_by_subgroup", + "template_name": "Missing Rate by Subgroup", + "family_id": "missingness_structure", + "canonical_subitem_id": "co_missingness_pattern_consistency", + "intended_facet_id": "missing_rate_by_subgroup", + "variant_semantic_role": "missing_rate_by_subgroup", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Missing Rate by Subgroup to probe co_missingness_pattern_consistency with semantic role missing_rate_by_subgroup. Focus on group_col=company_size, missing_col=gender.", + "bindings": { + "missing_col": "gender", + "group_col": "company_size" + }, + "binding_roles": [ + "missing_col", + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY missing_rate DESC, total_rows DESC;", + "notes": [ + "default_facets=missing_rate_by_subgroup,missing_target_interaction", + "template_selection_mode=deterministic", + "problem_index_within_template=2", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_13f9249ee76c113c.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_13f9249ee76c113c/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..b4c9681b8049e3e69287cd4fbb8419c57b10e4f6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": []} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..bdbc2e618290871401580cefb5cf741d5aa407ad --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_m9_199100e1219f2d05 +-- problem_id: v2p_m9_a4c632a454eca2b0 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "enrollee_id", + COUNT(*) AS support, + AVG("city_development_index") AS avg_response +FROM "m9" +GROUP BY "enrollee_id" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6d5b830c7b72fd244f38e81a5016874ed6348307 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_m9_199100e1219f2d05\n-- problem_id: v2p_m9_a4c632a454eca2b0\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"enrollee_id\",\n COUNT(*) AS support,\n AVG(\"city_development_index\") AS avg_response\nFROM \"m9\"\nGROUP BY \"enrollee_id\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_m9_199100e1219f2d05\\n-- problem_id: v2p_m9_a4c632a454eca2b0\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"enrollee_id\\\",\\n COUNT(*) AS support,\\n AVG(\\\"city_development_index\\\") AS avg_response\\nFROM \\\"m9\\\"\\nGROUP BY \\\"enrollee_id\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"enrollee_id\", \"support\", \"avg_response\"], \"rows\": [], \"row_count_returned\": 0, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 14.63}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..1f662b6caf24cb7148736b6e2883cb46bc09ad41 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.372537+00:00", + "ended_at": "2026-05-19T16:08:56.387865+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_199100e1219f2d05", + "problem_id": "v2p_m9_a4c632a454eca2b0", + "dataset_id": "m9", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=city_development_index, key_col=enrollee_id.", + "bindings": { + "key_col": "enrollee_id", + "measure_col": "city_development_index", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=1", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_199100e1219f2d05.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_199100e1219f2d05/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..2301a28fd12bb835527047f1afb29fa7d709cbb9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=company_size, condition_col=education_level. +Result preview: [{"company_size": "10/49", "condition_ratio": 3.3266666666666667}, {"company_size": "", "condition_ratio": 3.280538302277433}, {"company_size": "<10", "condition_ratio": 2.760135135135135}, {"company_size": "50-99", "condition_ratio": 2.5963541666666665}, {"company_size": "5000-9999", "condition_ratio": 2.5211267605633805}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..32fa06ead9872f6e9cf9d00134641b339e0453d8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_m9_19a7dbe29f1919bc +-- problem_id: v2p_m9_9410883061fea888 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT + "company_size", + SUM(CASE WHEN "education_level" = 'Graduate' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "education_level" = 'Masters' THEN 1 ELSE 0 END) AS denominator_count + FROM "m9" + GROUP BY "company_size" +) +SELECT + "company_size", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6cc969ebde89a08705311efcc646170a1544ad42 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_ratio_two_conditions.\nWITH grouped AS (\n SELECT\n \"company_size\",\n SUM(CASE WHEN \"education_level\" = 'Graduate' THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN \"education_level\" = 'Masters' THEN 1 ELSE 0 END) AS denominator_count\n FROM \"m9\"\n GROUP BY \"company_size\"\n)\nSELECT\n \"company_size\",\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions.\\nWITH grouped AS (\\n SELECT\\n \\\"company_size\\\",\\n SUM(CASE WHEN \\\"education_level\\\" = 'Graduate' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"education_level\\\" = 'Masters' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"m9\\\"\\n GROUP BY \\\"company_size\\\"\\n)\\nSELECT\\n \\\"company_size\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\", \"columns\": [\"company_size\", \"condition_ratio\"], \"rows\": [{\"company_size\": \"10/49\", \"condition_ratio\": 3.3266666666666667}, {\"company_size\": \"\", \"condition_ratio\": 3.280538302277433}, {\"company_size\": \"<10\", \"condition_ratio\": 2.760135135135135}, {\"company_size\": \"50-99\", \"condition_ratio\": 2.5963541666666665}, {\"company_size\": \"5000-9999\", \"condition_ratio\": 2.5211267605633805}, {\"company_size\": \"100-500\", \"condition_ratio\": 2.4567164179104477}, {\"company_size\": \"500-999\", \"condition_ratio\": 2.429787234042553}, {\"company_size\": \"10000+\", \"condition_ratio\": 2.130508474576271}, {\"company_size\": \"1000-4999\", \"condition_ratio\": 2.0}], \"row_count_returned\": 9, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 23.94}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..6242b9ec3d05541dff1ed3c275b7e93f1a719a11 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:41:41.671641+00:00", + "ended_at": "2026-05-19T15:41:55.399633+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_19a7dbe29f1919bc", + "problem_id": "v2p_m9_9410883061fea888", + "dataset_id": "m9", + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "contrastive_conditional_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=company_size, condition_col=education_level.", + "bindings": { + "group_col": "company_size", + "condition_col": "education_level", + "condition_value": "Graduate", + "positive_value": "Graduate", + "negative_value": "Masters", + "top_k": 13, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/1", + "binding_index=43" + ], + "template_selection_mode": "rule", + "selected_template_rank": 4, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_19a7dbe29f1919bc.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_19a7dbe29f1919bc", + "api_calls": 0, + "input_tokens": 14855, + "cached_input_tokens": 13696, + "output_tokens": 684, + "total_tokens": 15539, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13697.45, + "sql_execution_elapsed_ms_total": 23.94, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f4a3b289cbef96080566e5215cab8f3745551bf1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:41:55.372521+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13697.45, "started_at": "2026-05-19T15:41:41.673394+00:00", "ended_at": "2026-05-19T15:41:55.370881+00:00", "prompt_metrics": {"chars": 10128, "bytes_utf8": 10128, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 645, "bytes_utf8": 645, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14855, "cached_input_tokens": 13696, "output_tokens": 684, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions.\\nWITH grouped AS (\\n SELECT\\n \\\"company_size\\\",\\n SUM(CASE WHEN \\\"education_level\\\" = 'Graduate' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"education_level\\\" = 'Masters' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"m9\\\"\\n GROUP BY \\\"company_size\\\"\\n)\\nSELECT\\n \\\"company_size\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Computes the Graduate-to-Masters ratio within each company_size group using the requested template and bindings.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..27f49d659a091648a837e84f1431c2081e63d5e2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_19a7dbe29f1919bc", + "api_calls": 0, + "input_tokens": 14855, + "cached_input_tokens": 13696, + "output_tokens": 684, + "total_tokens": 15539, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13697.45, + "sql_execution_elapsed_ms_total": 23.94, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_19a7dbe29f1919bc/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..d3adc9820f69c76548b6d9b23808facc68747e51 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=experience, measure_col=enrollee_id. +Result preview: [{"experience": "18", "percentile_measure": 31089.699999999997}, {"experience": "19", "percentile_measure": 30641.0}, {"experience": "2", "percentile_measure": 30423.8}, {"experience": "5", "percentile_measure": 30394.600000000002}, {"experience": "1", "percentile_measure": 30293.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..a84c620b3376ece1e67a7f4676216ef71c5a495a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/generated_sql.sql @@ -0,0 +1,56 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_m9_1aaf6b7ff4c9d23d +-- problem_id: v2p_m9_a55194f956b65d09 +-- realization_mode: agent +-- source_kind: agent +WITH "ordered" AS ( + SELECT + "experience", + CAST("enrollee_id" AS REAL) AS "measure_value", + ROW_NUMBER() OVER ( + PARTITION BY "experience" + ORDER BY CAST("enrollee_id" AS REAL) + ) AS "rn", + COUNT(*) OVER (PARTITION BY "experience") AS "cnt" + FROM "m9" + WHERE "experience" IS NOT NULL + AND "experience" <> '' + AND "enrollee_id" IS NOT NULL + AND "enrollee_id" <> '' +), +"bounds" AS ( + SELECT + "experience", + "measure_value", + "rn", + "cnt", + 1 + (("cnt" - 1) * 0.9) AS "pos" + FROM "ordered" +), +"picked" AS ( + SELECT + "experience", + "cnt", + MAX(CASE WHEN "rn" = CAST("pos" AS INTEGER) THEN "measure_value" END) AS "lower_value", + MAX(CASE WHEN "rn" = CAST("pos" AS INTEGER) + 1 THEN "measure_value" END) AS "upper_value", + MAX("pos") AS "pos" + FROM "bounds" + GROUP BY "experience", "cnt" +) +SELECT + "experience", + CASE + WHEN "cnt" = 1 THEN "lower_value" + WHEN CAST("pos" AS INTEGER) = "pos" THEN "lower_value" + ELSE "lower_value" + ("pos" - CAST("pos" AS INTEGER)) * ("upper_value" - "lower_value") + END AS "percentile_measure" +FROM "picked" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..21f5c525e6692244eca6dc7daa3974aad61d6522 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n SELECT\n \"experience\",\n CAST(\"enrollee_id\" AS REAL) AS \"measure_value\",\n ROW_NUMBER() OVER (\n PARTITION BY \"experience\"\n ORDER BY CAST(\"enrollee_id\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (PARTITION BY \"experience\") AS \"cnt\"\n FROM \"m9\"\n WHERE \"experience\" IS NOT NULL\n AND \"experience\" <> ''\n AND \"enrollee_id\" IS NOT NULL\n AND \"enrollee_id\" <> ''\n),\n\"bounds\" AS (\n SELECT\n \"experience\",\n \"measure_value\",\n \"rn\",\n \"cnt\",\n 1 + ((\"cnt\" - 1) * 0.9) AS \"pos\"\n FROM \"ordered\"\n),\n\"picked\" AS (\n SELECT\n \"experience\",\n \"cnt\",\n MAX(CASE WHEN \"rn\" = CAST(\"pos\" AS INTEGER) THEN \"measure_value\" END) AS \"lower_value\",\n MAX(CASE WHEN \"rn\" = CAST(\"pos\" AS INTEGER) + 1 THEN \"measure_value\" END) AS \"upper_value\",\n MAX(\"pos\") AS \"pos\"\n FROM \"bounds\"\n GROUP BY \"experience\", \"cnt\"\n)\nSELECT\n \"experience\",\n CASE\n WHEN \"cnt\" = 1 THEN \"lower_value\"\n WHEN CAST(\"pos\" AS INTEGER) = \"pos\" THEN \"lower_value\"\n ELSE \"lower_value\" + (\"pos\" - CAST(\"pos\" AS INTEGER)) * (\"upper_value\" - \"lower_value\")\n END AS \"percentile_measure\"\nFROM \"picked\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"experience\\\",\\n CAST(\\\"enrollee_id\\\" AS REAL) AS \\\"measure_value\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"experience\\\"\\n ORDER BY CAST(\\\"enrollee_id\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"experience\\\") AS \\\"cnt\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"experience\\\" IS NOT NULL\\n AND \\\"experience\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\n),\\n\\\"bounds\\\" AS (\\n SELECT\\n \\\"experience\\\",\\n \\\"measure_value\\\",\\n \\\"rn\\\",\\n \\\"cnt\\\",\\n 1 + ((\\\"cnt\\\" - 1) * 0.9) AS \\\"pos\\\"\\n FROM \\\"ordered\\\"\\n),\\n\\\"picked\\\" AS (\\n SELECT\\n \\\"experience\\\",\\n \\\"cnt\\\",\\n MAX(CASE WHEN \\\"rn\\\" = CAST(\\\"pos\\\" AS INTEGER) THEN \\\"measure_value\\\" END) AS \\\"lower_value\\\",\\n MAX(CASE WHEN \\\"rn\\\" = CAST(\\\"pos\\\" AS INTEGER) + 1 THEN \\\"measure_value\\\" END) AS \\\"upper_value\\\",\\n MAX(\\\"pos\\\") AS \\\"pos\\\"\\n FROM \\\"bounds\\\"\\n GROUP BY \\\"experience\\\", \\\"cnt\\\"\\n)\\nSELECT\\n \\\"experience\\\",\\n CASE\\n WHEN \\\"cnt\\\" = 1 THEN \\\"lower_value\\\"\\n WHEN CAST(\\\"pos\\\" AS INTEGER) = \\\"pos\\\" THEN \\\"lower_value\\\"\\n ELSE \\\"lower_value\\\" + (\\\"pos\\\" - CAST(\\\"pos\\\" AS INTEGER)) * (\\\"upper_value\\\" - \\\"lower_value\\\")\\n END AS \\\"percentile_measure\\\"\\nFROM \\\"picked\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"experience\", \"percentile_measure\"], \"rows\": [{\"experience\": \"18\", \"percentile_measure\": 31089.699999999997}, {\"experience\": \"19\", \"percentile_measure\": 30641.0}, {\"experience\": \"2\", \"percentile_measure\": 30423.8}, {\"experience\": \"5\", \"percentile_measure\": 30394.600000000002}, {\"experience\": \"1\", \"percentile_measure\": 30293.0}, {\"experience\": \"9\", \"percentile_measure\": 30280.8}, {\"experience\": \"11\", \"percentile_measure\": 30251.600000000002}, {\"experience\": \"13\", \"percentile_measure\": 30231.8}, {\"experience\": \"6\", \"percentile_measure\": 30207.0}, {\"experience\": \"4\", \"percentile_measure\": 30194.6}, {\"experience\": \"10\", \"percentile_measure\": 30165.6}, {\"experience\": \">20\", \"percentile_measure\": 30153.5}, {\"experience\": \"17\", \"percentile_measure\": 30137.100000000006}, {\"experience\": \"3\", \"percentile_measure\": 29964.100000000002}, {\"experience\": \"15\", \"percentile_measure\": 29889.5}, {\"experience\": \"7\", \"percentile_measure\": 29879.500000000004}, {\"experience\": \"16\", \"percentile_measure\": 29877.300000000003}, {\"experience\": \"<1\", \"percentile_measure\": 29840.8}, {\"experience\": \"12\", \"percentile_measure\": 29725.8}, {\"experience\": \"8\", \"percentile_measure\": 29639.8}, {\"experience\": \"14\", \"percentile_measure\": 29368.5}, {\"experience\": \"20\", \"percentile_measure\": 28812.2}], \"row_count_returned\": 22, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 55.41}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..f6d3e599945525594d92ca07eb3a045bd5ad2bc2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:56:41.571320+00:00", + "ended_at": "2026-05-19T15:57:20.603793+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_1aaf6b7ff4c9d23d", + "problem_id": "v2p_m9_a55194f956b65d09", + "dataset_id": "m9", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=experience, measure_col=enrollee_id.", + "bindings": { + "group_col": "experience", + "measure_col": "enrollee_id", + "top_k": 15, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=2/2", + "binding_index=90" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 7, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_1aaf6b7ff4c9d23d.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_1aaf6b7ff4c9d23d", + "api_calls": 0, + "input_tokens": 14686, + "cached_input_tokens": 13696, + "output_tokens": 2004, + "total_tokens": 16690, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 37969.48, + "sql_execution_elapsed_ms_total": 55.41, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2d4a6cf1b08d571497ccde7792c4580bea616932 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:56:44.698706+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3124.15, "started_at": "2026-05-19T15:56:41.573451+00:00", "ended_at": "2026-05-19T15:56:44.697628+00:00", "prompt_metrics": {"chars": 9474, "bytes_utf8": 9474, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f4-21d5-7190-9c5c-00ef0d42b2f1\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:57:20.546401+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 34845.33, "started_at": "2026-05-19T15:56:45.700229+00:00", "ended_at": "2026-05-19T15:57:20.545596+00:00", "prompt_metrics": {"chars": 9474, "bytes_utf8": 9474, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 1553, "bytes_utf8": 1555, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14686, "cached_input_tokens": 13696, "output_tokens": 2004, "reasoning_output_tokens": 1537}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"experience\\\",\\n CAST(\\\"enrollee_id\\\" AS REAL) AS \\\"measure_value\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"experience\\\"\\n ORDER BY CAST(\\\"enrollee_id\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"experience\\\") AS \\\"cnt\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"experience\\\" IS NOT NULL\\n AND \\\"experience\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\n),\\n\\\"bounds\\\" AS (\\n SELECT\\n \\\"experience\\\",\\n \\\"measure_value\\\",\\n \\\"rn\\\",\\n \\\"cnt\\\",\\n 1 + ((\\\"cnt\\\" - 1) * 0.9) AS \\\"pos\\\"\\n FROM \\\"ordered\\\"\\n),\\n\\\"picked\\\" AS (\\n SELECT\\n \\\"experience\\\",\\n \\\"cnt\\\",\\n MAX(CASE WHEN \\\"rn\\\" = CAST(\\\"pos\\\" AS INTEGER) THEN \\\"measure_value\\\" END) AS \\\"lower_value\\\",\\n MAX(CASE WHEN \\\"rn\\\" = CAST(\\\"pos\\\" AS INTEGER) + 1 THEN \\\"measure_value\\\" END) AS \\\"upper_value\\\",\\n MAX(\\\"pos\\\") AS \\\"pos\\\"\\n FROM \\\"bounds\\\"\\n GROUP BY \\\"expe"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..9ff34fd1ff771d75f57b9cc0399ccf07aeb8947e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1aaf6b7ff4c9d23d/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_1aaf6b7ff4c9d23d", + "api_calls": 0, + "input_tokens": 14686, + "cached_input_tokens": 13696, + "output_tokens": 2004, + "total_tokens": 16690, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 37969.48, + "sql_execution_elapsed_ms_total": 55.41, + "conversation_log_path": 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"assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 843, "bytes_utf8": 843, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14771, "cached_input_tokens": 12032, "output_tokens": 1502, "reasoning_output_tokens": 1277}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..1660d89cf26f47065fb1792527cf74cbe2d9100d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_1b47d3df01de1317", + "api_calls": 0, + "input_tokens": 14771, + "cached_input_tokens": 12032, + "output_tokens": 1502, + "total_tokens": 16273, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 28826.27, + "sql_execution_elapsed_ms_total": 34.85, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..d06e147a33662c3ecde156b479c00dc4da287d6a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:38:09.517356+00:00", + "ended_at": "2026-05-19T15:38:38.343663+00:00", + "elapsed_ms": 28826.27, + "prompt_metrics": { + "chars": 9743, + "bytes_utf8": 9743, + "lines": 266, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1243, + "bytes_utf8": 1243, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 843, + "bytes_utf8": 843, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14771, + "cached_input_tokens": 12032, + "output_tokens": 1502, + "reasoning_output_tokens": 1277 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..d0a18a8273148b6a3772d056897ce7edc055701e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,266 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "required_roles": [ + "group_col", + "item_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=company_size, measure_col=city_development_index.", + "planned_template_id": "tpl_tpcds_within_group_share", + "bindings": { + "group_col": "company_size", + "measure_col": "city_development_index", + "item_col": "city_development_index", + "top_k": 16, + "top_n": 7, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..0f78a121d3755acd8f4ad2b5cb6758a6ab6dd8fb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40e3-2a05-7fd2-98a0-3178f7f4c633"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"company_size\\\",\\n \\\"city_development_index\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"city_development_index\\\" AS REAL))) OVER (PARTITION BY \\\"company_size\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nWHERE \\\"company_size\\\" IS NOT NULL\\n AND \\\"company_size\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\nGROUP BY \\\"company_size\\\", \\\"city_development_index\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Uses the planned Within-Group Share of Total template with group_col=\\\"company_size\\\" and item_col/measure_col=\\\"city_development_index\\\". The measure is cast from TEXT to REAL, and blank values are excluded before aggregation.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14771,"cached_input_tokens":12032,"output_tokens":1502,"reasoning_output_tokens":1277}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..380bd4082d6322306a9306a05e532a956efe7902 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"company_size\",\n \"city_development_index\",\n SUM(CAST(\"city_development_index\" AS REAL)) AS total_measure,\n SUM(CAST(\"city_development_index\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"city_development_index\" AS REAL))) OVER (PARTITION BY \"company_size\") AS share_within_group\nFROM \"m9\"\nWHERE \"company_size\" IS NOT NULL\n AND \"company_size\" <> ''\n AND \"city_development_index\" IS NOT NULL\n AND \"city_development_index\" <> ''\nGROUP BY \"company_size\", \"city_development_index\"\nORDER BY share_within_group DESC;","notes":"Uses the planned Within-Group Share of Total template with group_col=\"company_size\" and item_col/measure_col=\"city_development_index\". The measure is cast from TEXT to REAL, and blank values are excluded before aggregation."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1b47d3df01de1317/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..c94be639816061c04a9e4982ba8c10315a4c452b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=enrolled_university, measure_col=enrollee_id. +Result preview: [{"enrolled_university": "no_enrollment", "experience": ">20", "total_measure": 51028374, "share_within_group": 22.188326682007784}, {"enrolled_university": "Full time course", "experience": "3", "total_measure": 8634558, "share_within_group": 13.218084919099955}, {"enrolled_university": "", "experience": "2", "total_measure": 902064, "share_within_group": 13.116401696345145}, {"enrolled_university": "Full time course", "experience": "4", "total_measure": 8139132, "share_within_group": 12.459669382470285}, {"enrolled_university": "Full time course", "experience": "2", "total_measure": 7907783, "share_within_group": 12.105512200603087}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..bf2863f2fb8176ea5faeb5615d347a4964def7d3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_m9_1fcfeb0362f1c7eb +-- problem_id: v2p_m9_d2a6390306a85493 +-- realization_mode: agent +-- source_kind: agent +SELECT "enrolled_university", "experience", + SUM(CAST("enrollee_id" AS NUMERIC)) AS total_measure, + SUM(CAST("enrollee_id" AS NUMERIC)) * 100.0 / SUM(SUM(CAST("enrollee_id" AS NUMERIC))) OVER (PARTITION BY "enrolled_university") AS share_within_group +FROM "m9" +GROUP BY "enrolled_university", "experience" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8e5c130d60cdd74e5f4cba4bd7d142f666db7ad4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT \"enrolled_university\", \"experience\",\n SUM(CAST(\"enrollee_id\" AS NUMERIC)) AS total_measure,\n SUM(CAST(\"enrollee_id\" AS NUMERIC)) * 100.0 / SUM(SUM(CAST(\"enrollee_id\" AS NUMERIC))) OVER (PARTITION BY \"enrolled_university\") AS share_within_group\nFROM \"m9\"\nGROUP BY \"enrolled_university\", \"experience\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"enrolled_university\\\", \\\"experience\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS NUMERIC)) AS total_measure,\\n SUM(CAST(\\\"enrollee_id\\\" AS NUMERIC)) * 100.0 / SUM(SUM(CAST(\\\"enrollee_id\\\" AS NUMERIC))) OVER (PARTITION BY \\\"enrolled_university\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nGROUP BY \\\"enrolled_university\\\", \\\"experience\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"enrolled_university\", \"experience\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"enrolled_university\": \"no_enrollment\", \"experience\": \">20\", \"total_measure\": 51028374, \"share_within_group\": 22.188326682007784}, {\"enrolled_university\": \"Full time course\", \"experience\": \"3\", \"total_measure\": 8634558, \"share_within_group\": 13.218084919099955}, {\"enrolled_university\": \"\", \"experience\": \"2\", \"total_measure\": 902064, \"share_within_group\": 13.116401696345145}, {\"enrolled_university\": \"Full time course\", \"experience\": \"4\", \"total_measure\": 8139132, \"share_within_group\": 12.459669382470285}, {\"enrolled_university\": \"Full time course\", \"experience\": \"2\", \"total_measure\": 7907783, \"share_within_group\": 12.105512200603087}, {\"enrolled_university\": \"\", \"experience\": \"3\", \"total_measure\": 794923, \"share_within_group\": 11.558525099841887}, {\"enrolled_university\": \"Full time course\", \"experience\": \"5\", \"total_measure\": 7179044, \"share_within_group\": 10.989932921865256}, {\"enrolled_university\": \"Part time course\", \"experience\": \"3\", \"total_measure\": 2268940, \"share_within_group\": 10.743876124615023}, {\"enrolled_university\": \"Part time course\", \"experience\": \"5\", \"total_measure\": 2086963, \"share_within_group\": 9.882179321028737}, {\"enrolled_university\": \"\", \"experience\": \"4\", \"total_measure\": 620446, \"share_within_group\": 9.021553866344917}, {\"enrolled_university\": \"Part time course\", \"experience\": \"4\", \"total_measure\": 1866327, \"share_within_group\": 8.837424566548425}, {\"enrolled_university\": \"\", \"experience\": \"6\", \"total_measure\": 601014, \"share_within_group\": 8.73900416059967}, {\"enrolled_university\": \"Part time course\", \"experience\": \"6\", \"total_measure\": 1828668, \"share_within_group\": 8.65910181188022}, {\"enrolled_university\": \"Full time course\", \"experience\": \"6\", \"total_measure\": 5569551, \"share_within_group\": 8.52606445856963}, {\"enrolled_university\": \"\", \"experience\": \">20\", \"total_measure\": 559783, \"share_within_group\": 8.13948754277432}, {\"enrolled_university\": \"Part time course\", \"experience\": \"7\", \"total_measure\": 1624570, \"share_within_group\": 7.692657732582539}, {\"enrolled_university\": \"Part time course\", \"experience\": \"2\", \"total_measure\": 1592386, \"share_within_group\": 7.5402601772507065}, {\"enrolled_university\": \"Full time course\", \"experience\": \"7\", \"total_measure\": 4516309, \"share_within_group\": 6.913724580099571}, {\"enrolled_university\": \"\", \"experience\": \"5\", \"total_measure\": 453501, \"share_within_group\": 6.594101178734791}, {\"enrolled_university\": \"no_enrollment\", \"experience\": \"5\", \"total_measure\": 14842302, \"share_within_group\": 6.453778940497251}, {\"enrolled_university\": \"Part time course\", \"experience\": \">20\", \"total_measure\": 1354500, \"share_within_group\": 6.413823287874976}, {\"enrolled_university\": \"Full time course\", \"experience\": \"1\", \"total_measure\": 3863125, \"share_within_group\": 5.913807551364878}, {\"enrolled_university\": \"no_enrollment\", \"experience\": \"4\", \"total_measure\": 13306569, \"share_within_group\": 5.786006428280031}, {\"enrolled_university\": \"\", \"experience\": \"<1\", \"total_measure\": 382931, \"share_within_group\": 5.567982779473677}, {\"enrolled_university\": \"no_enrollment\", \"experience\": \"6\", \"total_measure\": 12682375, \"share_within_group\": 5.514592324727581}, {\"enrolled_university\": \"no_enrollment\", \"experience\": \"10\", \"total_measure\": 12280841, \"share_within_group\": 5.339995980232393}, {\"enrolled_university\": \"Part time course\", \"experience\": \"10\", \"total_measure\": 1107897, \"share_within_group\": 5.246109692998761}, {\"enrolled_university\": \"no_enrollment\", \"experience\": \"3\", \"total_measure\": 11970822, \"share_within_group\": 5.205192491302306}, {\"enrolled_university\": \"no_enrollment\", \"experience\": \"9\", \"total_measure\": 11734447, \"share_within_group\": 5.102411130495873}, {\"enrolled_university\": \"\", \"experience\": \"9\", \"total_measure\": 350823, \"share_within_group\": 5.101118537395233}, {\"enrolled_university\": \"Full time course\", \"experience\": \"9\", \"total_measure\": 3305934, \"share_within_group\": 5.060839981495264}, {\"enrolled_university\": \"Part time course\", \"experience\": \"9\", \"total_measure\": 1066162, \"share_within_group\": 5.048486278514108}, {\"enrolled_university\": \"\", \"experience\": \"1\", \"total_measure\": 341275, \"share_within_group\": 4.96228647736767}, {\"enrolled_university\": \"Full time course\", \"experience\": \"<1\", \"total_measure\": 3223299, \"share_within_group\": 4.934339418607179}, {\"enrolled_university\": \"no_enrollment\", \"experience\": \"7\", \"total_measure\": 10926650, \"share_within_group\": 4.7511621620543965}, {\"enrolled_university\": \"\", \"experience\": \"8\", \"total_measure\": 297788, \"share_within_group\": 4.329966641337231}, {\"enrolled_university\": \"Part time course\", \"experience\": \"8\", \"total_measure\": 910399, \"share_within_group\": 4.310917908791502}, {\"enrolled_university\": \"Full time course\", \"experience\": \"8\", \"total_measure\": 2764807, \"share_within_group\": 4.232463747527318}, {\"enrolled_university\": \"\", \"experience\": \"10\", \"total_measure\": 289132, \"share_within_group\": 4.2041046480822475}, {\"enrolled_university\": \"Part time course\", \"experience\": \"11\", \"total_measure\": 869141, \"share_within_group\": 4.115553182906567}, {\"enrolled_university\": \"no_enrollment\", \"experience\": \"2\", \"total_measure\": 9462079, \"share_within_group\": 4.114332546495907}, {\"enrolled_university\": \"no_enrollment\", \"experience\": \"15\", \"total_measure\": 9391128, \"share_within_group\": 4.083481397556395}, {\"enrolled_university\": \"Full time course\", \"experience\": \"10\", \"total_measure\": 2663696, \"share_within_group\": 4.077679474347948}, {\"enrolled_university\": \"\", \"experience\": \"7\", \"total_measure\": 270534, \"share_within_group\": 3.933681663960692}, {\"enrolled_university\": \"no_enrollment\", \"experience\": \"8\", \"total_measure\": 9029058, \"share_within_group\": 3.926044920318171}, {\"enrolled_university\": \"Part time course\", \"experience\": \"1\", \"total_measure\": 820374, \"share_within_group\": 3.8846318685619385}, {\"enrolled_university\": \"no_enrollment\", \"experience\": \"11\", \"total_measure\": 8890611, \"share_within_group\": 3.8658449369884273}, {\"enrolled_university\": \"no_enrollment\", \"experience\": \"16\", \"total_measure\": 7916648, \"share_within_group\": 3.4423431177811694}, {\"enrolled_university\": \"Part time course\", \"experience\": \"<1\", \"total_measure\": 719403, \"share_within_group\": 3.406514370444534}, {\"enrolled_university\": \"no_enrollment\", \"experience\": \"14\", \"total_measure\": 7743994, \"share_within_group\": 3.3672691333552622}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 23.47}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..d03881fb8ec0147b6b84dadc920933fa6d969560 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:35:41.739581+00:00", + "ended_at": "2026-05-19T15:35:57.402963+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_1fcfeb0362f1c7eb", + "problem_id": "v2p_m9_d2a6390306a85493", + "dataset_id": "m9", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=enrolled_university, measure_col=enrollee_id.", + "bindings": { + "group_col": "enrolled_university", + "measure_col": "enrollee_id", + "item_col": "experience", + "top_k": 12, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/2", + "binding_index=27" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_1fcfeb0362f1c7eb.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_1fcfeb0362f1c7eb", + "api_calls": 0, + "input_tokens": 14770, + "cached_input_tokens": 12032, + "output_tokens": 877, + "total_tokens": 15647, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15633.23, + "sql_execution_elapsed_ms_total": 23.47, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8e51eae67570636b371c73e38598baec36be20f8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:35:57.377341+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15633.23, "started_at": "2026-05-19T15:35:41.743027+00:00", "ended_at": "2026-05-19T15:35:57.376290+00:00", "prompt_metrics": {"chars": 9720, "bytes_utf8": 9720, "lines": 266, "estimated_tokens": null}, "response_metrics": {"chars": 651, "bytes_utf8": 651, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14770, "cached_input_tokens": 12032, "output_tokens": 877, "reasoning_output_tokens": 694}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"enrolled_university\\\", \\\"experience\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS NUMERIC)) AS total_measure,\\n SUM(CAST(\\\"enrollee_id\\\" AS NUMERIC)) * 100.0 / SUM(SUM(CAST(\\\"enrollee_id\\\" AS NUMERIC))) OVER (PARTITION BY \\\"enrolled_university\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nGROUP BY \\\"enrolled_university\\\", \\\"experience\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Applied the Within-Group Share of Total template with group_col=\\\"enrolled_university\\\", item_col=\\\"experience\\\", and measure_col=\\\"enrollee_id\\\". CAST is used because the schema stores \\\"enrollee_id\\\" as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..28a9e41c424a1586490989c94e0fad8f31fc6e02 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_1fcfeb0362f1c7eb", + "api_calls": 0, + "input_tokens": 14770, + "cached_input_tokens": 12032, + "output_tokens": 877, + "total_tokens": 15647, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15633.23, + "sql_execution_elapsed_ms_total": 23.47, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_1fcfeb0362f1c7eb/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3c1fbbfc502ce3527f253e3a3e071a2157c198f3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"total_rows": 19158, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..8ce3fc615a5f1b719019c46fb4542d758452b600 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: marginal_missing_rate_consistency +-- intended_facet_id: missing_indicator_distribution +-- variant_semantic_role: missing_indicator_view +-- template_id: tpl_missing_marginal_rate_profile +-- query_record_id: v2q_m9_23398cbc8b31c740 +-- problem_id: v2p_m9_e4446598547fd0b2 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + COUNT(*) AS total_rows, + SUM(CASE WHEN "company_size" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "company_size" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3f4c73112e8e652413d5dfda96870672a653c83e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: marginal_missing_rate_consistency\n-- intended_facet_id: missing_indicator_distribution\n-- variant_semantic_role: missing_indicator_view\n-- template_id: tpl_missing_marginal_rate_profile\n-- query_record_id: v2q_m9_23398cbc8b31c740\n-- problem_id: v2p_m9_e4446598547fd0b2\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"company_size\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"company_size\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\";", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: marginal_missing_rate_consistency\\n-- intended_facet_id: missing_indicator_distribution\\n-- variant_semantic_role: missing_indicator_view\\n-- template_id: tpl_missing_marginal_rate_profile\\n-- query_record_id: v2q_m9_23398cbc8b31c740\\n-- problem_id: v2p_m9_e4446598547fd0b2\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"company_size\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"company_size\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\";\", \"columns\": [\"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"total_rows\": 19158, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.06}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..91becff960abfe22cb539c1449dd37509559bab3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:55.922906+00:00", + "ended_at": "2026-05-19T16:08:55.926602+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_23398cbc8b31c740", + "problem_id": "v2p_m9_e4446598547fd0b2", + "dataset_id": "m9", + "template_id": "tpl_missing_marginal_rate_profile", + "template_name": "Marginal Missing Rate Profile", + "family_id": "missingness_structure", + "canonical_subitem_id": "marginal_missing_rate_consistency", + "intended_facet_id": "missing_indicator_distribution", + "variant_semantic_role": "missing_indicator_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Marginal Missing Rate Profile to probe marginal_missing_rate_consistency with semantic role missing_indicator_view. Focus on missing_col=company_size.", + "bindings": { + "missing_col": "company_size" + }, + "binding_roles": [ + "missing_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table};", + "notes": [ + "default_facets=missing_indicator_distribution", + "template_selection_mode=deterministic", + "problem_index_within_template=6", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_23398cbc8b31c740.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_23398cbc8b31c740/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..e41c4e367c530a823bfeeed72ce467554d84b092 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"experience": ">20", "total_rows": 3286, "missing_rows": 0, "missing_rate": 0.0}, {"experience": "5", "total_rows": 1430, "missing_rows": 0, "missing_rate": 0.0}, {"experience": "4", "total_rows": 1403, "missing_rows": 0, "missing_rate": 0.0}, {"experience": "3", "total_rows": 1354, "missing_rows": 0, "missing_rate": 0.0}, {"experience": "6", "total_rows": 1216, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..5bc23d2a01ec8d5a564b61ed7f8ce5bc0b96623e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: co_missingness_pattern_consistency +-- intended_facet_id: missing_rate_by_subgroup +-- variant_semantic_role: missing_rate_by_subgroup +-- template_id: tpl_missing_rate_by_subgroup +-- query_record_id: v2q_m9_24d22f21f606121d +-- problem_id: v2p_m9_7f6a9aeb8ec62d34 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "experience", + COUNT(*) AS total_rows, + SUM(CASE WHEN "company_type" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "company_type" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9" +GROUP BY "experience" +ORDER BY missing_rate DESC, total_rows DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..cb0c3bde2678e6f17950c7ea07d7b12a089b4927 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: co_missingness_pattern_consistency\n-- intended_facet_id: missing_rate_by_subgroup\n-- variant_semantic_role: missing_rate_by_subgroup\n-- template_id: tpl_missing_rate_by_subgroup\n-- query_record_id: v2q_m9_24d22f21f606121d\n-- problem_id: v2p_m9_7f6a9aeb8ec62d34\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"experience\",\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"company_type\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"company_type\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\"\nGROUP BY \"experience\"\nORDER BY missing_rate DESC, total_rows DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: co_missingness_pattern_consistency\\n-- intended_facet_id: missing_rate_by_subgroup\\n-- variant_semantic_role: missing_rate_by_subgroup\\n-- template_id: tpl_missing_rate_by_subgroup\\n-- query_record_id: v2q_m9_24d22f21f606121d\\n-- problem_id: v2p_m9_7f6a9aeb8ec62d34\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"experience\\\",\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"company_type\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"company_type\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\"\\nORDER BY missing_rate DESC, total_rows DESC;\", \"columns\": [\"experience\", \"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"experience\": \">20\", \"total_rows\": 3286, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"5\", \"total_rows\": 1430, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"4\", \"total_rows\": 1403, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"3\", \"total_rows\": 1354, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"6\", \"total_rows\": 1216, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"2\", \"total_rows\": 1127, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"7\", \"total_rows\": 1028, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"10\", \"total_rows\": 985, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"9\", \"total_rows\": 980, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"8\", \"total_rows\": 802, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"15\", \"total_rows\": 686, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"11\", \"total_rows\": 664, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"14\", \"total_rows\": 586, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"1\", \"total_rows\": 549, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"<1\", \"total_rows\": 522, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"16\", \"total_rows\": 508, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"12\", \"total_rows\": 494, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"13\", \"total_rows\": 399, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"17\", \"total_rows\": 342, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"19\", \"total_rows\": 304, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"18\", \"total_rows\": 280, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"20\", \"total_rows\": 148, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"experience\": \"\", \"total_rows\": 65, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 23, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.68}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..6af9e6f87e31f6190fa206543bda909087556407 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/run_manifest.json @@ -0,0 +1,59 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.036756+00:00", + "ended_at": "2026-05-19T16:08:56.047171+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_24d22f21f606121d", + "problem_id": "v2p_m9_7f6a9aeb8ec62d34", + "dataset_id": "m9", + "template_id": "tpl_missing_rate_by_subgroup", + "template_name": "Missing Rate by Subgroup", + "family_id": "missingness_structure", + "canonical_subitem_id": "co_missingness_pattern_consistency", + "intended_facet_id": "missing_rate_by_subgroup", + "variant_semantic_role": "missing_rate_by_subgroup", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Missing Rate by Subgroup to probe co_missingness_pattern_consistency with semantic role missing_rate_by_subgroup. Focus on group_col=experience, missing_col=company_type.", + "bindings": { + "missing_col": "company_type", + "group_col": "experience" + }, + "binding_roles": [ + "missing_col", + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY missing_rate DESC, total_rows DESC;", + "notes": [ + "default_facets=missing_rate_by_subgroup,missing_target_interaction", + "template_selection_mode=deterministic", + "problem_index_within_template=11", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 11, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_24d22f21f606121d.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24d22f21f606121d/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..8bda2a4f8563271e409abc256d3bf25070e89326 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"city": "city_103", "support": 4355, "avg_response": 17095.4429391504}, {"city": "city_21", "support": 2702, "avg_response": 17957.994448556623}, {"city": "city_16", "support": 1533, "avg_response": 17052.47553816047}, {"city": "city_114", "support": 1336, "avg_response": 17025.49026946108}, {"city": "city_160", "support": 845, "avg_response": 16684.862721893493}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..a8e9250467074bbeb307168cc33bcc8153bb4cd9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_m9_24e382894c464291 +-- problem_id: v2p_m9_a60c27c2d70b4ada +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "city", + COUNT(*) AS support, + AVG("enrollee_id") AS avg_response +FROM "m9" +GROUP BY "city" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5ca95996722b5054cc408d5ce219a5b269e80993 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_m9_24e382894c464291\n-- problem_id: v2p_m9_a60c27c2d70b4ada\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"city\",\n COUNT(*) AS support,\n AVG(\"enrollee_id\") AS avg_response\nFROM \"m9\"\nGROUP BY \"city\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_m9_24e382894c464291\\n-- problem_id: v2p_m9_a60c27c2d70b4ada\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"city\\\",\\n COUNT(*) AS support,\\n AVG(\\\"enrollee_id\\\") AS avg_response\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"city\", \"support\", \"avg_response\"], \"rows\": [{\"city\": \"city_103\", \"support\": 4355, \"avg_response\": 17095.4429391504}, {\"city\": \"city_21\", \"support\": 2702, \"avg_response\": 17957.994448556623}, {\"city\": \"city_16\", \"support\": 1533, \"avg_response\": 17052.47553816047}, {\"city\": \"city_114\", \"support\": 1336, \"avg_response\": 17025.49026946108}, {\"city\": \"city_160\", \"support\": 845, \"avg_response\": 16684.862721893493}, {\"city\": \"city_136\", \"support\": 586, \"avg_response\": 17703.0204778157}, {\"city\": \"city_67\", \"support\": 431, \"avg_response\": 13940.241299303945}, {\"city\": \"city_75\", \"support\": 305, \"avg_response\": 16098.75737704918}, {\"city\": \"city_102\", \"support\": 304, \"avg_response\": 15721.480263157895}, {\"city\": \"city_104\", \"support\": 301, \"avg_response\": 15683.232558139534}, {\"city\": \"city_73\", \"support\": 280, \"avg_response\": 16375.171428571428}, {\"city\": \"city_100\", \"support\": 275, \"avg_response\": 15617.603636363636}, {\"city\": \"city_71\", \"support\": 266, \"avg_response\": 16738.57894736842}, {\"city\": \"city_11\", \"support\": 247, \"avg_response\": 16938.975708502025}, {\"city\": \"city_90\", \"support\": 197, \"avg_response\": 17102.015228426397}, {\"city\": \"city_61\", \"support\": 197, \"avg_response\": 16653.319796954314}, {\"city\": \"city_28\", \"support\": 192, \"avg_response\": 16437.645833333332}, {\"city\": \"city_23\", \"support\": 182, \"avg_response\": 13085.648351648351}, {\"city\": \"city_65\", \"support\": 175, \"avg_response\": 15679.885714285714}, {\"city\": \"city_36\", \"support\": 160, \"avg_response\": 15496.18125}, {\"city\": \"city_173\", \"support\": 151, \"avg_response\": 16098.476821192053}, {\"city\": \"city_83\", \"support\": 143, \"avg_response\": 16058.237762237763}, {\"city\": \"city_50\", \"support\": 140, \"avg_response\": 17859.657142857144}, {\"city\": \"city_46\", \"support\": 128, \"avg_response\": 17110.234375}, {\"city\": \"city_162\", \"support\": 128, \"avg_response\": 16197.671875}, {\"city\": \"city_116\", \"support\": 128, \"avg_response\": 15199.453125}, {\"city\": \"city_138\", \"support\": 120, \"avg_response\": 17027.8}, {\"city\": \"city_19\", \"support\": 119, \"avg_response\": 18748.991596638654}, {\"city\": \"city_64\", \"support\": 114, \"avg_response\": 19004.973684210527}, {\"city\": \"city_45\", \"support\": 113, \"avg_response\": 13652.566371681416}, {\"city\": \"city_74\", \"support\": 104, \"avg_response\": 16787.03846153846}, {\"city\": \"city_97\", \"support\": 104, \"avg_response\": 16301.298076923076}, {\"city\": \"city_57\", \"support\": 103, \"avg_response\": 15241.116504854368}, {\"city\": \"city_149\", \"support\": 102, \"avg_response\": 17904.196078431374}, {\"city\": \"city_159\", \"support\": 94, \"avg_response\": 16908.35106382979}, {\"city\": \"city_99\", \"support\": 94, \"avg_response\": 16347.808510638299}, {\"city\": \"city_128\", \"support\": 92, \"avg_response\": 17873.510869565216}, {\"city\": \"city_41\", \"support\": 89, \"avg_response\": 17819.955056179777}, {\"city\": \"city_10\", \"support\": 86, \"avg_response\": 15119.941860465116}, {\"city\": \"city_165\", \"support\": 82, \"avg_response\": 16664.60975609756}, {\"city\": \"city_98\", \"support\": 79, \"avg_response\": 15815.189873417721}, {\"city\": \"city_123\", \"support\": 79, \"avg_response\": 15586.405063291139}, {\"city\": \"city_105\", \"support\": 79, \"avg_response\": 14663.20253164557}, {\"city\": \"city_101\", \"support\": 75, \"avg_response\": 15548.186666666666}, {\"city\": \"city_40\", \"support\": 68, \"avg_response\": 15112.691176470587}, {\"city\": \"city_89\", \"support\": 67, \"avg_response\": 16696.55223880597}, {\"city\": \"city_150\", \"support\": 65, \"avg_response\": 15252.046153846153}, {\"city\": \"city_145\", \"support\": 63, \"avg_response\": 20235.20634920635}, {\"city\": \"city_24\", \"support\": 62, \"avg_response\": 15420.322580645161}, {\"city\": \"city_115\", \"support\": 54, \"avg_response\": 16702.59259259259}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 9.48}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..ad1a28b0b3ee52d2082b9a257c9a8cd623f087e2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.403340+00:00", + "ended_at": "2026-05-19T16:08:56.413643+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_24e382894c464291", + "problem_id": "v2p_m9_a60c27c2d70b4ada", + "dataset_id": "m9", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=enrollee_id, key_col=city.", + "bindings": { + "key_col": "city", + "measure_col": "enrollee_id", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=3", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_24e382894c464291.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_24e382894c464291/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..649e09f0e9bdf24601630a4cba83fa171fae3203 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"city_development_index": "0.92", "total_rows": 5200, "missing_rows": 0, "missing_rate": 0.0}, {"city_development_index": "0.624", "total_rows": 2702, "missing_rows": 0, "missing_rate": 0.0}, {"city_development_index": "0.91", "total_rows": 1533, "missing_rows": 0, "missing_rate": 0.0}, {"city_development_index": "0.9259999999999999", "total_rows": 1336, "missing_rows": 0, "missing_rate": 0.0}, {"city_development_index": "0.698", "total_rows": 683, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..bf2fa58c986cfaeb81827e5676e007767a833e0a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: co_missingness_pattern_consistency +-- intended_facet_id: missing_rate_by_subgroup +-- variant_semantic_role: missing_rate_by_subgroup +-- template_id: tpl_missing_rate_by_subgroup +-- query_record_id: v2q_m9_26eb494b4e647dfb +-- problem_id: v2p_m9_1c8b20a6a08de913 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "city_development_index", + COUNT(*) AS total_rows, + SUM(CASE WHEN "experience" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "experience" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9" +GROUP BY "city_development_index" +ORDER BY missing_rate DESC, total_rows DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..fc7291b488dbed60ae35d606856cd57fd95b853e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: co_missingness_pattern_consistency\n-- intended_facet_id: missing_rate_by_subgroup\n-- variant_semantic_role: missing_rate_by_subgroup\n-- template_id: tpl_missing_rate_by_subgroup\n-- query_record_id: v2q_m9_26eb494b4e647dfb\n-- problem_id: v2p_m9_1c8b20a6a08de913\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"city_development_index\",\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"experience\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"experience\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\"\nGROUP BY \"city_development_index\"\nORDER BY missing_rate DESC, total_rows DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: co_missingness_pattern_consistency\\n-- intended_facet_id: missing_rate_by_subgroup\\n-- variant_semantic_role: missing_rate_by_subgroup\\n-- template_id: tpl_missing_rate_by_subgroup\\n-- query_record_id: v2q_m9_26eb494b4e647dfb\\n-- problem_id: v2p_m9_1c8b20a6a08de913\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"city_development_index\\\",\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"experience\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"experience\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city_development_index\\\"\\nORDER BY missing_rate DESC, total_rows DESC;\", \"columns\": [\"city_development_index\", \"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"city_development_index\": \"0.92\", \"total_rows\": 5200, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.624\", \"total_rows\": 2702, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.91\", \"total_rows\": 1533, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.9259999999999999\", \"total_rows\": 1336, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.698\", \"total_rows\": 683, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.897\", \"total_rows\": 586, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.9390000000000001\", \"total_rows\": 497, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.855\", \"total_rows\": 431, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.804\", \"total_rows\": 304, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.924\", \"total_rows\": 301, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.754\", \"total_rows\": 280, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.887\", \"total_rows\": 275, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.884\", \"total_rows\": 266, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.55\", \"total_rows\": 247, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.9129999999999999\", \"total_rows\": 197, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.899\", \"total_rows\": 182, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.802\", \"total_rows\": 175, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.925\", \"total_rows\": 171, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.893\", \"total_rows\": 160, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.878\", \"total_rows\": 151, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.743\", \"total_rows\": 146, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.9229999999999999\", \"total_rows\": 143, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.8959999999999999\", \"total_rows\": 140, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.8270000000000001\", \"total_rows\": 137, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.579\", \"total_rows\": 135, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.762\", \"total_rows\": 128, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.767\", \"total_rows\": 128, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.836\", \"total_rows\": 120, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.682\", \"total_rows\": 119, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.6659999999999999\", \"total_rows\": 114, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.89\", \"total_rows\": 113, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.866\", \"total_rows\": 103, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.6890000000000001\", \"total_rows\": 102, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.843\", \"total_rows\": 94, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.915\", \"total_rows\": 94, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.794\", \"total_rows\": 93, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.527\", \"total_rows\": 92, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.895\", \"total_rows\": 86, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.7759999999999999\", \"total_rows\": 82, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.903\", \"total_rows\": 82, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.738\", \"total_rows\": 79, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.9490000000000001\", \"total_rows\": 79, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.5579999999999999\", \"total_rows\": 75, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.74\", \"total_rows\": 67, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.555\", \"total_rows\": 63, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.789\", \"total_rows\": 54, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.727\", \"total_rows\": 53, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.7659999999999999\", \"total_rows\": 49, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.848\", \"total_rows\": 47, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.691\", \"total_rows\": 45, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 9.97}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..0de8ab1a4333db50913568ed3fc0cd4862238c55 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/run_manifest.json @@ -0,0 +1,59 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:55.995270+00:00", + "ended_at": "2026-05-19T16:08:56.006072+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_26eb494b4e647dfb", + "problem_id": "v2p_m9_1c8b20a6a08de913", + "dataset_id": "m9", + "template_id": "tpl_missing_rate_by_subgroup", + "template_name": "Missing Rate by Subgroup", + "family_id": "missingness_structure", + "canonical_subitem_id": "co_missingness_pattern_consistency", + "intended_facet_id": "missing_rate_by_subgroup", + "variant_semantic_role": "missing_rate_by_subgroup", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Missing Rate by Subgroup to probe co_missingness_pattern_consistency with semantic role missing_rate_by_subgroup. Focus on group_col=city_development_index, missing_col=experience.", + "bindings": { + "missing_col": "experience", + "group_col": "city_development_index" + }, + "binding_roles": [ + "missing_col", + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY missing_rate DESC, total_rows DESC;", + "notes": [ + "default_facets=missing_rate_by_subgroup,missing_target_interaction", + "template_selection_mode=deterministic", + "problem_index_within_template=7", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_26eb494b4e647dfb.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_26eb494b4e647dfb/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3c1fbbfc502ce3527f253e3a3e071a2157c198f3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"total_rows": 19158, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..a353280644bf095a618090a6c58128ca731399f9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: marginal_missing_rate_consistency +-- intended_facet_id: missing_indicator_distribution +-- variant_semantic_role: missing_indicator_view +-- template_id: tpl_missing_marginal_rate_profile +-- query_record_id: v2q_m9_2744f3972a46e249 +-- problem_id: v2p_m9_477f164940d8835b +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + COUNT(*) AS total_rows, + SUM(CASE WHEN "education_level" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "education_level" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d9aafa209810844811680307bd1f80be18a31628 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: marginal_missing_rate_consistency\n-- intended_facet_id: missing_indicator_distribution\n-- variant_semantic_role: missing_indicator_view\n-- template_id: tpl_missing_marginal_rate_profile\n-- query_record_id: v2q_m9_2744f3972a46e249\n-- problem_id: v2p_m9_477f164940d8835b\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"education_level\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"education_level\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\";", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: marginal_missing_rate_consistency\\n-- intended_facet_id: missing_indicator_distribution\\n-- variant_semantic_role: missing_indicator_view\\n-- template_id: tpl_missing_marginal_rate_profile\\n-- query_record_id: v2q_m9_2744f3972a46e249\\n-- problem_id: v2p_m9_477f164940d8835b\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"education_level\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"education_level\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\";\", \"columns\": [\"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"total_rows\": 19158, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.88}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..1b84313a052f7179102b023436ac72de45def2c0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:55.910669+00:00", + "ended_at": "2026-05-19T16:08:55.914414+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_2744f3972a46e249", + "problem_id": "v2p_m9_477f164940d8835b", + "dataset_id": "m9", + "template_id": "tpl_missing_marginal_rate_profile", + "template_name": "Marginal Missing Rate Profile", + "family_id": "missingness_structure", + "canonical_subitem_id": "marginal_missing_rate_consistency", + "intended_facet_id": "missing_indicator_distribution", + "variant_semantic_role": "missing_indicator_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Marginal Missing Rate Profile to probe marginal_missing_rate_consistency with semantic role missing_indicator_view. Focus on missing_col=education_level.", + "bindings": { + "missing_col": "education_level" + }, + "binding_roles": [ + "missing_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table};", + "notes": [ + "default_facets=missing_indicator_distribution", + "template_selection_mode=deterministic", + "problem_index_within_template=3", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_2744f3972a46e249.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2744f3972a46e249/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b807f30e3ef86c10164ea7533f8b3b1b78fadd2d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9710, "bytes_utf8": 9710, "lines": 266, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 639, "bytes_utf8": 639, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14770, "cached_input_tokens": 12032, "output_tokens": 704, "reasoning_output_tokens": 516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..e4f86d94bedab0efaee33c9d9f7ad705924e5477 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_2c8fa5178b92e059", + "api_calls": 0, + "input_tokens": 14770, + "cached_input_tokens": 12032, + "output_tokens": 704, + "total_tokens": 15474, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12736.93, + "sql_execution_elapsed_ms_total": 31.77, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..ae0879619f1df72c88b2a4e9a19fc74da37bad3b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:39:27.718106+00:00", + "ended_at": "2026-05-19T15:39:40.455074+00:00", + "elapsed_ms": 12736.93, + "prompt_metrics": { + "chars": 9710, + "bytes_utf8": 9710, + "lines": 266, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1025, + "bytes_utf8": 1025, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 639, + "bytes_utf8": 639, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14770, + "cached_input_tokens": 12032, + "output_tokens": 704, + "reasoning_output_tokens": 516 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..ae16f8fdf97b9275f1b9e1bbefedf89c70add5d8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,266 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "required_roles": [ + "group_col", + "item_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=last_new_job, measure_col=enrollee_id.", + "planned_template_id": "tpl_tpcds_within_group_share", + "bindings": { + "group_col": "last_new_job", + "measure_col": "enrollee_id", + "item_col": "training_hours", + "top_k": 13, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..f02b74d746ef5d19d86b93b1438884fa22ed953b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40e4-5b72-7620-beb3-3dfe92041936"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"last_new_job\\\",\\n \\\"training_hours\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"enrollee_id\\\" AS REAL))) OVER (PARTITION BY \\\"last_new_job\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nGROUP BY \\\"last_new_job\\\", \\\"training_hours\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Used the required template with group_col=\\\"last_new_job\\\", item_col=\\\"training_hours\\\", and measure_col=\\\"enrollee_id\\\". Because \\\"enrollee_id\\\" is stored as TEXT in SQLite, it is cast to REAL so SUM() is SQLite-compatible.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14770,"cached_input_tokens":12032,"output_tokens":704,"reasoning_output_tokens":516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..4425214f7548d10c826e1e568dc73679b37be468 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"last_new_job\",\n \"training_hours\",\n SUM(CAST(\"enrollee_id\" AS REAL)) AS total_measure,\n SUM(CAST(\"enrollee_id\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"enrollee_id\" AS REAL))) OVER (PARTITION BY \"last_new_job\") AS share_within_group\nFROM \"m9\"\nGROUP BY \"last_new_job\", \"training_hours\"\nORDER BY share_within_group DESC;","notes":"Used the required template with group_col=\"last_new_job\", item_col=\"training_hours\", and measure_col=\"enrollee_id\". Because \"enrollee_id\" is stored as TEXT in SQLite, it is cast to REAL so SUM() is SQLite-compatible."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2c8fa5178b92e059/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..acbce8f82720e0b556bdec83c0edd413e44cefe8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:55:53.601560+00:00", + "ended_at": "2026-05-19T15:55:57.017484+00:00", + "elapsed_ms": 3415.9, + "returncode": 1, + "prompt_metrics": { + "chars": 9490, + "bytes_utf8": 9490, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..4065249f6b5f14b486585f050fa3de8126717948 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:55:58.019790+00:00", + "ended_at": "2026-05-19T15:56:01.231415+00:00", + "elapsed_ms": 3211.58, + "returncode": 1, + "prompt_metrics": { + "chars": 9490, + "bytes_utf8": 9490, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..a8ada252bdc39b3bda10f93a8f79a34506085313 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=major_discipline, measure_col=training_hours.", + "planned_template_id": "tpl_grouped_percentile_point", + "bindings": { + "group_col": "major_discipline", + "measure_col": "training_hours", + "top_k": 19, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 70.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..a8ada252bdc39b3bda10f93a8f79a34506085313 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=major_discipline, measure_col=training_hours.", + "planned_template_id": "tpl_grouped_percentile_point", + "bindings": { + "group_col": "major_discipline", + "measure_col": "training_hours", + "top_k": 19, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 70.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..27d30f64f0a888e693497191ca18537368644f32 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f3-6697-7822-8245-015592da6dfd"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..51d54f1039e7b4681019f004d30d7413e9b27cbc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f3-6697-7822-8245-015592da6dfd"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..9fb4c776c2090025f256396c3f4fdeceb2fcd449 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f3-77e0-7f23-923d-8135bb4d9b6f"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..b5479a7338f5d17978802e1960deb233f6fb34ec --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f3-77e0-7f23-923d-8135bb4d9b6f"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2f71dcc641ef5656/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..d6a843f8a8f16107f6abdc0e393d3ee03400302f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=company_type, measure_col=training_hours. +Result preview: [{"company_type": "Pvt Ltd", "group_value": 640827.0}, {"company_type": "", "group_value": 399546.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..d474dda0016e6ded4aefe16b11815d868e69e3a9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/generated_sql.sql @@ -0,0 +1,27 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_m9_2fb04cf42eeead01 +-- problem_id: v2p_m9_98e1fc7850db9798 +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT "company_type", SUM(CAST("training_hours" AS REAL)) AS "group_value" + FROM "m9" + GROUP BY "company_type" +), +"total" AS ( + SELECT SUM("group_value") AS "total_value" + FROM "grouped" +) +SELECT g."company_type", g."group_value" +FROM "grouped" AS g +CROSS JOIN "total" AS t +WHERE g."group_value" > t."total_value" * 0.1 +ORDER BY g."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..cb8843de46362d29cba4ab8755bc65461ee08599 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n SELECT \"company_type\", SUM(CAST(\"training_hours\" AS REAL)) AS \"group_value\"\n FROM \"m9\"\n GROUP BY \"company_type\"\n),\n\"total\" AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM \"grouped\"\n)\nSELECT g.\"company_type\", g.\"group_value\"\nFROM \"grouped\" AS g\nCROSS JOIN \"total\" AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT \\\"company_type\\\", SUM(CAST(\\\"training_hours\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n GROUP BY \\\"company_type\\\"\\n),\\n\\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT g.\\\"company_type\\\", g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\", \"columns\": [\"company_type\", \"group_value\"], \"rows\": [{\"company_type\": \"Pvt Ltd\", \"group_value\": 640827.0}, {\"company_type\": \"\", \"group_value\": 399546.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 8.35}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..9ee2bc3c79034d6f70b3402e1e2079c1e3d7dbbb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:49:53.489854+00:00", + "ended_at": "2026-05-19T15:50:09.387757+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_2fb04cf42eeead01", + "problem_id": "v2p_m9_98e1fc7850db9798", + "dataset_id": "m9", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=company_type, measure_col=training_hours.", + "bindings": { + "group_col": "company_type", + "measure_col": "training_hours", + "top_k": 10, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=9", + "sql_variant_index=1/2", + "binding_index=80" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 9, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_2fb04cf42eeead01.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_2fb04cf42eeead01", + "api_calls": 0, + "input_tokens": 14782, + "cached_input_tokens": 13696, + "output_tokens": 650, + "total_tokens": 15432, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15884.75, + "sql_execution_elapsed_ms_total": 8.35, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..06625dbb3f540fce2657f622d206abc46d04f2e2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:50:09.377980+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15884.75, "started_at": "2026-05-19T15:49:53.492452+00:00", "ended_at": "2026-05-19T15:50:09.377235+00:00", "prompt_metrics": {"chars": 9855, "bytes_utf8": 9855, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 690, "bytes_utf8": 690, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14782, "cached_input_tokens": 13696, "output_tokens": 650, "reasoning_output_tokens": 455}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT \\\"company_type\\\", SUM(CAST(\\\"training_hours\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n GROUP BY \\\"company_type\\\"\\n),\\n\\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT g.\\\"company_type\\\", g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Uses the required template with group_col=\\\"company_type\\\" and measure_col=\\\"training_hours\\\". CAST to REAL is applied because \\\"training_hours\\\" is stored as TEXT in the SQLite schema snapshot.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..73851d539b0936e83fb679eabdde3f5ccfb660e2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_2fb04cf42eeead01", + "api_calls": 0, + "input_tokens": 14782, + "cached_input_tokens": 13696, + "output_tokens": 650, + "total_tokens": 15432, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15884.75, + "sql_execution_elapsed_ms_total": 8.35, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_2fb04cf42eeead01/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3118ae6c80eb666b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3118ae6c80eb666b/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..43b42b3a5e22d7f7d0b3e0e83418698491295779 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3118ae6c80eb666b/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:57:20.604314+00:00", + "ended_at": "2026-05-19T15:57:27.919112+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_3118ae6c80eb666b", + "problem_id": "v2p_m9_7f21873544d6d77c", + "dataset_id": "m9", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=company_size, measure_col=city_development_index.", + "bindings": { + "group_col": "company_size", + "measure_col": "city_development_index", + "top_k": 11, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/2", + "binding_index=91" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3118ae6c80eb666b/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3118ae6c80eb666b/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..4c85737404da7eb2cc3e9c63334d138c9cab9ffc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3118ae6c80eb666b/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:57:23.735504+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3128.28, "started_at": "2026-05-19T15:57:20.606443+00:00", "ended_at": "2026-05-19T15:57:23.734748+00:00", "prompt_metrics": {"chars": 9494, "bytes_utf8": 9494, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f4-ba5b-7d53-81f3-f512cbf47eca\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:57:27.918967+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3180.46, "started_at": "2026-05-19T15:57:24.737417+00:00", "ended_at": "2026-05-19T15:57:27.917927+00:00", "prompt_metrics": {"chars": 9494, "bytes_utf8": 9494, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f4-ca9f-7120-a4c6-a94a63c1f547\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..eb827910d7fd5ad601a69b295589a3cebf92995d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=experience, measure_col=enrollee_id. +Result preview: [{"experience": ">20", "group_value": 3286}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..6281b9063c924740c8467502b2eeac6a0c9df1b4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/generated_sql.sql @@ -0,0 +1,31 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_m9_335ae5b066dd48bd +-- problem_id: v2p_m9_d5a95e17176a84f8 +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT + "experience", + COUNT("enrollee_id") AS "group_value" + FROM "m9" + GROUP BY "experience" +), +"total" AS ( + SELECT SUM("group_value") AS "total_value" + FROM "grouped" +) +SELECT + g."experience", + g."group_value" +FROM "grouped" AS g +CROSS JOIN "total" AS t +WHERE g."group_value" > t."total_value" * 0.1 +ORDER BY g."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f5c72138c32533fe5ebbf109353c13d427141403 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n SELECT\n \"experience\",\n COUNT(\"enrollee_id\") AS \"group_value\"\n FROM \"m9\"\n GROUP BY \"experience\"\n),\n\"total\" AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM \"grouped\"\n)\nSELECT\n g.\"experience\",\n g.\"group_value\"\nFROM \"grouped\" AS g\nCROSS JOIN \"total\" AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"experience\\\",\\n COUNT(\\\"enrollee_id\\\") AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n GROUP BY \\\"experience\\\"\\n),\\n\\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT\\n g.\\\"experience\\\",\\n g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\", \"columns\": [\"experience\", \"group_value\"], \"rows\": [{\"experience\": \">20\", \"group_value\": 3286}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 15.5}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..d342807767e7c7ba06df1bb1b51950f95677e510 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:48:54.226064+00:00", + "ended_at": "2026-05-19T15:49:11.005675+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_335ae5b066dd48bd", + "problem_id": "v2p_m9_d5a95e17176a84f8", + "dataset_id": "m9", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=experience, measure_col=enrollee_id.", + "bindings": { + "group_col": "experience", + "measure_col": "enrollee_id", + "top_k": 13, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/2", + "binding_index=78" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_335ae5b066dd48bd.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_335ae5b066dd48bd", + "api_calls": 0, + "input_tokens": 14784, + "cached_input_tokens": 13696, + "output_tokens": 929, + "total_tokens": 15713, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16756.66, + "sql_execution_elapsed_ms_total": 15.5, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3247c23bba78cad7e70c2da494895fa2937f8220 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:49:10.987500+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 16756.66, "started_at": "2026-05-19T15:48:54.229580+00:00", "ended_at": "2026-05-19T15:49:10.986279+00:00", "prompt_metrics": {"chars": 9849, "bytes_utf8": 9849, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 695, "bytes_utf8": 695, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14784, "cached_input_tokens": 13696, "output_tokens": 929, "reasoning_output_tokens": 732}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"experience\\\",\\n COUNT(\\\"enrollee_id\\\") AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n GROUP BY \\\"experience\\\"\\n),\\n\\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT\\n g.\\\"experience\\\",\\n g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Applied the planned relative-to-total threshold template on \\\"experience\\\". For count_distribution semantics, used COUNT(\\\"enrollee_id\\\") as the group measure instead of summing the identifier-like field.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..6ee0479a2f037ad6d294a8da4ab8b5873d1eecf3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_335ae5b066dd48bd", + "api_calls": 0, + "input_tokens": 14784, + "cached_input_tokens": 13696, + "output_tokens": 929, + "total_tokens": 15713, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16756.66, + "sql_execution_elapsed_ms_total": 15.5, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_335ae5b066dd48bd/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..5cb96cefd458b50da4cb1d24b1923532139d1d20 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=enrollee_id. +Result preview: [{"enrollee_id": "33380"}, {"enrollee_id": "33379"}, {"enrollee_id": "33377"}, {"enrollee_id": "33376"}, {"enrollee_id": "33375"}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..4666625bc808791f2b235b4cb1f1227218960659 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/generated_sql.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_m9_38a7d957278baec1 +-- problem_id: v2p_m9_e87cc71c342d5ff0 +-- realization_mode: agent +-- source_kind: agent +WITH buckets AS ( + SELECT + "enrollee_id", + NTILE(10) OVER (ORDER BY CAST("enrollee_id" AS INTEGER) DESC) AS tail_bucket + FROM "m9" + WHERE "enrollee_id" IS NOT NULL AND "enrollee_id" <> '' +) +SELECT "enrollee_id" +FROM buckets +WHERE tail_bucket = 1 +ORDER BY CAST("enrollee_id" AS INTEGER) DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b1ccb2d45a1f7467d826fce290d04c56661df689 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH buckets AS (\n SELECT\n \"enrollee_id\",\n NTILE(10) OVER (ORDER BY CAST(\"enrollee_id\" AS INTEGER) DESC) AS tail_bucket\n FROM \"m9\"\n WHERE \"enrollee_id\" IS NOT NULL AND \"enrollee_id\" <> ''\n)\nSELECT \"enrollee_id\"\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY CAST(\"enrollee_id\" AS INTEGER) DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n SELECT\\n \\\"enrollee_id\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"enrollee_id\\\" AS INTEGER) DESC) AS tail_bucket\\n FROM \\\"m9\\\"\\n WHERE \\\"enrollee_id\\\" IS NOT NULL AND \\\"enrollee_id\\\" <> ''\\n)\\nSELECT \\\"enrollee_id\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY CAST(\\\"enrollee_id\\\" AS INTEGER) DESC;\", \"columns\": [\"enrollee_id\"], \"rows\": [{\"enrollee_id\": \"33380\"}, {\"enrollee_id\": \"33379\"}, {\"enrollee_id\": \"33377\"}, {\"enrollee_id\": \"33376\"}, {\"enrollee_id\": \"33375\"}, {\"enrollee_id\": \"33374\"}, {\"enrollee_id\": \"33373\"}, {\"enrollee_id\": \"33370\"}, {\"enrollee_id\": \"33368\"}, {\"enrollee_id\": \"33367\"}, {\"enrollee_id\": \"33365\"}, {\"enrollee_id\": \"33362\"}, {\"enrollee_id\": \"33360\"}, {\"enrollee_id\": \"33358\"}, {\"enrollee_id\": \"33357\"}, {\"enrollee_id\": \"33356\"}, {\"enrollee_id\": \"33352\"}, {\"enrollee_id\": \"33350\"}, {\"enrollee_id\": \"33349\"}, {\"enrollee_id\": \"33348\"}, {\"enrollee_id\": \"33344\"}, {\"enrollee_id\": \"33342\"}, {\"enrollee_id\": \"33341\"}, {\"enrollee_id\": \"33340\"}, {\"enrollee_id\": \"33339\"}, {\"enrollee_id\": \"33338\"}, {\"enrollee_id\": \"33337\"}, {\"enrollee_id\": \"33336\"}, {\"enrollee_id\": \"33335\"}, {\"enrollee_id\": \"33333\"}, {\"enrollee_id\": \"33332\"}, {\"enrollee_id\": \"33331\"}, {\"enrollee_id\": \"33330\"}, {\"enrollee_id\": \"33328\"}, {\"enrollee_id\": \"33327\"}, {\"enrollee_id\": \"33326\"}, {\"enrollee_id\": \"33325\"}, {\"enrollee_id\": \"33321\"}, {\"enrollee_id\": \"33318\"}, {\"enrollee_id\": \"33317\"}, {\"enrollee_id\": \"33315\"}, {\"enrollee_id\": \"33314\"}, {\"enrollee_id\": \"33312\"}, {\"enrollee_id\": \"33311\"}, {\"enrollee_id\": \"33310\"}, {\"enrollee_id\": \"33307\"}, {\"enrollee_id\": \"33306\"}, {\"enrollee_id\": \"33305\"}, {\"enrollee_id\": \"33304\"}, {\"enrollee_id\": \"33302\"}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 43.81}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..77f7d5d5ba5542fd6fff4040c3156eb3c12975d5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:44:03.605483+00:00", + "ended_at": "2026-05-19T15:44:15.333751+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_38a7d957278baec1", + "problem_id": "v2p_m9_e87cc71c342d5ff0", + "dataset_id": "m9", + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=enrollee_id.", + "bindings": { + "measure_col": "enrollee_id", + "top_k": 10, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/1", + "binding_index=60" + ], + "template_selection_mode": "rule", + "selected_template_rank": 6, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_38a7d957278baec1.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_38a7d957278baec1", + "api_calls": 0, + "input_tokens": 14703, + "cached_input_tokens": 12032, + "output_tokens": 434, + "total_tokens": 15137, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11678.49, + "sql_execution_elapsed_ms_total": 43.81, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ab359a932692c194021bf3414daf9676eee924ba --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:44:15.287681+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11678.49, "started_at": "2026-05-19T15:44:03.608103+00:00", "ended_at": "2026-05-19T15:44:15.286622+00:00", "prompt_metrics": {"chars": 9462, "bytes_utf8": 9462, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 614, "bytes_utf8": 614, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14703, "cached_input_tokens": 12032, "output_tokens": 434, "reasoning_output_tokens": 258}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n SELECT\\n \\\"enrollee_id\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"enrollee_id\\\" AS INTEGER) DESC) AS tail_bucket\\n FROM \\\"m9\\\"\\n WHERE \\\"enrollee_id\\\" IS NOT NULL AND \\\"enrollee_id\\\" <> ''\\n)\\nSELECT \\\"enrollee_id\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY CAST(\\\"enrollee_id\\\" AS INTEGER) DESC;\",\"notes\":\"Applied the Quantile Tail Slice template with measure_col bound to \\\"enrollee_id\\\" and num_tiles=10. Cast to INTEGER for correct descending numeric tail slicing because the schema stores \\\"enrollee_id\\\" as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..313b1b4e53cbf0a6d98090516ac4a4e805b14f47 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_38a7d957278baec1", + "api_calls": 0, + "input_tokens": 14703, + "cached_input_tokens": 12032, + "output_tokens": 434, + "total_tokens": 15137, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11678.49, + "sql_execution_elapsed_ms_total": 43.81, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_38a7d957278baec1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0c9584e2e0e1dec1802dd88865c4e6e3182fca49 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9880, "bytes_utf8": 9880, "lines": 264, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 859, "bytes_utf8": 859, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14788, "cached_input_tokens": 13696, "output_tokens": 612, "reasoning_output_tokens": 394}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..f4a5c2ffd1523d8c54287b6dcb3531f6a2fdedad --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_3c214e997dd8d8a5", + "api_calls": 0, + "input_tokens": 14788, + "cached_input_tokens": 13696, + "output_tokens": 612, + "total_tokens": 15400, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12489.85, + "sql_execution_elapsed_ms_total": 13.14, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..cc0ff9621cae15684cfcdb6201f1d02b8e6e9d1a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:48:09.891843+00:00", + "ended_at": "2026-05-19T15:48:22.381725+00:00", + "elapsed_ms": 12489.85, + "prompt_metrics": { + "chars": 9880, + "bytes_utf8": 9880, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1248, + "bytes_utf8": 1248, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 859, + "bytes_utf8": 859, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14788, + "cached_input_tokens": 13696, + "output_tokens": 612, + "reasoning_output_tokens": 394 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..f7cc90ab31c6c882f884470febfb9ceee15a14e7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "primary_family": "tail_rarity_structure", + "portability": "partial", + "sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=education_level, measure_col=city_development_index.", + "planned_template_id": "tpl_tpch_relative_total_threshold", + "bindings": { + "group_col": "education_level", + "measure_col": "city_development_index", + "top_k": 16, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..3f3f3fc651af6a4a4e2bb856a87343633e41a677 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40ec-533e-77a2-8ea7-eddc6dea05f7"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT\\n \\\"education_level\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS group_value\\n FROM \\\"m9\\\"\\n WHERE \\\"education_level\\\" IS NOT NULL\\n AND \\\"education_level\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n GROUP BY \\\"education_level\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"education_level\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\",\"notes\":\"Applied the requested template with group_col=\\\"education_level\\\" and measure_col=\\\"city_development_index\\\", casting the text measure to REAL and filtering blank/null group or measure values for a stable grouped view.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14788,"cached_input_tokens":13696,"output_tokens":612,"reasoning_output_tokens":394}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..78cae30cef4caad11d791d6040e7b69f23d0c534 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT\n \"education_level\",\n SUM(CAST(\"city_development_index\" AS REAL)) AS group_value\n FROM \"m9\"\n WHERE \"education_level\" IS NOT NULL\n AND \"education_level\" <> ''\n AND \"city_development_index\" IS NOT NULL\n AND \"city_development_index\" <> ''\n GROUP BY \"education_level\"\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.\"education_level\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.05\nORDER BY g.group_value DESC;","notes":"Applied the requested template with group_col=\"education_level\" and measure_col=\"city_development_index\", casting the text measure to REAL and filtering blank/null group or measure values for a stable grouped view."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3c214e997dd8d8a5/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..486a779cda576ed5cd77f95ca0c2e25066d85f9c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9557, "bytes_utf8": 9557, "lines": 267, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 396, "bytes_utf8": 396, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14706, "cached_input_tokens": 12032, "output_tokens": 589, "reasoning_output_tokens": 486}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..cf73934c7bbc38ab2642255e5c04c47ddb8d20c1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_3ca64cfda21f41bb", + "api_calls": 0, + "input_tokens": 14706, + "cached_input_tokens": 12032, + "output_tokens": 589, + "total_tokens": 15295, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13179.5, + "sql_execution_elapsed_ms_total": 13.23, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..329dbbd9538792d227248d40a112c9647c41b5a8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:59:21.954362+00:00", + "ended_at": "2026-05-19T15:59:35.133903+00:00", + "elapsed_ms": 13179.5, + "prompt_metrics": { + "chars": 9557, + "bytes_utf8": 9557, + "lines": 267, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 743, + "bytes_utf8": 743, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 396, + "bytes_utf8": 396, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14706, + "cached_input_tokens": 12032, + "output_tokens": 589, + "reasoning_output_tokens": 486 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..9a6208298efb5b01070f9d85e8abbd74595797d4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,267 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=city_development_index, condition_col=gender.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "city_development_index", + "condition_col": "gender", + "condition_value": "", + "positive_value": "Male", + "negative_value": "", + "top_k": 16, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..6786fcf8fb87530077d434779bb2ba7629a551b3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f6-9486-79e2-bdee-234d0c0e8886"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"city_development_index\\\",\\n AVG(CASE WHEN \\\"gender\\\" = '' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city_development_index\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Uses the provided Grouped Condition Rate template to compute, for each city_development_index group, the rate of rows where gender is blank.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14706,"cached_input_tokens":12032,"output_tokens":589,"reasoning_output_tokens":486}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..2a5446ccc0882e3f5e6864d33345dc0dfabcfe0a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT \"city_development_index\",\n AVG(CASE WHEN \"gender\" = '' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"m9\"\nGROUP BY \"city_development_index\"\nORDER BY condition_rate DESC;","notes":"Uses the provided Grouped Condition Rate template to compute, for each city_development_index group, the rate of rows where gender is blank."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3ca64cfda21f41bb/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..d71158554adcde44ac47613da576de1633b759d0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=company_type, condition_col=gender. +Result preview: [{"company_type": "Funded Startup", "condition_rate": 0.7412587412587412}, {"company_type": "Pvt Ltd", "condition_rate": 0.7198736884995416}, {"company_type": "NGO", "condition_rate": 0.6641074856046065}, {"company_type": "Other", "condition_rate": 0.6528925619834711}, {"company_type": "", "condition_rate": 0.6498371335504886}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..f58cf14af92744e6d59b7a1d889e0edb390b09ae --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_m9_3cc6043271b19bf1 +-- problem_id: v2p_m9_a6c9915dc5e73511 +-- realization_mode: agent +-- source_kind: agent +SELECT "company_type", + AVG(CASE WHEN "gender" = 'Male' THEN 1 ELSE 0 END) AS condition_rate +FROM "m9" +GROUP BY "company_type" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f97dc53692e7ae7e6452cab42eed16781d2332d4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"company_type\",\n AVG(CASE WHEN \"gender\" = 'Male' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"m9\"\nGROUP BY \"company_type\"\nORDER BY condition_rate DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"company_type\\\",\\n AVG(CASE WHEN \\\"gender\\\" = 'Male' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"company_type\\\"\\nORDER BY condition_rate DESC;\", \"columns\": [\"company_type\", \"condition_rate\"], \"rows\": [{\"company_type\": \"Funded Startup\", \"condition_rate\": 0.7412587412587412}, {\"company_type\": \"Pvt Ltd\", \"condition_rate\": 0.7198736884995416}, {\"company_type\": \"NGO\", \"condition_rate\": 0.6641074856046065}, {\"company_type\": \"Other\", \"condition_rate\": 0.6528925619834711}, {\"company_type\": \"\", \"condition_rate\": 0.6498371335504886}, {\"company_type\": \"Early Stage Startup\", \"condition_rate\": 0.6417910447761194}, {\"company_type\": \"Public Sector\", \"condition_rate\": 0.6387434554973822}], \"row_count_returned\": 7, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 10.05}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..1b122ab037f4d7d1317fbbe99285e25aa039e63d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:02:10.623003+00:00", + "ended_at": "2026-05-19T16:02:24.352951+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_3cc6043271b19bf1", + "problem_id": "v2p_m9_a6c9915dc5e73511", + "dataset_id": "m9", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=company_type, condition_col=gender.", + "bindings": { + "group_col": "company_type", + "condition_col": "gender", + "condition_value": "Male", + "positive_value": "Male", + "negative_value": "", + "top_k": 14, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=9", + "sql_variant_index=1/2", + "binding_index=104" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 9, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_3cc6043271b19bf1.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_3cc6043271b19bf1", + "api_calls": 0, + "input_tokens": 14704, + "cached_input_tokens": 12032, + "output_tokens": 377, + "total_tokens": 15081, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12712.29, + "sql_execution_elapsed_ms_total": 10.05, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..14137ad54df62ad2bccd9c171c7d06416ac0ff00 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:02:13.635447+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3009.29, "started_at": "2026-05-19T16:02:10.625045+00:00", "ended_at": "2026-05-19T16:02:13.634360+00:00", "prompt_metrics": {"chars": 9540, "bytes_utf8": 9540, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f9-2769-71f3-86f8-e97145c6951e\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:02:24.341074+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9703.0, "started_at": "2026-05-19T16:02:14.637176+00:00", "ended_at": "2026-05-19T16:02:24.340228+00:00", "prompt_metrics": {"chars": 9540, "bytes_utf8": 9540, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 394, "bytes_utf8": 394, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14704, "cached_input_tokens": 12032, "output_tokens": 377, "reasoning_output_tokens": 273}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"company_type\\\",\\n AVG(CASE WHEN \\\"gender\\\" = 'Male' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"company_type\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Computes the within-group proportion of rows where \\\"gender\\\" is 'Male' for each \\\"company_type\\\", following the provided Grouped Condition Rate template.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..cf1fa980c759194bfe802583b5fc2fd0f566645b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_3cc6043271b19bf1", + "api_calls": 0, + "input_tokens": 14704, + "cached_input_tokens": 12032, + "output_tokens": 377, + "total_tokens": 15081, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12712.29, + "sql_execution_elapsed_ms_total": 10.05, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cc6043271b19bf1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..b2a7eec2f9c4e0d0b6b7f06a4c4c5d759b3d4e59 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=enrolled_university, condition_col=target. +Result preview: [{"enrolled_university": "no_enrollment", "condition_ratio": 3.730229373502225}, {"enrolled_university": "Part time course", "condition_ratio": 2.966887417218543}, {"enrolled_university": "", "condition_ratio": 2.138211382113821}, {"enrolled_university": "Full time course", "condition_ratio": 1.6254367575122293}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..d7d157196fbda6278353823aaa01f2f10df76834 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_m9_3cf01897659feb3f +-- problem_id: v2p_m9_674086dc5ded99f3 +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT + "enrolled_university", + SUM(CASE WHEN "target" = '0.0' THEN 1 ELSE 0 END) AS "numerator_count", + SUM(CASE WHEN "target" = '1.0' THEN 1 ELSE 0 END) AS "denominator_count" + FROM "m9" + GROUP BY "enrolled_university" +) +SELECT + "enrolled_university", + CAST("numerator_count" AS FLOAT) / NULLIF("denominator_count", 0) AS "condition_ratio" +FROM "grouped" +ORDER BY "condition_ratio" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..79835c416f5f71273f969cc557ef5fdc663446d8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_ratio_two_conditions\nWITH \"grouped\" AS (\n SELECT\n \"enrolled_university\",\n SUM(CASE WHEN \"target\" = '0.0' THEN 1 ELSE 0 END) AS \"numerator_count\",\n SUM(CASE WHEN \"target\" = '1.0' THEN 1 ELSE 0 END) AS \"denominator_count\"\n FROM \"m9\"\n GROUP BY \"enrolled_university\"\n)\nSELECT\n \"enrolled_university\",\n CAST(\"numerator_count\" AS FLOAT) / NULLIF(\"denominator_count\", 0) AS \"condition_ratio\"\nFROM \"grouped\"\nORDER BY \"condition_ratio\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"enrolled_university\\\",\\n SUM(CASE WHEN \\\"target\\\" = '0.0' THEN 1 ELSE 0 END) AS \\\"numerator_count\\\",\\n SUM(CASE WHEN \\\"target\\\" = '1.0' THEN 1 ELSE 0 END) AS \\\"denominator_count\\\"\\n FROM \\\"m9\\\"\\n GROUP BY \\\"enrolled_university\\\"\\n)\\nSELECT\\n \\\"enrolled_university\\\",\\n CAST(\\\"numerator_count\\\" AS FLOAT) / NULLIF(\\\"denominator_count\\\", 0) AS \\\"condition_ratio\\\"\\nFROM \\\"grouped\\\"\\nORDER BY \\\"condition_ratio\\\" DESC;\", \"columns\": [\"enrolled_university\", \"condition_ratio\"], \"rows\": [{\"enrolled_university\": \"no_enrollment\", \"condition_ratio\": 3.730229373502225}, {\"enrolled_university\": \"Part time course\", \"condition_ratio\": 2.966887417218543}, {\"enrolled_university\": \"\", \"condition_ratio\": 2.138211382113821}, {\"enrolled_university\": \"Full time course\", \"condition_ratio\": 1.6254367575122293}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 12.88}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..31d1c20fec2bbdf664571f14bdfe96e9231d4f05 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:40:38.178695+00:00", + "ended_at": "2026-05-19T15:40:52.575590+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_3cf01897659feb3f", + "problem_id": "v2p_m9_674086dc5ded99f3", + "dataset_id": "m9", + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "contrastive_conditional_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=enrolled_university, condition_col=target.", + "bindings": { + "group_col": "enrolled_university", + "condition_col": "target", + "condition_value": "0.0", + "positive_value": "0.0", + "negative_value": "1.0", + "top_k": 14, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/1", + "binding_index=39" + ], + "template_selection_mode": "rule", + "selected_template_rank": 4, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_3cf01897659feb3f.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_3cf01897659feb3f", + "api_calls": 0, + "input_tokens": 14863, + "cached_input_tokens": 13696, + "output_tokens": 718, + "total_tokens": 15581, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14377.96, + "sql_execution_elapsed_ms_total": 12.88, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..67f96ff1613a06b67b80a9c81475b05342499915 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:40:52.561166+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14377.96, "started_at": "2026-05-19T15:40:38.182248+00:00", "ended_at": "2026-05-19T15:40:52.560242+00:00", "prompt_metrics": {"chars": 10114, "bytes_utf8": 10114, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 726, "bytes_utf8": 726, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14863, "cached_input_tokens": 13696, "output_tokens": 718, "reasoning_output_tokens": 501}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"enrolled_university\\\",\\n SUM(CASE WHEN \\\"target\\\" = '0.0' THEN 1 ELSE 0 END) AS \\\"numerator_count\\\",\\n SUM(CASE WHEN \\\"target\\\" = '1.0' THEN 1 ELSE 0 END) AS \\\"denominator_count\\\"\\n FROM \\\"m9\\\"\\n GROUP BY \\\"enrolled_university\\\"\\n)\\nSELECT\\n \\\"enrolled_university\\\",\\n CAST(\\\"numerator_count\\\" AS FLOAT) / NULLIF(\\\"denominator_count\\\", 0) AS \\\"condition_ratio\\\"\\nFROM \\\"grouped\\\"\\nORDER BY \\\"condition_ratio\\\" DESC;\",\"notes\":\"Computes the ratio of rows with target='0.0' to rows with target='1.0' for each enrolled_university group. Groups with zero target='1.0' rows return NULL for the ratio.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..dff3d394203285b284fa1a711d967c7640e5dbfc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_3cf01897659feb3f", + "api_calls": 0, + "input_tokens": 14863, + "cached_input_tokens": 13696, + "output_tokens": 718, + "total_tokens": 15581, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14377.96, + "sql_execution_elapsed_ms_total": 12.88, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3cf01897659feb3f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3c1fbbfc502ce3527f253e3a3e071a2157c198f3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"total_rows": 19158, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..40c515f0f99895ff49f0019522332bfa8a0faeac --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: marginal_missing_rate_consistency +-- intended_facet_id: missing_indicator_distribution +-- variant_semantic_role: missing_indicator_view +-- template_id: tpl_missing_marginal_rate_profile +-- query_record_id: v2q_m9_3da77e5212fcafa1 +-- problem_id: v2p_m9_78efb5e51c91f33a +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + COUNT(*) AS total_rows, + SUM(CASE WHEN "enrolled_university" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "enrolled_university" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..16da7530d8bf256142f29c4ceb879145b2175380 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: marginal_missing_rate_consistency\n-- intended_facet_id: missing_indicator_distribution\n-- variant_semantic_role: missing_indicator_view\n-- template_id: tpl_missing_marginal_rate_profile\n-- query_record_id: v2q_m9_3da77e5212fcafa1\n-- problem_id: v2p_m9_78efb5e51c91f33a\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"enrolled_university\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"enrolled_university\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\";", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: marginal_missing_rate_consistency\\n-- intended_facet_id: missing_indicator_distribution\\n-- variant_semantic_role: missing_indicator_view\\n-- template_id: tpl_missing_marginal_rate_profile\\n-- query_record_id: v2q_m9_3da77e5212fcafa1\\n-- problem_id: v2p_m9_78efb5e51c91f33a\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"enrolled_university\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"enrolled_university\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\";\", \"columns\": [\"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"total_rows\": 19158, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 3.03}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..43ee8a08b19903617b86b7e71056777fb2de881f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:55.906442+00:00", + "ended_at": "2026-05-19T16:08:55.910207+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_3da77e5212fcafa1", + "problem_id": "v2p_m9_78efb5e51c91f33a", + "dataset_id": "m9", + "template_id": "tpl_missing_marginal_rate_profile", + "template_name": "Marginal Missing Rate Profile", + "family_id": "missingness_structure", + "canonical_subitem_id": "marginal_missing_rate_consistency", + "intended_facet_id": "missing_indicator_distribution", + "variant_semantic_role": "missing_indicator_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Marginal Missing Rate Profile to probe marginal_missing_rate_consistency with semantic role missing_indicator_view. Focus on missing_col=enrolled_university.", + "bindings": { + "missing_col": "enrolled_university" + }, + "binding_roles": [ + "missing_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table};", + "notes": [ + "default_facets=missing_indicator_distribution", + "template_selection_mode=deterministic", + "problem_index_within_template=2", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_3da77e5212fcafa1.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3da77e5212fcafa1/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..a7f76f2a01e83e4325d95c184d60e8534a755a27 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "Pvt Ltd", "support": 9817, "support_share": 0.5124230086647875, "cumulative_support": 9817}, {"value_label": "", "support": 6140, "support_share": 0.32049274454535964, "cumulative_support": 15957}, {"value_label": "Funded Startup", "support": 1001, "support_share": 0.05224971291366531, "cumulative_support": 16958}, {"value_label": "Public Sector", "support": 955, "support_share": 0.049848627205345025, "cumulative_support": 17913}, {"value_label": "Early Stage Startup", "support": 603, "support_share": 0.03147510178515503, "cumulative_support": 18516}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..ee94e54e858d032303898ff8f0a0bec8419cbbde --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/generated_sql.sql @@ -0,0 +1,28 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: support_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_cardinality_distinct_share_profile +-- query_record_id: v2q_m9_3e511195791e8d5f +-- problem_id: v2p_m9_c3f69d0e41bc1c82 +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "company_type" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "company_type" +), ranked AS ( + SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support + FROM grouped +) +SELECT * +FROM ranked +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..84b145191bb5009c19e5f7e1d6694d1259242691 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: ranked_signal_view\n-- template_id: tpl_cardinality_distinct_share_profile\n-- query_record_id: v2q_m9_3e511195791e8d5f\n-- problem_id: v2p_m9_c3f69d0e41bc1c82\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"company_type\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"company_type\"\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: ranked_signal_view\\n-- template_id: tpl_cardinality_distinct_share_profile\\n-- query_record_id: v2q_m9_3e511195791e8d5f\\n-- problem_id: v2p_m9_c3f69d0e41bc1c82\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"company_type\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"company_type\\\"\\n), ranked AS (\\n SELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\\n FROM grouped\\n)\\nSELECT *\\nFROM ranked\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"cumulative_support\"], \"rows\": [{\"value_label\": \"Pvt Ltd\", \"support\": 9817, \"support_share\": 0.5124230086647875, \"cumulative_support\": 9817}, {\"value_label\": \"\", \"support\": 6140, \"support_share\": 0.32049274454535964, \"cumulative_support\": 15957}, {\"value_label\": \"Funded Startup\", \"support\": 1001, \"support_share\": 0.05224971291366531, \"cumulative_support\": 16958}, {\"value_label\": \"Public Sector\", \"support\": 955, \"support_share\": 0.049848627205345025, \"cumulative_support\": 17913}, {\"value_label\": \"Early Stage Startup\", \"support\": 603, \"support_share\": 0.03147510178515503, \"cumulative_support\": 18516}, {\"value_label\": \"NGO\", \"support\": 521, \"support_share\": 0.02719490552249713, \"cumulative_support\": 19037}, {\"value_label\": \"Other\", \"support\": 121, \"support_share\": 0.006315899363190312, \"cumulative_support\": 19158}], \"row_count_returned\": 7, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 6.5}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..a81ef45430dc04eba777706ab9a764ce86744189 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.235960+00:00", + "ended_at": "2026-05-19T16:08:56.244133+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_3e511195791e8d5f", + "problem_id": "v2p_m9_c3f69d0e41bc1c82", + "dataset_id": "m9", + "template_id": "tpl_cardinality_distinct_share_profile", + "template_name": "Cardinality Distinct Share Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "support_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Distinct Share Profile to probe support_rank_profile_consistency with semantic role ranked_signal_view. Focus on group_col=company_type.", + "bindings": { + "group_col": "company_type" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=9", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 9, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_3e511195791e8d5f.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_3e511195791e8d5f/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..0e53f0c94259ee18316249c1108a4f951bba6999 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=company_size, measure_col=city_development_index. +Result preview: [{"company_size": "", "total_measure": 4840.433}, {"company_size": "50-99", "total_measure": 2556.904}, {"company_size": "100-500", "total_measure": 2147.117}, {"company_size": "10000+", "total_measure": 1708.489}, {"company_size": "10/49", "total_measure": 1197.287}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..6a5fcd225f0110aa00d89821301be54877dfa2fd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_conditional_contrast +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_m9_4088565feebc9016 +-- problem_id: v2p_m9_93ab0d62b0d41c6e +-- realization_mode: agent +-- source_kind: agent +SELECT + "company_size", + SUM(CAST(NULLIF("city_development_index", '') AS REAL)) AS "total_measure" +FROM "m9" +GROUP BY "company_size" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c1afffecefec64a828a52ab8fbae0b5692d38f30 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT\n \"company_size\",\n SUM(CAST(NULLIF(\"city_development_index\", '') AS REAL)) AS \"total_measure\"\nFROM \"m9\"\nGROUP BY \"company_size\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT\\n \\\"company_size\\\",\\n SUM(CAST(NULLIF(\\\"city_development_index\\\", '') AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"company_size\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"company_size\", \"total_measure\"], \"rows\": [{\"company_size\": \"\", \"total_measure\": 4840.433}, {\"company_size\": \"50-99\", \"total_measure\": 2556.904}, {\"company_size\": \"100-500\", \"total_measure\": 2147.117}, {\"company_size\": \"10000+\", \"total_measure\": 1708.489}, {\"company_size\": \"10/49\", \"total_measure\": 1197.287}, {\"company_size\": \"1000-4999\", \"total_measure\": 1138.266}, {\"company_size\": \"<10\", \"total_measure\": 1078.606}, {\"company_size\": \"500-999\", \"total_measure\": 733.945}, {\"company_size\": \"5000-9999\", \"total_measure\": 478.023}], \"row_count_returned\": 9, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 11.62}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..c38369c0223d9b59264eb017c429f850439a1b1e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:31:57.917584+00:00", + "ended_at": "2026-05-19T15:32:07.904599+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_4088565feebc9016", + "problem_id": "v2p_m9_93ab0d62b0d41c6e", + "dataset_id": "m9", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_conditional_contrast", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=company_size, measure_col=city_development_index.", + "bindings": { + "group_col": "company_size", + "measure_col": "city_development_index", + "top_k": 17, + "top_n": 7, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=2/2", + "binding_index=7" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 8, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_4088565feebc9016.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_4088565feebc9016", + "api_calls": 0, + "input_tokens": 14650, + "cached_input_tokens": 13696, + "output_tokens": 391, + "total_tokens": 15041, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9969.74, + "sql_execution_elapsed_ms_total": 11.62, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..51bee0cd844d316bf59cfe1b822f2127f29d422b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:32:07.891555+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9969.74, "started_at": "2026-05-19T15:31:57.920895+00:00", "ended_at": "2026-05-19T15:32:07.890671+00:00", "prompt_metrics": {"chars": 9319, "bytes_utf8": 9319, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 463, "bytes_utf8": 463, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14650, "cached_input_tokens": 13696, "output_tokens": 391, "reasoning_output_tokens": 270}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT\\n \\\"company_size\\\",\\n SUM(CAST(NULLIF(\\\"city_development_index\\\", '') AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"company_size\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Uses the planned grouped numeric sum template with group_col=\\\"company_size\\\" and measure_col=\\\"city_development_index\\\". Casts the text-valued measure to REAL and treats empty strings as NULL so SQLite can sum it correctly.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..c01ae1388f027445a892ed5d3af42fb99a4bd66c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_4088565feebc9016", + "api_calls": 0, + "input_tokens": 14650, + "cached_input_tokens": 13696, + "output_tokens": 391, + "total_tokens": 15041, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9969.74, + "sql_execution_elapsed_ms_total": 11.62, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4088565feebc9016/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..b4c9681b8049e3e69287cd4fbb8419c57b10e4f6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": []} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..2cd2cc4011f9ee11f1145dbb232aabbebbf3b049 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_m9_41247a499a22dd8c +-- problem_id: v2p_m9_90110f8d84570d1d +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "enrollee_id", + COUNT(*) AS support, + AVG("training_hours") AS avg_response +FROM "m9" +GROUP BY "enrollee_id" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ab05f36d37c218ae6431cf807748e084ed041cf9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_m9_41247a499a22dd8c\n-- problem_id: v2p_m9_90110f8d84570d1d\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"enrollee_id\",\n COUNT(*) AS support,\n AVG(\"training_hours\") AS avg_response\nFROM \"m9\"\nGROUP BY \"enrollee_id\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_m9_41247a499a22dd8c\\n-- problem_id: v2p_m9_90110f8d84570d1d\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"enrollee_id\\\",\\n COUNT(*) AS support,\\n AVG(\\\"training_hours\\\") AS avg_response\\nFROM \\\"m9\\\"\\nGROUP BY \\\"enrollee_id\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"enrollee_id\", \"support\", \"avg_response\"], \"rows\": [], \"row_count_returned\": 0, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 13.72}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..4ace817837a6ad81f0985f86f3dc90d022bf83b5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.388344+00:00", + "ended_at": "2026-05-19T16:08:56.402846+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_41247a499a22dd8c", + "problem_id": "v2p_m9_90110f8d84570d1d", + "dataset_id": "m9", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=training_hours, key_col=enrollee_id.", + "bindings": { + "key_col": "enrollee_id", + "measure_col": "training_hours", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=2", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_41247a499a22dd8c.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41247a499a22dd8c/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..5cb96cefd458b50da4cb1d24b1923532139d1d20 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=enrollee_id. +Result preview: [{"enrollee_id": "33380"}, {"enrollee_id": "33379"}, {"enrollee_id": "33377"}, {"enrollee_id": "33376"}, {"enrollee_id": "33375"}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..ee5e2a4438e28a8fcb0ed7f1185f93fb523e94a2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/generated_sql.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_m9_41350f98b5babc7a +-- problem_id: v2p_m9_2648fb534f046b0e +-- realization_mode: agent +-- source_kind: agent +WITH buckets AS ( + SELECT "enrollee_id", + NTILE(10) OVER (ORDER BY CAST("enrollee_id" AS INTEGER) DESC) AS tail_bucket + FROM "m9" +) +SELECT "enrollee_id" +FROM buckets +WHERE tail_bucket = 1 +ORDER BY CAST("enrollee_id" AS INTEGER) DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a366ed1762a06873522b02427a59719317ac3888 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH buckets AS (\n SELECT \"enrollee_id\",\n NTILE(10) OVER (ORDER BY CAST(\"enrollee_id\" AS INTEGER) DESC) AS tail_bucket\n FROM \"m9\"\n)\nSELECT \"enrollee_id\"\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY CAST(\"enrollee_id\" AS INTEGER) DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n SELECT \\\"enrollee_id\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"enrollee_id\\\" AS INTEGER) DESC) AS tail_bucket\\n FROM \\\"m9\\\"\\n)\\nSELECT \\\"enrollee_id\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY CAST(\\\"enrollee_id\\\" AS INTEGER) DESC;\", \"columns\": [\"enrollee_id\"], \"rows\": [{\"enrollee_id\": \"33380\"}, {\"enrollee_id\": \"33379\"}, {\"enrollee_id\": \"33377\"}, {\"enrollee_id\": \"33376\"}, {\"enrollee_id\": \"33375\"}, {\"enrollee_id\": \"33374\"}, {\"enrollee_id\": \"33373\"}, {\"enrollee_id\": \"33370\"}, {\"enrollee_id\": \"33368\"}, {\"enrollee_id\": \"33367\"}, {\"enrollee_id\": \"33365\"}, {\"enrollee_id\": \"33362\"}, {\"enrollee_id\": \"33360\"}, {\"enrollee_id\": \"33358\"}, {\"enrollee_id\": \"33357\"}, {\"enrollee_id\": \"33356\"}, {\"enrollee_id\": \"33352\"}, {\"enrollee_id\": \"33350\"}, {\"enrollee_id\": \"33349\"}, {\"enrollee_id\": \"33348\"}, {\"enrollee_id\": \"33344\"}, {\"enrollee_id\": \"33342\"}, {\"enrollee_id\": \"33341\"}, {\"enrollee_id\": \"33340\"}, {\"enrollee_id\": \"33339\"}, {\"enrollee_id\": \"33338\"}, {\"enrollee_id\": \"33337\"}, {\"enrollee_id\": \"33336\"}, {\"enrollee_id\": \"33335\"}, {\"enrollee_id\": \"33333\"}, {\"enrollee_id\": \"33332\"}, {\"enrollee_id\": \"33331\"}, {\"enrollee_id\": \"33330\"}, {\"enrollee_id\": \"33328\"}, {\"enrollee_id\": \"33327\"}, {\"enrollee_id\": \"33326\"}, {\"enrollee_id\": \"33325\"}, {\"enrollee_id\": \"33321\"}, {\"enrollee_id\": \"33318\"}, {\"enrollee_id\": \"33317\"}, {\"enrollee_id\": \"33315\"}, {\"enrollee_id\": \"33314\"}, {\"enrollee_id\": \"33312\"}, {\"enrollee_id\": \"33311\"}, {\"enrollee_id\": \"33310\"}, {\"enrollee_id\": \"33307\"}, {\"enrollee_id\": \"33306\"}, {\"enrollee_id\": \"33305\"}, {\"enrollee_id\": \"33304\"}, {\"enrollee_id\": \"33302\"}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 25.8}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..4b6a458f71c15cb489ce9dfbcc4335c42dd6c22e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:44:43.802425+00:00", + "ended_at": "2026-05-19T15:44:55.359832+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_41350f98b5babc7a", + "problem_id": "v2p_m9_2648fb534f046b0e", + "dataset_id": "m9", + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=enrollee_id.", + "bindings": { + "measure_col": "enrollee_id", + "top_k": 13, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/1", + "binding_index=63" + ], + "template_selection_mode": "rule", + "selected_template_rank": 6, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_41350f98b5babc7a.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_41350f98b5babc7a", + "api_calls": 0, + "input_tokens": 14703, + "cached_input_tokens": 13696, + "output_tokens": 550, + "total_tokens": 15253, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11527.29, + "sql_execution_elapsed_ms_total": 25.8, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3df5f7d917776e6e08f6ddf5187514a86ab80e5d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:44:55.332444+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11527.29, "started_at": "2026-05-19T15:44:43.804289+00:00", "ended_at": "2026-05-19T15:44:55.331609+00:00", "prompt_metrics": {"chars": 9461, "bytes_utf8": 9461, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 478, "bytes_utf8": 478, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14703, "cached_input_tokens": 13696, "output_tokens": 550, "reasoning_output_tokens": 408}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n SELECT \\\"enrollee_id\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"enrollee_id\\\" AS INTEGER) DESC) AS tail_bucket\\n FROM \\\"m9\\\"\\n)\\nSELECT \\\"enrollee_id\\\"\\nFROM buckets\\nWHERE tail_bucket = 1\\nORDER BY CAST(\\\"enrollee_id\\\" AS INTEGER) DESC;\",\"notes\":\"Applied the Quantile Tail Slice template with 10 tiles on \\\"m9\\\" and used a numeric cast for \\\"enrollee_id\\\" because the schema stores it as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..88d2f4991787b1a5c2a45472024da49d9e80d3cc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_41350f98b5babc7a", + "api_calls": 0, + "input_tokens": 14703, + "cached_input_tokens": 13696, + "output_tokens": 550, + "total_tokens": 15253, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11527.29, + "sql_execution_elapsed_ms_total": 25.8, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_41350f98b5babc7a/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..95384b3b6ffe858de8dc3931a52f0eaf6a8222b0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"company_size": "", "total_rows": 5938, "missing_rows": 0, "missing_rate": 0.0}, {"company_size": "50-99", "total_rows": 3083, "missing_rows": 0, "missing_rate": 0.0}, {"company_size": "100-500", "total_rows": 2571, "missing_rows": 0, "missing_rate": 0.0}, {"company_size": "10000+", "total_rows": 2019, "missing_rows": 0, "missing_rate": 0.0}, {"company_size": "10/49", "total_rows": 1471, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..d11898fce90eaf6359fe27b087bf7b751c634e8d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: co_missingness_pattern_consistency +-- intended_facet_id: missing_rate_by_subgroup +-- variant_semantic_role: missing_rate_by_subgroup +-- template_id: tpl_missing_rate_by_subgroup +-- query_record_id: v2q_m9_44ce333f71e09544 +-- problem_id: v2p_m9_6ff4bb8832d09dc9 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "company_size", + COUNT(*) AS total_rows, + SUM(CASE WHEN "education_level" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "education_level" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9" +GROUP BY "company_size" +ORDER BY missing_rate DESC, total_rows DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..36534e25af1d4c5e2d1cf77a2c431006a0c4a715 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: co_missingness_pattern_consistency\n-- intended_facet_id: missing_rate_by_subgroup\n-- variant_semantic_role: missing_rate_by_subgroup\n-- template_id: tpl_missing_rate_by_subgroup\n-- query_record_id: v2q_m9_44ce333f71e09544\n-- problem_id: v2p_m9_6ff4bb8832d09dc9\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"company_size\",\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"education_level\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"education_level\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\"\nGROUP BY \"company_size\"\nORDER BY missing_rate DESC, total_rows DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: co_missingness_pattern_consistency\\n-- intended_facet_id: missing_rate_by_subgroup\\n-- variant_semantic_role: missing_rate_by_subgroup\\n-- template_id: tpl_missing_rate_by_subgroup\\n-- query_record_id: v2q_m9_44ce333f71e09544\\n-- problem_id: v2p_m9_6ff4bb8832d09dc9\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"company_size\\\",\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"education_level\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"education_level\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"company_size\\\"\\nORDER BY missing_rate DESC, total_rows DESC;\", \"columns\": [\"company_size\", \"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"company_size\": \"\", \"total_rows\": 5938, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"50-99\", \"total_rows\": 3083, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"100-500\", \"total_rows\": 2571, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"10000+\", \"total_rows\": 2019, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"10/49\", \"total_rows\": 1471, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"1000-4999\", \"total_rows\": 1328, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"<10\", \"total_rows\": 1308, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"500-999\", \"total_rows\": 877, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"company_size\": \"5000-9999\", \"total_rows\": 563, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 9, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.01}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..1fa8aee65006b4c15266c035a30a9a820ce7f7fc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/run_manifest.json @@ -0,0 +1,59 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:55.976474+00:00", + "ended_at": "2026-05-19T16:08:55.986201+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_44ce333f71e09544", + "problem_id": "v2p_m9_6ff4bb8832d09dc9", + "dataset_id": "m9", + "template_id": "tpl_missing_rate_by_subgroup", + "template_name": "Missing Rate by Subgroup", + "family_id": "missingness_structure", + "canonical_subitem_id": "co_missingness_pattern_consistency", + "intended_facet_id": "missing_rate_by_subgroup", + "variant_semantic_role": "missing_rate_by_subgroup", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Missing Rate by Subgroup to probe co_missingness_pattern_consistency with semantic role missing_rate_by_subgroup. Focus on group_col=company_size, missing_col=education_level.", + "bindings": { + "missing_col": "education_level", + "group_col": "company_size" + }, + "binding_roles": [ + "missing_col", + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY missing_rate DESC, total_rows DESC;", + "notes": [ + "default_facets=missing_rate_by_subgroup,missing_target_interaction", + "template_selection_mode=deterministic", + "problem_index_within_template=5", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_44ce333f71e09544.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_44ce333f71e09544/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..f54ee74baed7abe7eeb964709aa9d44ae2f80375 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"experience": ">20", "support": 3286, "avg_response": 64.66889835666464}, {"experience": "5", "support": 1430, "avg_response": 67.23846153846154}, {"experience": "4", "support": 1403, "avg_response": 65.06557377049181}, {"experience": "3", "support": 1354, "avg_response": 65.67946824224519}, {"experience": "6", "support": 1216, "avg_response": 66.60773026315789}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..abfb5d076ae92bc19622061bbcc66d58e63b2b25 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_m9_4531ca1fc3c328c5 +-- problem_id: v2p_m9_d79a90bcdb8733e6 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "experience", + COUNT(*) AS support, + AVG("training_hours") AS avg_response +FROM "m9" +GROUP BY "experience" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1124ecbba78012059780404dab230a2185ca79d4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_m9_4531ca1fc3c328c5\n-- problem_id: v2p_m9_d79a90bcdb8733e6\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"experience\",\n COUNT(*) AS support,\n AVG(\"training_hours\") AS avg_response\nFROM \"m9\"\nGROUP BY \"experience\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_m9_4531ca1fc3c328c5\\n-- problem_id: v2p_m9_d79a90bcdb8733e6\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"experience\\\",\\n COUNT(*) AS support,\\n AVG(\\\"training_hours\\\") AS avg_response\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"experience\", \"support\", \"avg_response\"], \"rows\": [{\"experience\": \">20\", \"support\": 3286, \"avg_response\": 64.66889835666464}, {\"experience\": \"5\", \"support\": 1430, \"avg_response\": 67.23846153846154}, {\"experience\": \"4\", \"support\": 1403, \"avg_response\": 65.06557377049181}, {\"experience\": \"3\", \"support\": 1354, \"avg_response\": 65.67946824224519}, {\"experience\": \"6\", \"support\": 1216, \"avg_response\": 66.60773026315789}, {\"experience\": \"2\", \"support\": 1127, \"avg_response\": 63.23779946761313}, {\"experience\": \"7\", \"support\": 1028, \"avg_response\": 64.46206225680933}, {\"experience\": \"10\", \"support\": 985, \"avg_response\": 64.68020304568527}, {\"experience\": \"9\", \"support\": 980, \"avg_response\": 63.7469387755102}, {\"experience\": \"8\", \"support\": 802, \"avg_response\": 67.8927680798005}, {\"experience\": \"15\", \"support\": 686, \"avg_response\": 65.53206997084548}, {\"experience\": \"11\", \"support\": 664, \"avg_response\": 63.661144578313255}, {\"experience\": \"14\", \"support\": 586, \"avg_response\": 69.99829351535836}, {\"experience\": \"1\", \"support\": 549, \"avg_response\": 65.32058287795992}, {\"experience\": \"<1\", \"support\": 522, \"avg_response\": 61.35823754789272}, {\"experience\": \"16\", \"support\": 508, \"avg_response\": 68.87992125984252}, {\"experience\": \"12\", \"support\": 494, \"avg_response\": 70.21457489878543}, {\"experience\": \"13\", \"support\": 399, \"avg_response\": 63.48370927318296}, {\"experience\": \"17\", \"support\": 342, \"avg_response\": 58.58187134502924}, {\"experience\": \"19\", \"support\": 304, \"avg_response\": 68.45065789473684}, {\"experience\": \"18\", \"support\": 280, \"avg_response\": 66.66071428571429}, {\"experience\": \"20\", \"support\": 148, \"avg_response\": 60.49324324324324}, {\"experience\": \"\", \"support\": 65, \"avg_response\": 71.72307692307692}], \"row_count_returned\": 23, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.02}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..76c8e55f46c0e37a115439c09cad3def98e95e7a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.480339+00:00", + "ended_at": "2026-05-19T16:08:56.490090+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_4531ca1fc3c328c5", + "problem_id": "v2p_m9_d79a90bcdb8733e6", + "dataset_id": "m9", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=training_hours, key_col=experience.", + "bindings": { + "key_col": "experience", + "measure_col": "training_hours", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=10", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 10, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_4531ca1fc3c328c5.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ca1fc3c328c5/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a8258e23294c49c5b2f1a0a4aac988b2ed104937 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9559, "bytes_utf8": 9559, "lines": 267, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 483, "bytes_utf8": 483, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14706, "cached_input_tokens": 12032, "output_tokens": 417, "reasoning_output_tokens": 291}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..2b7a6b52e4e123887327f555d7c657f70757ed52 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_4531ecc9489cfc03", + "api_calls": 0, + "input_tokens": 14706, + "cached_input_tokens": 12032, + "output_tokens": 417, + "total_tokens": 15123, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10234.38, + "sql_execution_elapsed_ms_total": 9.4, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..093188351309c8a7b4c15ccabee91e420f8040c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:00:50.243010+00:00", + "ended_at": "2026-05-19T16:01:00.477416+00:00", + "elapsed_ms": 10234.38, + "prompt_metrics": { + "chars": 9559, + "bytes_utf8": 9559, + "lines": 267, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 847, + "bytes_utf8": 847, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 483, + "bytes_utf8": 483, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14706, + "cached_input_tokens": 12032, + "output_tokens": 417, + "reasoning_output_tokens": 291 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..ad8974bc33b349401430e14ed7cdfb0e64740ca5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,267 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=education_level, condition_col=major_discipline.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "education_level", + "condition_col": "major_discipline", + "condition_value": "", + "positive_value": "STEM", + "negative_value": "", + "top_k": 15, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..6b028bb2dc5eb59719fc8a290cf5c8892435e1bb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f7-ed41-7d93-93d3-481d228ca47a"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT\\n \\\"education_level\\\",\\n AVG(CASE WHEN \\\"major_discipline\\\" = 'STEM' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"education_level\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Applied the Grouped Condition Rate template with group_col=\\\"education_level\\\" and condition_col=\\\"major_discipline\\\". Since condition_value was blank, used the bound positive_value 'STEM' as the condition being measured.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14706,"cached_input_tokens":12032,"output_tokens":417,"reasoning_output_tokens":291}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..f40cc91719b657cf698e3b10654e750c88a6ef2e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT\n \"education_level\",\n AVG(CASE WHEN \"major_discipline\" = 'STEM' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"m9\"\nGROUP BY \"education_level\"\nORDER BY \"condition_rate\" DESC;","notes":"Applied the Grouped Condition Rate template with group_col=\"education_level\" and condition_col=\"major_discipline\". Since condition_value was blank, used the bound positive_value 'STEM' as the condition being measured."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4531ecc9489cfc03/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..2f19fb855570ff9788a51299e962495813e0eefa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=major_discipline, measure_col=training_hours. +Result preview: [{"major_discipline": "STEM", "group_value": 944971.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..06248691b44f130bd4f788a8ad62893d976cbdee --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/generated_sql.sql @@ -0,0 +1,34 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_m9_4706c75934b09268 +-- problem_id: v2p_m9_c05e8639eebd70bf +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT + "major_discipline", + SUM(CAST("training_hours" AS REAL)) AS "group_value" + FROM "m9" + WHERE "major_discipline" IS NOT NULL + AND "major_discipline" <> '' + AND "training_hours" IS NOT NULL + AND "training_hours" <> '' + GROUP BY "major_discipline" +), total AS ( + SELECT SUM("group_value") AS "total_value" + FROM grouped +) +SELECT + g."major_discipline", + g."group_value" +FROM grouped AS g +CROSS JOIN total AS t +WHERE g."group_value" > t."total_value" * 0.1 +ORDER BY g."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2eef06371193163d80f6ea9fc1d9a929cc8500bf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT\n \"major_discipline\",\n SUM(CAST(\"training_hours\" AS REAL)) AS \"group_value\"\n FROM \"m9\"\n WHERE \"major_discipline\" IS NOT NULL\n AND \"major_discipline\" <> ''\n AND \"training_hours\" IS NOT NULL\n AND \"training_hours\" <> ''\n GROUP BY \"major_discipline\"\n), total AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM grouped\n)\nSELECT\n g.\"major_discipline\",\n g.\"group_value\"\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT\\n \\\"major_discipline\\\",\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"major_discipline\\\" IS NOT NULL\\n AND \\\"major_discipline\\\" <> ''\\n AND \\\"training_hours\\\" IS NOT NULL\\n AND \\\"training_hours\\\" <> ''\\n GROUP BY \\\"major_discipline\\\"\\n), total AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM grouped\\n)\\nSELECT\\n g.\\\"major_discipline\\\",\\n g.\\\"group_value\\\"\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\", \"columns\": [\"major_discipline\", \"group_value\"], \"rows\": [{\"major_discipline\": \"STEM\", \"group_value\": 944971.0}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 15.44}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..1d59cd2fa2abe67ddd29cb685ce4af29c1461488 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:48:22.397954+00:00", + "ended_at": "2026-05-19T15:48:38.156499+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_4706c75934b09268", + "problem_id": "v2p_m9_c05e8639eebd70bf", + "dataset_id": "m9", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=major_discipline, measure_col=training_hours.", + "bindings": { + "group_col": "major_discipline", + "measure_col": "training_hours", + "top_k": 12, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=77" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_4706c75934b09268.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_4706c75934b09268", + "api_calls": 0, + "input_tokens": 14786, + "cached_input_tokens": 13696, + "output_tokens": 665, + "total_tokens": 15451, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15737.49, + "sql_execution_elapsed_ms_total": 15.44, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1da828fc595f3305a922099adad7d9be4d354962 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:48:38.138803+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15737.49, "started_at": "2026-05-19T15:48:22.399765+00:00", "ended_at": "2026-05-19T15:48:38.137292+00:00", "prompt_metrics": {"chars": 9864, "bytes_utf8": 9864, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 846, "bytes_utf8": 846, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14786, "cached_input_tokens": 13696, "output_tokens": 665, "reasoning_output_tokens": 435}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT\\n \\\"major_discipline\\\",\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"major_discipline\\\" IS NOT NULL\\n AND \\\"major_discipline\\\" <> ''\\n AND \\\"training_hours\\\" IS NOT NULL\\n AND \\\"training_hours\\\" <> ''\\n GROUP BY \\\"major_discipline\\\"\\n), total AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM grouped\\n)\\nSELECT\\n g.\\\"major_discipline\\\",\\n g.\\\"group_value\\\"\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Uses the planned threshold template with group_col=major_discipline and measure_col=training_hours, casting the TEXT measure to REAL and filtering blank/null values for a stable grouped view.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..7fd83d67a628866745df63639571972b39f60a19 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_4706c75934b09268", + "api_calls": 0, + "input_tokens": 14786, + "cached_input_tokens": 13696, + "output_tokens": 665, + "total_tokens": 15451, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15737.49, + "sql_execution_elapsed_ms_total": 15.44, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4706c75934b09268/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..09e8a832a6af6ca8461f172ad61c28e6e254c988 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=experience, measure_col=enrollee_id. +Result preview: [{"experience": "18", "percentile_measure": 32173.45}, {"experience": "2", "percentile_measure": 32122.2}, {"experience": "13", "percentile_measure": 32120.5}, {"experience": "19", "percentile_measure": 32053.449999999997}, {"experience": "17", "percentile_measure": 32001.649999999998}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..efbd3f2eeb102293505b0e78155fae755bc8510d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/generated_sql.sql @@ -0,0 +1,66 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_m9_4c8980cb676340ca +-- problem_id: v2p_m9_2cb0394c0800c8dd +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "experience", + CAST("enrollee_id" AS REAL) AS "measure_value", + ROW_NUMBER() OVER ( + PARTITION BY "experience" + ORDER BY CAST("enrollee_id" AS REAL) + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "experience" + ) AS "cnt" + FROM "m9" + WHERE "experience" IS NOT NULL + AND "experience" <> '' + AND "enrollee_id" IS NOT NULL + AND "enrollee_id" <> '' +), +"bounds" AS ( + SELECT DISTINCT + "experience", + (1.0 + (0.95 * ("cnt" - 1))) AS "rank_pos", + CAST((1.0 + (0.95 * ("cnt" - 1))) AS INTEGER) AS "lower_rn", + CASE + WHEN (1.0 + (0.95 * ("cnt" - 1))) = CAST((1.0 + (0.95 * ("cnt" - 1))) AS INTEGER) + THEN CAST((1.0 + (0.95 * ("cnt" - 1))) AS INTEGER) + ELSE CAST((1.0 + (0.95 * ("cnt" - 1))) AS INTEGER) + 1 + END AS "upper_rn" + FROM "ranked" +), +"points" AS ( + SELECT + "b"."experience", + "b"."lower_rn", + "b"."upper_rn", + ("b"."rank_pos" - "b"."lower_rn") AS "frac", + "lr"."measure_value" AS "lower_value", + "ur"."measure_value" AS "upper_value" + FROM "bounds" AS "b" + JOIN "ranked" AS "lr" + ON "lr"."experience" = "b"."experience" + AND "lr"."rn" = "b"."lower_rn" + JOIN "ranked" AS "ur" + ON "ur"."experience" = "b"."experience" + AND "ur"."rn" = "b"."upper_rn" +) +SELECT + "experience", + CASE + WHEN "lower_rn" = "upper_rn" THEN "lower_value" + ELSE "lower_value" + "frac" * ("upper_value" - "lower_value") + END AS "percentile_measure" +FROM "points" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b06d7bb97ba1af6f45d5f6364e1f80871b506c8a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n SELECT\n \"experience\",\n CAST(\"enrollee_id\" AS REAL) AS \"measure_value\",\n ROW_NUMBER() OVER (\n PARTITION BY \"experience\"\n ORDER BY CAST(\"enrollee_id\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (\n PARTITION BY \"experience\"\n ) AS \"cnt\"\n FROM \"m9\"\n WHERE \"experience\" IS NOT NULL\n AND \"experience\" <> ''\n AND \"enrollee_id\" IS NOT NULL\n AND \"enrollee_id\" <> ''\n),\n\"bounds\" AS (\n SELECT DISTINCT\n \"experience\",\n (1.0 + (0.95 * (\"cnt\" - 1))) AS \"rank_pos\",\n CAST((1.0 + (0.95 * (\"cnt\" - 1))) AS INTEGER) AS \"lower_rn\",\n CASE\n WHEN (1.0 + (0.95 * (\"cnt\" - 1))) = CAST((1.0 + (0.95 * (\"cnt\" - 1))) AS INTEGER)\n THEN CAST((1.0 + (0.95 * (\"cnt\" - 1))) AS INTEGER)\n ELSE CAST((1.0 + (0.95 * (\"cnt\" - 1))) AS INTEGER) + 1\n END AS \"upper_rn\"\n FROM \"ranked\"\n),\n\"points\" AS (\n SELECT\n \"b\".\"experience\",\n \"b\".\"lower_rn\",\n \"b\".\"upper_rn\",\n (\"b\".\"rank_pos\" - \"b\".\"lower_rn\") AS \"frac\",\n \"lr\".\"measure_value\" AS \"lower_value\",\n \"ur\".\"measure_value\" AS \"upper_value\"\n FROM \"bounds\" AS \"b\"\n JOIN \"ranked\" AS \"lr\"\n ON \"lr\".\"experience\" = \"b\".\"experience\"\n AND \"lr\".\"rn\" = \"b\".\"lower_rn\"\n JOIN \"ranked\" AS \"ur\"\n ON \"ur\".\"experience\" = \"b\".\"experience\"\n AND \"ur\".\"rn\" = \"b\".\"upper_rn\"\n)\nSELECT\n \"experience\",\n CASE\n WHEN \"lower_rn\" = \"upper_rn\" THEN \"lower_value\"\n ELSE \"lower_value\" + \"frac\" * (\"upper_value\" - \"lower_value\")\n END AS \"percentile_measure\"\nFROM \"points\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"experience\\\",\\n CAST(\\\"enrollee_id\\\" AS REAL) AS \\\"measure_value\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"experience\\\"\\n ORDER BY CAST(\\\"enrollee_id\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"experience\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"experience\\\" IS NOT NULL\\n AND \\\"experience\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\n),\\n\\\"bounds\\\" AS (\\n SELECT DISTINCT\\n \\\"experience\\\",\\n (1.0 + (0.95 * (\\\"cnt\\\" - 1))) AS \\\"rank_pos\\\",\\n CAST((1.0 + (0.95 * (\\\"cnt\\\" - 1))) AS INTEGER) AS \\\"lower_rn\\\",\\n CASE\\n WHEN (1.0 + (0.95 * (\\\"cnt\\\" - 1))) = CAST((1.0 + (0.95 * (\\\"cnt\\\" - 1))) AS INTEGER)\\n THEN CAST((1.0 + (0.95 * (\\\"cnt\\\" - 1))) AS INTEGER)\\n ELSE CAST((1.0 + (0.95 * (\\\"cnt\\\" - 1))) AS INTEGER) + 1\\n END AS \\\"upper_rn\\\"\\n FROM \\\"ranked\\\"\\n),\\n\\\"points\\\" AS (\\n SELECT\\n \\\"b\\\".\\\"experience\\\",\\n \\\"b\\\".\\\"lower_rn\\\",\\n \\\"b\\\".\\\"upper_rn\\\",\\n (\\\"b\\\".\\\"rank_pos\\\" - \\\"b\\\".\\\"lower_rn\\\") AS \\\"frac\\\",\\n \\\"lr\\\".\\\"measure_value\\\" AS \\\"lower_value\\\",\\n \\\"ur\\\".\\\"measure_value\\\" AS \\\"upper_value\\\"\\n FROM \\\"bounds\\\" AS \\\"b\\\"\\n JOIN \\\"ranked\\\" AS \\\"lr\\\"\\n ON \\\"lr\\\".\\\"experience\\\" = \\\"b\\\".\\\"experience\\\"\\n AND \\\"lr\\\".\\\"rn\\\" = \\\"b\\\".\\\"lower_rn\\\"\\n JOIN \\\"ranked\\\" AS \\\"ur\\\"\\n ON \\\"ur\\\".\\\"experience\\\" = \\\"b\\\".\\\"experience\\\"\\n AND \\\"ur\\\".\\\"rn\\\" = \\\"b\\\".\\\"upper_rn\\\"\\n)\\nSELECT\\n \\\"experience\\\",\\n CASE\\n WHEN \\\"lower_rn\\\" = \\\"upper_rn\\\" THEN \\\"lower_value\\\"\\n ELSE \\\"lower_value\\\" + \\\"frac\\\" * (\\\"upper_value\\\" - \\\"lower_value\\\")\\n END AS \\\"percentile_measure\\\"\\nFROM \\\"points\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"experience\", \"percentile_measure\"], \"rows\": [{\"experience\": \"18\", \"percentile_measure\": 32173.45}, {\"experience\": \"2\", \"percentile_measure\": 32122.2}, {\"experience\": \"13\", \"percentile_measure\": 32120.5}, {\"experience\": \"19\", \"percentile_measure\": 32053.449999999997}, {\"experience\": \"17\", \"percentile_measure\": 32001.649999999998}, {\"experience\": \"11\", \"percentile_measure\": 31907.95}, {\"experience\": \"5\", \"percentile_measure\": 31891.4}, {\"experience\": \"3\", \"percentile_measure\": 31791.85}, {\"experience\": \"10\", \"percentile_measure\": 31790.6}, {\"experience\": \"4\", \"percentile_measure\": 31780.1}, {\"experience\": \"6\", \"percentile_measure\": 31773.0}, {\"experience\": \"14\", \"percentile_measure\": 31738.0}, {\"experience\": \"1\", \"percentile_measure\": 31737.200000000004}, {\"experience\": \"12\", \"percentile_measure\": 31728.899999999998}, {\"experience\": \"7\", \"percentile_measure\": 31722.25}, {\"experience\": \"15\", \"percentile_measure\": 31700.0}, {\"experience\": \"16\", \"percentile_measure\": 31692.149999999998}, {\"experience\": \"9\", \"percentile_measure\": 31660.2}, {\"experience\": \">20\", \"percentile_measure\": 31659.25}, {\"experience\": \"<1\", \"percentile_measure\": 31588.7}, {\"experience\": \"8\", \"percentile_measure\": 31371.1}, {\"experience\": \"20\", \"percentile_measure\": 30938.85}], \"row_count_returned\": 22, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 68.04}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..99f70efdbabc281fc7ee00290a7658fa55fef079 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:56:01.232616+00:00", + "ended_at": "2026-05-19T15:56:41.570793+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_4c8980cb676340ca", + "problem_id": "v2p_m9_2cb0394c0800c8dd", + "dataset_id": "m9", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=experience, measure_col=enrollee_id.", + "bindings": { + "group_col": "experience", + "measure_col": "enrollee_id", + "top_k": 10, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/2", + "binding_index=90" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_4c8980cb676340ca.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_4c8980cb676340ca", + "api_calls": 0, + "input_tokens": 14686, + "cached_input_tokens": 12032, + "output_tokens": 2407, + "total_tokens": 17093, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 40264.34, + "sql_execution_elapsed_ms_total": 68.04, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a030425010b05766fb9a91f37218e8f9c97d0c1e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:56:41.500528+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 40264.34, "started_at": "2026-05-19T15:56:01.235327+00:00", "ended_at": "2026-05-19T15:56:41.499697+00:00", "prompt_metrics": {"chars": 9474, "bytes_utf8": 9474, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 1979, "bytes_utf8": 1979, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14686, "cached_input_tokens": 12032, "output_tokens": 2407, "reasoning_output_tokens": 1746}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"experience\\\",\\n CAST(\\\"enrollee_id\\\" AS REAL) AS \\\"measure_value\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"experience\\\"\\n ORDER BY CAST(\\\"enrollee_id\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"experience\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"experience\\\" IS NOT NULL\\n AND \\\"experience\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\n),\\n\\\"bounds\\\" AS (\\n SELECT DISTINCT\\n \\\"experience\\\",\\n (1.0 + (0.95 * (\\\"cnt\\\" - 1))) AS \\\"rank_pos\\\",\\n CAST((1.0 + (0.95 * (\\\"cnt\\\" - 1))) AS INTEGER) AS \\\"lower_rn\\\",\\n CASE\\n WHEN (1.0 + (0.95 * (\\\"cnt\\\" - 1))) = CAST((1.0 + (0.95 * (\\\"cnt\\\" - 1))) AS INTEGER)\\n THEN CAST((1.0 + (0.95 * (\\\"cnt\\\" - 1))) AS INTEGER)\\n ELSE CAST((1.0 + (0.95 * (\\\"cnt\\\" - 1))) AS INTEGER) + 1\\n END AS \\\"upper_rn\\\"\\n FROM \\\"ranked\\\"\\n),\\n\\\"points\\\" AS (\\n SELECT\\n "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..db786e13f463016bac40df924a0d522fca4bc1de --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_4c8980cb676340ca", + "api_calls": 0, + "input_tokens": 14686, + "cached_input_tokens": 12032, + "output_tokens": 2407, + "total_tokens": 17093, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 40264.34, + "sql_execution_elapsed_ms_total": 68.04, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4c8980cb676340ca/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..0d848f0aeaa76fa8145e998f7a397b141550d084 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=major_discipline, measure_col=training_hours. +Result preview: [{"major_discipline": "No Major", "enrollee_id": "15741", "total_measure": 314.0, "share_within_group": 2.237104588201767}, {"major_discipline": "No Major", "enrollee_id": "31271", "total_measure": 304.0, "share_within_group": 2.165859219150755}, {"major_discipline": "Arts", "enrollee_id": "6302", "total_measure": 322.0, "share_within_group": 2.1116138763197587}, {"major_discipline": "No Major", "enrollee_id": "7951", "total_measure": 292.0, "share_within_group": 2.080364776289541}, {"major_discipline": "No Major", "enrollee_id": "27253", "total_measure": 290.0, "share_within_group": 2.0661157024793386}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..2fe043b9b92a891a1a78f1434a6430c025330146 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/generated_sql.sql @@ -0,0 +1,27 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_m9_4e6a7a50e53f1c56 +-- problem_id: v2p_m9_b049b4a2b0cafb1f +-- realization_mode: agent +-- source_kind: agent +SELECT + "major_discipline", + "enrollee_id", + SUM(CAST("training_hours" AS REAL)) AS "total_measure", + SUM(CAST("training_hours" AS REAL)) * 100.0 / SUM(SUM(CAST("training_hours" AS REAL))) OVER (PARTITION BY "major_discipline") AS "share_within_group" +FROM "m9" +WHERE "major_discipline" IS NOT NULL + AND "major_discipline" <> '' + AND "enrollee_id" IS NOT NULL + AND "enrollee_id" <> '' + AND "training_hours" IS NOT NULL + AND "training_hours" <> '' +GROUP BY "major_discipline", "enrollee_id" +ORDER BY "share_within_group" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2dc5ab8a98c67e40dbfe65e7359052aa8c866d6a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"major_discipline\",\n \"enrollee_id\",\n SUM(CAST(\"training_hours\" AS REAL)) AS \"total_measure\",\n SUM(CAST(\"training_hours\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"training_hours\" AS REAL))) OVER (PARTITION BY \"major_discipline\") AS \"share_within_group\"\nFROM \"m9\"\nWHERE \"major_discipline\" IS NOT NULL\n AND \"major_discipline\" <> ''\n AND \"enrollee_id\" IS NOT NULL\n AND \"enrollee_id\" <> ''\n AND \"training_hours\" IS NOT NULL\n AND \"training_hours\" <> ''\nGROUP BY \"major_discipline\", \"enrollee_id\"\nORDER BY \"share_within_group\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"major_discipline\\\",\\n \\\"enrollee_id\\\",\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"training_hours\\\" AS REAL))) OVER (PARTITION BY \\\"major_discipline\\\") AS \\\"share_within_group\\\"\\nFROM \\\"m9\\\"\\nWHERE \\\"major_discipline\\\" IS NOT NULL\\n AND \\\"major_discipline\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\n AND \\\"training_hours\\\" IS NOT NULL\\n AND \\\"training_hours\\\" <> ''\\nGROUP BY \\\"major_discipline\\\", \\\"enrollee_id\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\", \"columns\": [\"major_discipline\", \"enrollee_id\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"major_discipline\": \"No Major\", \"enrollee_id\": \"15741\", \"total_measure\": 314.0, \"share_within_group\": 2.237104588201767}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"31271\", \"total_measure\": 304.0, \"share_within_group\": 2.165859219150755}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"6302\", \"total_measure\": 322.0, \"share_within_group\": 2.1116138763197587}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"7951\", \"total_measure\": 292.0, \"share_within_group\": 2.080364776289541}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"27253\", \"total_measure\": 290.0, \"share_within_group\": 2.0661157024793386}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"5013\", \"total_measure\": 288.0, \"share_within_group\": 2.0518666286691367}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"2844\", \"total_measure\": 242.0, \"share_within_group\": 1.7241379310344827}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"13028\", \"total_measure\": 260.0, \"share_within_group\": 1.7050298380221653}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"30804\", \"total_measure\": 258.0, \"share_within_group\": 1.6919142238835334}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"27200\", \"total_measure\": 240.0, \"share_within_group\": 1.5738736966358449}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"13799\", \"total_measure\": 212.0, \"share_within_group\": 1.5104018238814476}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"14212\", \"total_measure\": 312.0, \"share_within_group\": 1.4415080391794493}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"3064\", \"total_measure\": 308.0, \"share_within_group\": 1.423027166882277}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"7640\", \"total_measure\": 304.0, \"share_within_group\": 1.4045462945851044}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"31792\", \"total_measure\": 206.0, \"share_within_group\": 1.3509082562791002}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"26396\", \"total_measure\": 290.0, \"share_within_group\": 1.339863241545001}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"27539\", \"total_measure\": 188.0, \"share_within_group\": 1.3394129381590196}, {\"major_discipline\": \"Other\", \"enrollee_id\": \"6564\", \"total_measure\": 334.0, \"share_within_group\": 1.3272402145837472}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"12383\", \"total_measure\": 278.0, \"share_within_group\": 1.2844206246534837}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"1596\", \"total_measure\": 180.0, \"share_within_group\": 1.2824166429182102}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"29017\", \"total_measure\": 194.0, \"share_within_group\": 1.272214571447308}, {\"major_discipline\": \"Other\", \"enrollee_id\": \"3753\", \"total_measure\": 312.0, \"share_within_group\": 1.2398172064375124}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"13320\", \"total_measure\": 174.0, \"share_within_group\": 1.2396694214876034}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"662\", \"total_measure\": 188.0, \"share_within_group\": 1.2328677290314118}, {\"major_discipline\": \"Other\", \"enrollee_id\": \"18392\", \"total_measure\": 304.0, \"share_within_group\": 1.2080270216570634}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"14199\", \"total_measure\": 260.0, \"share_within_group\": 1.2012566993162077}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"23074\", \"total_measure\": 256.0, \"share_within_group\": 1.1827758270190354}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"3025\", \"total_measure\": 166.0, \"share_within_group\": 1.182673126246794}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"3940\", \"total_measure\": 180.0, \"share_within_group\": 1.1804052724768836}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"19262\", \"total_measure\": 178.0, \"share_within_group\": 1.1672896583382517}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"24682\", \"total_measure\": 178.0, \"share_within_group\": 1.1672896583382517}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"5549\", \"total_measure\": 172.0, \"share_within_group\": 1.1279428159223555}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"24173\", \"total_measure\": 158.0, \"share_within_group\": 1.1256768310059846}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"6029\", \"total_measure\": 170.0, \"share_within_group\": 1.1148272017837235}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"2762\", \"total_measure\": 156.0, \"share_within_group\": 1.1114277571957822}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"28651\", \"total_measure\": 156.0, \"share_within_group\": 1.1114277571957822}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"6384\", \"total_measure\": 156.0, \"share_within_group\": 1.1114277571957822}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"10404\", \"total_measure\": 154.0, \"share_within_group\": 1.09717868338558}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"29106\", \"total_measure\": 150.0, \"share_within_group\": 1.0686805357651752}, {\"major_discipline\": \"Other\", \"enrollee_id\": \"11551\", \"total_measure\": 268.0, \"share_within_group\": 1.0649711901450427}, {\"major_discipline\": \"Other\", \"enrollee_id\": \"31117\", \"total_measure\": 268.0, \"share_within_group\": 1.0649711901450427}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"25513\", \"total_measure\": 161.0, \"share_within_group\": 1.0558069381598794}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"20928\", \"total_measure\": 148.0, \"share_within_group\": 1.0544314619549728}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"7616\", \"total_measure\": 226.0, \"share_within_group\": 1.0441692847902422}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"13620\", \"total_measure\": 146.0, \"share_within_group\": 1.0401823881447705}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"3093\", \"total_measure\": 157.0, \"share_within_group\": 1.0295757098826153}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"16999\", \"total_measure\": 144.0, \"share_within_group\": 1.0259333143345684}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"8572\", \"total_measure\": 222.0, \"share_within_group\": 1.0256884124930696}, {\"major_discipline\": \"Other\", \"enrollee_id\": \"27000\", \"total_measure\": 256.0, \"share_within_group\": 1.0172859129743692}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"641\", \"total_measure\": 154.0, \"share_within_group\": 1.0099022886746671}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 62.32}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..4102f290281cf179839d9afe393c074e6ee1450b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:36:41.629653+00:00", + "ended_at": "2026-05-19T15:36:58.450655+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_4e6a7a50e53f1c56", + "problem_id": "v2p_m9_b049b4a2b0cafb1f", + "dataset_id": "m9", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=major_discipline, measure_col=training_hours.", + "bindings": { + "group_col": "major_discipline", + "measure_col": "training_hours", + "item_col": "enrollee_id", + "top_k": 14, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=29" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_4e6a7a50e53f1c56.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_4e6a7a50e53f1c56", + "api_calls": 0, + "input_tokens": 14768, + "cached_input_tokens": 13696, + "output_tokens": 916, + "total_tokens": 15684, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16753.32, + "sql_execution_elapsed_ms_total": 62.32, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f34987ae9155eea5f10b445d9277472e5cf98ebe --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:36:58.386121+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 16753.32, "started_at": "2026-05-19T15:36:41.631911+00:00", "ended_at": "2026-05-19T15:36:58.385263+00:00", "prompt_metrics": {"chars": 9717, "bytes_utf8": 9717, "lines": 266, "estimated_tokens": null}, "response_metrics": {"chars": 870, "bytes_utf8": 870, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14768, "cached_input_tokens": 13696, "output_tokens": 916, "reasoning_output_tokens": 668}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"major_discipline\\\",\\n \\\"enrollee_id\\\",\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"training_hours\\\" AS REAL))) OVER (PARTITION BY \\\"major_discipline\\\") AS \\\"share_within_group\\\"\\nFROM \\\"m9\\\"\\nWHERE \\\"major_discipline\\\" IS NOT NULL\\n AND \\\"major_discipline\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\n AND \\\"training_hours\\\" IS NOT NULL\\n AND \\\"training_hours\\\" <> ''\\nGROUP BY \\\"major_discipline\\\", \\\"enrollee_id\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\",\"notes\":\"Applied the provided template with group_col=\\\"major_discipline\\\", item_col=\\\"enrollee_id\\\", and measure_col=\\\"training_hours\\\". Cast \\\"training_hours\\\" from TEXT to REAL for aggregation and excluded blank keys/measures.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..298f14d9bf4e55315872ce24141dc802f537b782 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_4e6a7a50e53f1c56", + "api_calls": 0, + "input_tokens": 14768, + "cached_input_tokens": 13696, + "output_tokens": 916, + "total_tokens": 15684, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16753.32, + "sql_execution_elapsed_ms_total": 62.32, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4e6a7a50e53f1c56/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..cd951cb530dc75dbfd5b4b61bb7d0f5aca729bbc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=gender, measure_col=city_development_index. +Result preview: [{"gender": "Other", "percentile_measure": 0.9259999999999999}, {"gender": "Male", "percentile_measure": 0.9259999999999999}, {"gender": "Female", "percentile_measure": 0.9229999999999999}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..4ba03adb38facf1b1831f301d2ed681b519c64fa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/generated_sql.sql @@ -0,0 +1,35 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_m9_4fe32b6b75ad6eae +-- problem_id: v2p_m9_0e03de9ffb92066e +-- realization_mode: agent +-- source_kind: agent +WITH ranked AS ( + SELECT + "gender", + CAST("city_development_index" AS REAL) AS "measure_value", + ROW_NUMBER() OVER ( + PARTITION BY "gender" + ORDER BY CAST("city_development_index" AS REAL) + ) AS "rn", + COUNT(*) OVER (PARTITION BY "gender") AS "cnt" + FROM "m9" + WHERE "gender" IS NOT NULL + AND "gender" <> '' + AND "city_development_index" IS NOT NULL + AND "city_development_index" <> '' +) +SELECT + "gender", + MIN("measure_value") AS "percentile_measure" +FROM ranked +WHERE CAST("rn" AS REAL) / "cnt" >= 0.9 +GROUP BY "gender" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d4ae9f8a74e46d7bbbd67e474be4dd6420f0ba13 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH ranked AS (\n SELECT\n \"gender\",\n CAST(\"city_development_index\" AS REAL) AS \"measure_value\",\n ROW_NUMBER() OVER (\n PARTITION BY \"gender\"\n ORDER BY CAST(\"city_development_index\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (PARTITION BY \"gender\") AS \"cnt\"\n FROM \"m9\"\n WHERE \"gender\" IS NOT NULL\n AND \"gender\" <> ''\n AND \"city_development_index\" IS NOT NULL\n AND \"city_development_index\" <> ''\n)\nSELECT\n \"gender\",\n MIN(\"measure_value\") AS \"percentile_measure\"\nFROM ranked\nWHERE CAST(\"rn\" AS REAL) / \"cnt\" >= 0.9\nGROUP BY \"gender\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH ranked AS (\\n SELECT\\n \\\"gender\\\",\\n CAST(\\\"city_development_index\\\" AS REAL) AS \\\"measure_value\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"gender\\\"\\n ORDER BY CAST(\\\"city_development_index\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"gender\\\") AS \\\"cnt\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"gender\\\" IS NOT NULL\\n AND \\\"gender\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n)\\nSELECT\\n \\\"gender\\\",\\n MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\nFROM ranked\\nWHERE CAST(\\\"rn\\\" AS REAL) / \\\"cnt\\\" >= 0.9\\nGROUP BY \\\"gender\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"gender\", \"percentile_measure\"], \"rows\": [{\"gender\": \"Other\", \"percentile_measure\": 0.9259999999999999}, {\"gender\": \"Male\", \"percentile_measure\": 0.9259999999999999}, {\"gender\": \"Female\", \"percentile_measure\": 0.9229999999999999}], \"row_count_returned\": 3, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 54.45}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..b8ef736346bf66a448903c5918af497774a42528 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:51:45.431154+00:00", + "ended_at": "2026-05-19T15:52:00.399453+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_4fe32b6b75ad6eae", + "problem_id": "v2p_m9_0e03de9ffb92066e", + "dataset_id": "m9", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=gender, measure_col=city_development_index.", + "bindings": { + "group_col": "gender", + "measure_col": "city_development_index", + "top_k": 10, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/2", + "binding_index=85" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_4fe32b6b75ad6eae.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_4fe32b6b75ad6eae", + "api_calls": 0, + "input_tokens": 14686, + "cached_input_tokens": 12032, + "output_tokens": 776, + "total_tokens": 15462, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14908.62, + "sql_execution_elapsed_ms_total": 54.45, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d87daedece9a071d3c8fd970f8c1a6a5d86ad932 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:52:00.343067+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14908.62, "started_at": "2026-05-19T15:51:45.433346+00:00", "ended_at": "2026-05-19T15:52:00.342027+00:00", "prompt_metrics": {"chars": 9482, "bytes_utf8": 9482, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 959, "bytes_utf8": 959, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14686, "cached_input_tokens": 12032, "output_tokens": 776, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH ranked AS (\\n SELECT\\n \\\"gender\\\",\\n CAST(\\\"city_development_index\\\" AS REAL) AS \\\"measure_value\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"gender\\\"\\n ORDER BY CAST(\\\"city_development_index\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (PARTITION BY \\\"gender\\\") AS \\\"cnt\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"gender\\\" IS NOT NULL\\n AND \\\"gender\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n)\\nSELECT\\n \\\"gender\\\",\\n MIN(\\\"measure_value\\\") AS \\\"percentile_measure\\\"\\nFROM ranked\\nWHERE CAST(\\\"rn\\\" AS REAL) / \\\"cnt\\\" >= 0.9\\nGROUP BY \\\"gender\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this uses a grouped nearest-rank 90th percentile approximation with window functions and casts \\\"city_development_index\\\" from TEXT to REAL; empty/null gender and measure values are excluded.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..e4ae8bbe60b5b58fc8a36a2366f6bc4d4e88a5ef --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_4fe32b6b75ad6eae", + "api_calls": 0, + "input_tokens": 14686, + "cached_input_tokens": 12032, + "output_tokens": 776, + "total_tokens": 15462, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14908.62, + "sql_execution_elapsed_ms_total": 54.45, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_4fe32b6b75ad6eae/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3bd0d92a81bfb03f6267a53c726d094250aac77e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=major_discipline, measure_col=training_hours. +Result preview: [{"major_discipline": "No Major", "enrollee_id": "15741", "total_measure": 314.0, "share_within_group": 2.237104588201767}, {"major_discipline": "No Major", "enrollee_id": "31271", "total_measure": 304.0, "share_within_group": 2.165859219150755}, {"major_discipline": "Arts", "enrollee_id": "6302", "total_measure": 322.0, "share_within_group": 2.1116138763197587}, {"major_discipline": "No Major", "enrollee_id": "7951", "total_measure": 292.0, "share_within_group": 2.080364776289541}, {"major_discipline": "No Major", "enrollee_id": "27253", "total_measure": 290.0, "share_within_group": 2.0661157024793386}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..dc37870cf32db1f99d53da9a6025c81eb2ea7c5c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/generated_sql.sql @@ -0,0 +1,25 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_m9_504cec37ca19abaa +-- problem_id: v2p_m9_c74c92ba50a00068 +-- realization_mode: agent +-- source_kind: agent +SELECT + "major_discipline", + "enrollee_id", + SUM(CAST(NULLIF("training_hours", '') AS REAL)) AS total_measure, + SUM(CAST(NULLIF("training_hours", '') AS REAL)) * 100.0 + / SUM(SUM(CAST(NULLIF("training_hours", '') AS REAL))) OVER (PARTITION BY "major_discipline") AS share_within_group +FROM "m9" +WHERE NULLIF("major_discipline", '') IS NOT NULL + AND NULLIF("enrollee_id", '') IS NOT NULL + AND NULLIF("training_hours", '') IS NOT NULL +GROUP BY "major_discipline", "enrollee_id" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c4ca41a469d0124945b8e65d818312062a3055ff --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"major_discipline\",\n \"enrollee_id\",\n SUM(CAST(NULLIF(\"training_hours\", '') AS REAL)) AS total_measure,\n SUM(CAST(NULLIF(\"training_hours\", '') AS REAL)) * 100.0\n / SUM(SUM(CAST(NULLIF(\"training_hours\", '') AS REAL))) OVER (PARTITION BY \"major_discipline\") AS share_within_group\nFROM \"m9\"\nWHERE NULLIF(\"major_discipline\", '') IS NOT NULL\n AND NULLIF(\"enrollee_id\", '') IS NOT NULL\n AND NULLIF(\"training_hours\", '') IS NOT NULL\nGROUP BY \"major_discipline\", \"enrollee_id\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"major_discipline\\\",\\n \\\"enrollee_id\\\",\\n SUM(CAST(NULLIF(\\\"training_hours\\\", '') AS REAL)) AS total_measure,\\n SUM(CAST(NULLIF(\\\"training_hours\\\", '') AS REAL)) * 100.0\\n / SUM(SUM(CAST(NULLIF(\\\"training_hours\\\", '') AS REAL))) OVER (PARTITION BY \\\"major_discipline\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nWHERE NULLIF(\\\"major_discipline\\\", '') IS NOT NULL\\n AND NULLIF(\\\"enrollee_id\\\", '') IS NOT NULL\\n AND NULLIF(\\\"training_hours\\\", '') IS NOT NULL\\nGROUP BY \\\"major_discipline\\\", \\\"enrollee_id\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"major_discipline\", \"enrollee_id\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"major_discipline\": \"No Major\", \"enrollee_id\": \"15741\", \"total_measure\": 314.0, \"share_within_group\": 2.237104588201767}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"31271\", \"total_measure\": 304.0, \"share_within_group\": 2.165859219150755}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"6302\", \"total_measure\": 322.0, \"share_within_group\": 2.1116138763197587}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"7951\", \"total_measure\": 292.0, \"share_within_group\": 2.080364776289541}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"27253\", \"total_measure\": 290.0, \"share_within_group\": 2.0661157024793386}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"5013\", \"total_measure\": 288.0, \"share_within_group\": 2.0518666286691367}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"2844\", \"total_measure\": 242.0, \"share_within_group\": 1.7241379310344827}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"13028\", \"total_measure\": 260.0, \"share_within_group\": 1.7050298380221653}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"30804\", \"total_measure\": 258.0, \"share_within_group\": 1.6919142238835334}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"27200\", \"total_measure\": 240.0, \"share_within_group\": 1.5738736966358449}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"13799\", \"total_measure\": 212.0, \"share_within_group\": 1.5104018238814476}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"14212\", \"total_measure\": 312.0, \"share_within_group\": 1.4415080391794493}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"3064\", \"total_measure\": 308.0, \"share_within_group\": 1.423027166882277}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"7640\", \"total_measure\": 304.0, \"share_within_group\": 1.4045462945851044}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"31792\", \"total_measure\": 206.0, \"share_within_group\": 1.3509082562791002}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"26396\", \"total_measure\": 290.0, \"share_within_group\": 1.339863241545001}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"27539\", \"total_measure\": 188.0, \"share_within_group\": 1.3394129381590196}, {\"major_discipline\": \"Other\", \"enrollee_id\": \"6564\", \"total_measure\": 334.0, \"share_within_group\": 1.3272402145837472}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"12383\", \"total_measure\": 278.0, \"share_within_group\": 1.2844206246534837}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"1596\", \"total_measure\": 180.0, \"share_within_group\": 1.2824166429182102}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"29017\", \"total_measure\": 194.0, \"share_within_group\": 1.272214571447308}, {\"major_discipline\": \"Other\", \"enrollee_id\": \"3753\", \"total_measure\": 312.0, \"share_within_group\": 1.2398172064375124}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"13320\", \"total_measure\": 174.0, \"share_within_group\": 1.2396694214876034}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"662\", \"total_measure\": 188.0, \"share_within_group\": 1.2328677290314118}, {\"major_discipline\": \"Other\", \"enrollee_id\": \"18392\", \"total_measure\": 304.0, \"share_within_group\": 1.2080270216570634}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"14199\", \"total_measure\": 260.0, \"share_within_group\": 1.2012566993162077}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"23074\", \"total_measure\": 256.0, \"share_within_group\": 1.1827758270190354}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"3025\", \"total_measure\": 166.0, \"share_within_group\": 1.182673126246794}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"3940\", \"total_measure\": 180.0, \"share_within_group\": 1.1804052724768836}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"19262\", \"total_measure\": 178.0, \"share_within_group\": 1.1672896583382517}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"24682\", \"total_measure\": 178.0, \"share_within_group\": 1.1672896583382517}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"5549\", \"total_measure\": 172.0, \"share_within_group\": 1.1279428159223555}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"24173\", \"total_measure\": 158.0, \"share_within_group\": 1.1256768310059846}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"6029\", \"total_measure\": 170.0, \"share_within_group\": 1.1148272017837235}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"2762\", \"total_measure\": 156.0, \"share_within_group\": 1.1114277571957822}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"28651\", \"total_measure\": 156.0, \"share_within_group\": 1.1114277571957822}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"6384\", \"total_measure\": 156.0, \"share_within_group\": 1.1114277571957822}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"10404\", \"total_measure\": 154.0, \"share_within_group\": 1.09717868338558}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"29106\", \"total_measure\": 150.0, \"share_within_group\": 1.0686805357651752}, {\"major_discipline\": \"Other\", \"enrollee_id\": \"11551\", \"total_measure\": 268.0, \"share_within_group\": 1.0649711901450427}, {\"major_discipline\": \"Other\", \"enrollee_id\": \"31117\", \"total_measure\": 268.0, \"share_within_group\": 1.0649711901450427}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"25513\", \"total_measure\": 161.0, \"share_within_group\": 1.0558069381598794}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"20928\", \"total_measure\": 148.0, \"share_within_group\": 1.0544314619549728}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"7616\", \"total_measure\": 226.0, \"share_within_group\": 1.0441692847902422}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"13620\", \"total_measure\": 146.0, \"share_within_group\": 1.0401823881447705}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"3093\", \"total_measure\": 157.0, \"share_within_group\": 1.0295757098826153}, {\"major_discipline\": \"No Major\", \"enrollee_id\": \"16999\", \"total_measure\": 144.0, \"share_within_group\": 1.0259333143345684}, {\"major_discipline\": \"Business Degree\", \"enrollee_id\": \"8572\", \"total_measure\": 222.0, \"share_within_group\": 1.0256884124930696}, {\"major_discipline\": \"Other\", \"enrollee_id\": \"27000\", \"total_measure\": 256.0, \"share_within_group\": 1.0172859129743692}, {\"major_discipline\": \"Arts\", \"enrollee_id\": \"641\", \"total_measure\": 154.0, \"share_within_group\": 1.0099022886746671}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 81.89}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..880f70f96108d56a284627fc0fa66f19907efc79 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:36:58.451208+00:00", + "ended_at": "2026-05-19T15:37:17.701556+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_504cec37ca19abaa", + "problem_id": "v2p_m9_c74c92ba50a00068", + "dataset_id": "m9", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=major_discipline, measure_col=training_hours.", + "bindings": { + "group_col": "major_discipline", + "measure_col": "training_hours", + "item_col": "enrollee_id", + "top_k": 19, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 70.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=2/2", + "binding_index=29" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 6, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_504cec37ca19abaa.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_504cec37ca19abaa", + "api_calls": 0, + "input_tokens": 14769, + "cached_input_tokens": 13696, + "output_tokens": 754, + "total_tokens": 15523, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 19163.3, + "sql_execution_elapsed_ms_total": 81.89, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e239efc0258fbbe5d8631a67a089bfcaf21f4684 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:37:17.617477+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 19163.3, "started_at": "2026-05-19T15:36:58.452967+00:00", "ended_at": "2026-05-19T15:37:17.616296+00:00", "prompt_metrics": {"chars": 9724, "bytes_utf8": 9724, "lines": 266, "estimated_tokens": null}, "response_metrics": {"chars": 881, "bytes_utf8": 881, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14769, "cached_input_tokens": 13696, "output_tokens": 754, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"major_discipline\\\",\\n \\\"enrollee_id\\\",\\n SUM(CAST(NULLIF(\\\"training_hours\\\", '') AS REAL)) AS total_measure,\\n SUM(CAST(NULLIF(\\\"training_hours\\\", '') AS REAL)) * 100.0\\n / SUM(SUM(CAST(NULLIF(\\\"training_hours\\\", '') AS REAL))) OVER (PARTITION BY \\\"major_discipline\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nWHERE NULLIF(\\\"major_discipline\\\", '') IS NOT NULL\\n AND NULLIF(\\\"enrollee_id\\\", '') IS NOT NULL\\n AND NULLIF(\\\"training_hours\\\", '') IS NOT NULL\\nGROUP BY \\\"major_discipline\\\", \\\"enrollee_id\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Uses the requested template with group_col=\\\"major_discipline\\\", item_col=\\\"enrollee_id\\\", and measure_col=\\\"training_hours\\\". Since \\\"training_hours\\\" is stored as TEXT, the query casts non-empty values to REAL and filters out empty strings before aggregation.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..93344c4259e90b4a18eaa4e0f874e8ad23cf9fdf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_504cec37ca19abaa", + "api_calls": 0, + "input_tokens": 14769, + "cached_input_tokens": 13696, + "output_tokens": 754, + "total_tokens": 15523, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 19163.3, + "sql_execution_elapsed_ms_total": 81.89, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_504cec37ca19abaa/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5157bef19897be56/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5157bef19897be56/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..5c82b15e429f5f76320ee7829bb1f6d21b54912b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5157bef19897be56/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"training_hours": "28", "support": 329, "avg_response": 0.8267841945288754}, {"training_hours": "12", "support": 292, "avg_response": 0.8300102739726027}, {"training_hours": "18", "support": 291, "avg_response": 0.8228694158075602}, {"training_hours": "22", "support": 282, "avg_response": 0.8318297872340426}, {"training_hours": "50", "support": 279, "avg_response": 0.8241218637992832}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5157bef19897be56/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5157bef19897be56/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..ded0b3ba26706e11458333f4728b8bbd13b9cfd7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5157bef19897be56/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_m9_5157bef19897be56 +-- problem_id: v2p_m9_18318667be0a1a13 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "training_hours", + COUNT(*) AS support, + AVG("city_development_index") AS avg_response +FROM "m9" +GROUP BY "training_hours" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5157bef19897be56/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5157bef19897be56/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..36dd33ad7cfe295e0bfc3cca21f8888eeb9f6362 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5157bef19897be56/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_m9_5157bef19897be56\n-- problem_id: v2p_m9_18318667be0a1a13\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"training_hours\",\n COUNT(*) AS support,\n AVG(\"city_development_index\") AS avg_response\nFROM \"m9\"\nGROUP BY \"training_hours\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_m9_5157bef19897be56\\n-- problem_id: v2p_m9_18318667be0a1a13\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"training_hours\\\",\\n COUNT(*) AS support,\\n AVG(\\\"city_development_index\\\") AS avg_response\\nFROM \\\"m9\\\"\\nGROUP BY \\\"training_hours\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"training_hours\", \"support\", \"avg_response\"], \"rows\": [{\"training_hours\": \"28\", \"support\": 329, \"avg_response\": 0.8267841945288754}, {\"training_hours\": \"12\", \"support\": 292, \"avg_response\": 0.8300102739726027}, {\"training_hours\": \"18\", \"support\": 291, \"avg_response\": 0.8228694158075602}, {\"training_hours\": \"22\", \"support\": 282, \"avg_response\": 0.8318297872340426}, {\"training_hours\": \"50\", \"support\": 279, \"avg_response\": 0.8241218637992832}, {\"training_hours\": \"20\", \"support\": 278, \"avg_response\": 0.8208237410071942}, {\"training_hours\": \"24\", \"support\": 273, \"avg_response\": 0.8264212454212454}, {\"training_hours\": \"17\", \"support\": 273, \"avg_response\": 0.8208424908424908}, {\"training_hours\": \"34\", \"support\": 261, \"avg_response\": 0.8359616858237549}, {\"training_hours\": \"6\", \"support\": 261, \"avg_response\": 0.8314980842911878}, {\"training_hours\": \"23\", \"support\": 258, \"avg_response\": 0.8194534883720931}, {\"training_hours\": \"21\", \"support\": 256, \"avg_response\": 0.8193515625}, {\"training_hours\": \"26\", \"support\": 254, \"avg_response\": 0.8215905511811024}, {\"training_hours\": \"56\", \"support\": 250, \"avg_response\": 0.824136}, {\"training_hours\": \"42\", \"support\": 242, \"avg_response\": 0.8382644628099174}, {\"training_hours\": \"10\", \"support\": 241, \"avg_response\": 0.8222531120331951}, {\"training_hours\": \"11\", \"support\": 237, \"avg_response\": 0.834240506329114}, {\"training_hours\": \"48\", \"support\": 237, \"avg_response\": 0.8257004219409283}, {\"training_hours\": \"9\", \"support\": 234, \"avg_response\": 0.8251068376068376}, {\"training_hours\": \"14\", \"support\": 231, \"avg_response\": 0.8285887445887445}, {\"training_hours\": \"15\", \"support\": 230, \"avg_response\": 0.8301391304347826}, {\"training_hours\": \"8\", \"support\": 227, \"avg_response\": 0.8401321585903084}, {\"training_hours\": \"4\", \"support\": 224, \"avg_response\": 0.8195401785714286}, {\"training_hours\": \"46\", \"support\": 223, \"avg_response\": 0.8334304932735426}, {\"training_hours\": \"13\", \"support\": 213, \"avg_response\": 0.8146948356807512}, {\"training_hours\": \"36\", \"support\": 211, \"avg_response\": 0.829478672985782}, {\"training_hours\": \"7\", \"support\": 209, \"avg_response\": 0.8180239234449761}, {\"training_hours\": \"32\", \"support\": 207, \"avg_response\": 0.8196135265700483}, {\"training_hours\": \"44\", \"support\": 205, \"avg_response\": 0.8203121951219513}, {\"training_hours\": \"25\", \"support\": 199, \"avg_response\": 0.8245075376884422}, {\"training_hours\": \"43\", \"support\": 199, \"avg_response\": 0.8183768844221105}, {\"training_hours\": \"52\", \"support\": 196, \"avg_response\": 0.838811224489796}, {\"training_hours\": \"16\", \"support\": 192, \"avg_response\": 0.8396718750000001}, {\"training_hours\": \"40\", \"support\": 192, \"avg_response\": 0.8329739583333334}, {\"training_hours\": \"30\", \"support\": 187, \"avg_response\": 0.8390267379679144}, {\"training_hours\": \"31\", \"support\": 184, \"avg_response\": 0.8257065217391305}, {\"training_hours\": \"29\", \"support\": 179, \"avg_response\": 0.8367541899441341}, {\"training_hours\": \"39\", \"support\": 178, \"avg_response\": 0.8342078651685394}, {\"training_hours\": \"51\", \"support\": 176, \"avg_response\": 0.8261818181818182}, {\"training_hours\": \"45\", \"support\": 175, \"avg_response\": 0.8349314285714285}, {\"training_hours\": \"55\", \"support\": 171, \"avg_response\": 0.8251988304093568}, {\"training_hours\": \"78\", \"support\": 165, \"avg_response\": 0.8271454545454546}, {\"training_hours\": \"19\", \"support\": 163, \"avg_response\": 0.8404601226993865}, {\"training_hours\": \"37\", \"support\": 163, \"avg_response\": 0.8300736196319018}, {\"training_hours\": \"35\", \"support\": 162, \"avg_response\": 0.8378518518518518}, {\"training_hours\": \"54\", \"support\": 161, \"avg_response\": 0.849608695652174}, {\"training_hours\": \"47\", \"support\": 157, \"avg_response\": 0.8348343949044585}, {\"training_hours\": \"72\", \"support\": 153, \"avg_response\": 0.839437908496732}, {\"training_hours\": \"33\", \"support\": 150, \"avg_response\": 0.8429}, {\"training_hours\": \"41\", \"support\": 145, \"avg_response\": 0.8409862068965517}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 11.76}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..26bbd8c822a51426ae1b3193d5ec81f1abf70e0c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=experience. +Result preview: [{"experience": ">20", "row_count": 3286}, {"experience": "5", "row_count": 1430}, {"experience": "4", "row_count": 1403}, {"experience": "3", "row_count": 1354}, {"experience": "6", "row_count": 1216}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..e98afffe260764ad2a5a7abed32658b3c3e602e8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_m9_52930b19a0530d19 +-- problem_id: v2p_m9_4956e6a19843522d +-- realization_mode: agent +-- source_kind: agent +SELECT "experience", COUNT(*) AS row_count +FROM "m9" +GROUP BY "experience" +ORDER BY row_count DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8764c5c8a3047fee0ffca8e76084eb7de03cfb59 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"experience\", COUNT(*) AS row_count\nFROM \"m9\"\nGROUP BY \"experience\"\nORDER BY row_count DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"experience\\\", COUNT(*) AS row_count\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\"\\nORDER BY row_count DESC;\", \"columns\": [\"experience\", \"row_count\"], \"rows\": [{\"experience\": \">20\", \"row_count\": 3286}, {\"experience\": \"5\", \"row_count\": 1430}, {\"experience\": \"4\", \"row_count\": 1403}, {\"experience\": \"3\", \"row_count\": 1354}, {\"experience\": \"6\", \"row_count\": 1216}, {\"experience\": \"2\", \"row_count\": 1127}, {\"experience\": \"7\", \"row_count\": 1028}, {\"experience\": \"10\", \"row_count\": 985}, {\"experience\": \"9\", \"row_count\": 980}, {\"experience\": \"8\", \"row_count\": 802}, {\"experience\": \"15\", \"row_count\": 686}, {\"experience\": \"11\", \"row_count\": 664}, {\"experience\": \"14\", \"row_count\": 586}, {\"experience\": \"1\", \"row_count\": 549}, {\"experience\": \"<1\", \"row_count\": 522}, {\"experience\": \"16\", \"row_count\": 508}, {\"experience\": \"12\", \"row_count\": 494}, {\"experience\": \"13\", \"row_count\": 399}, {\"experience\": \"17\", \"row_count\": 342}, {\"experience\": \"19\", \"row_count\": 304}, {\"experience\": \"18\", \"row_count\": 280}, {\"experience\": \"20\", \"row_count\": 148}, {\"experience\": \"\", \"row_count\": 65}], \"row_count_returned\": 23, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.89}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..c5fc503f14575f20c1362939d3f7243664eecb61 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:33:27.512504+00:00", + "ended_at": "2026-05-19T15:33:34.674241+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_52930b19a0530d19", + "problem_id": "v2p_m9_4956e6a19843522d", + "dataset_id": "m9", + "template_id": "tpl_clickbench_group_count", + "template_name": "Grouped Count by Category", + "family_id": "subgroup_structure", + "canonical_subitem_id": "subgroup_size_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=experience.", + "bindings": { + "group_col": "experience", + "top_k": 13, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/1", + "binding_index=18" + ], + "template_selection_mode": "rule", + "selected_template_rank": 2, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_52930b19a0530d19.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_52930b19a0530d19", + "api_calls": 0, + "input_tokens": 14618, + "cached_input_tokens": 12032, + "output_tokens": 225, + "total_tokens": 14843, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7147.43, + "sql_execution_elapsed_ms_total": 9.89, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..05f2670351b059bb3d22f81e149b7b38fd7f6854 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:33:34.662558+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 7147.43, "started_at": "2026-05-19T15:33:27.514272+00:00", "ended_at": "2026-05-19T15:33:34.661729+00:00", "prompt_metrics": {"chars": 9199, "bytes_utf8": 9199, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 283, "bytes_utf8": 283, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14618, "cached_input_tokens": 12032, "output_tokens": 225, "reasoning_output_tokens": 151}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"experience\\\", COUNT(*) AS row_count\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Applied the provided grouped-count template with group_col bound to \\\"experience\\\" on the single table \\\"m9\\\".\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..2910601c9ecc425b1ec27d92d71df3cdaf673ddf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_52930b19a0530d19", + "api_calls": 0, + "input_tokens": 14618, + "cached_input_tokens": 12032, + "output_tokens": 225, + "total_tokens": 14843, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7147.43, + "sql_execution_elapsed_ms_total": 9.89, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_52930b19a0530d19/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..2e1f6c669d3bc37877c58348e5755ca9d419ceed --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=enrolled_university. +Result preview: [{"enrolled_university": "no_enrollment", "row_count": 13817}, {"enrolled_university": "Full time course", "row_count": 3757}, {"enrolled_university": "Part time course", "row_count": 1198}, {"enrolled_university": "", "row_count": 386}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..345c723f87bcd0d6d804e76fc28f9cfc4cd04e87 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_m9_54e2ae1c7a2dc453 +-- problem_id: v2p_m9_e4ea32b3149c89ce +-- realization_mode: agent +-- source_kind: agent +SELECT "enrolled_university", COUNT(*) AS row_count +FROM "m9" +GROUP BY "enrolled_university" +ORDER BY row_count DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2ad28b263201eac04b6609a8688d2aaf6839cf18 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"enrolled_university\", COUNT(*) AS row_count\nFROM \"m9\"\nGROUP BY \"enrolled_university\"\nORDER BY row_count DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"enrolled_university\\\", COUNT(*) AS row_count\\nFROM \\\"m9\\\"\\nGROUP BY \\\"enrolled_university\\\"\\nORDER BY row_count DESC;\", \"columns\": [\"enrolled_university\", \"row_count\"], \"rows\": [{\"enrolled_university\": \"no_enrollment\", \"row_count\": 13817}, {\"enrolled_university\": \"Full time course\", \"row_count\": 3757}, {\"enrolled_university\": \"Part time course\", \"row_count\": 1198}, {\"enrolled_university\": \"\", \"row_count\": 386}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 7.52}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..034c6a4a7897405a4652bd033c809a3794a5150e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:32:50.070675+00:00", + "ended_at": "2026-05-19T15:33:05.595519+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_54e2ae1c7a2dc453", + "problem_id": "v2p_m9_e4ea32b3149c89ce", + "dataset_id": "m9", + "template_id": "tpl_clickbench_group_count", + "template_name": "Grouped Count by Category", + "family_id": "subgroup_structure", + "canonical_subitem_id": "subgroup_size_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=enrolled_university.", + "bindings": { + "group_col": "enrolled_university", + "top_k": 10, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/1", + "binding_index=15" + ], + "template_selection_mode": "rule", + "selected_template_rank": 2, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_54e2ae1c7a2dc453.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_54e2ae1c7a2dc453", + "api_calls": 0, + "input_tokens": 14623, + "cached_input_tokens": 12032, + "output_tokens": 258, + "total_tokens": 14881, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15512.93, + "sql_execution_elapsed_ms_total": 7.52, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1423d42a313c1a5f01a73e641c0f896b4f35b0a1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:33:05.586422+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15512.93, "started_at": "2026-05-19T15:32:50.072606+00:00", "ended_at": "2026-05-19T15:33:05.585561+00:00", "prompt_metrics": {"chars": 9216, "bytes_utf8": 9216, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 321, "bytes_utf8": 321, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14623, "cached_input_tokens": 12032, "output_tokens": 258, "reasoning_output_tokens": 174}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"enrolled_university\\\", COUNT(*) AS row_count\\nFROM \\\"m9\\\"\\nGROUP BY \\\"enrolled_university\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Grouped count by \\\"enrolled_university\\\" using the planned template; empty strings, if present, will appear as their own category.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..3c2f86b74d79901ee3ea89e307fa692a4b2922c1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_54e2ae1c7a2dc453", + "api_calls": 0, + "input_tokens": 14623, + "cached_input_tokens": 12032, + "output_tokens": 258, + "total_tokens": 14881, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15512.93, + "sql_execution_elapsed_ms_total": 7.52, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_54e2ae1c7a2dc453/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..834f3744dfce32e3fbd91c9d3aa914c62395c134 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9736, "bytes_utf8": 9736, "lines": 266, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 942, "bytes_utf8": 942, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14770, "cached_input_tokens": 12032, "output_tokens": 754, "reasoning_output_tokens": 516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..b519fade3bbe478bba75480ea687b290a89a6232 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_557d0de19d5251a0", + "api_calls": 0, + "input_tokens": 14770, + "cached_input_tokens": 12032, + "output_tokens": 754, + "total_tokens": 15524, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14588.23, + "sql_execution_elapsed_ms_total": 35.07, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..79f99793a9b6d0af28aa3b30f339367e087317c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:37:54.885071+00:00", + "ended_at": "2026-05-19T15:38:09.473335+00:00", + "elapsed_ms": 14588.23, + "prompt_metrics": { + "chars": 9736, + "bytes_utf8": 9736, + "lines": 266, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1344, + "bytes_utf8": 1344, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 942, + "bytes_utf8": 942, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14770, + "cached_input_tokens": 12032, + "output_tokens": 754, + "reasoning_output_tokens": 516 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..cf34a4eb3eaf0cf64de00a26edb8720594c8be5c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,266 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "required_roles": [ + "group_col", + "item_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=company_size, measure_col=city_development_index.", + "planned_template_id": "tpl_tpcds_within_group_share", + "bindings": { + "group_col": "company_size", + "measure_col": "city_development_index", + "item_col": "city_development_index", + "top_k": 11, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..fc4453509f521a3196a2c02489b809b719c7a55a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40e2-f0c7-7712-bf3b-621018e965a7"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"company_size\\\",\\n \\\"city_development_index\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"city_development_index\\\" AS REAL))) OVER (PARTITION BY \\\"company_size\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nWHERE \\\"company_size\\\" IS NOT NULL\\n AND \\\"company_size\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\nGROUP BY \\\"company_size\\\", \\\"city_development_index\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Applied the provided Within-Group Share of Total template with group_col=\\\"company_size\\\", item_col=\\\"city_development_index\\\", and measure_col=\\\"city_development_index\\\". Cast the measure from TEXT to REAL for SQLite numeric aggregation and filtered empty/null group and measure values to avoid invalid numeric contributions.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14770,"cached_input_tokens":12032,"output_tokens":754,"reasoning_output_tokens":516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..a0be518d4f55068dd7cd7fd58976112afa6fcfe0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"company_size\",\n \"city_development_index\",\n SUM(CAST(\"city_development_index\" AS REAL)) AS total_measure,\n SUM(CAST(\"city_development_index\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"city_development_index\" AS REAL))) OVER (PARTITION BY \"company_size\") AS share_within_group\nFROM \"m9\"\nWHERE \"company_size\" IS NOT NULL\n AND \"company_size\" <> ''\n AND \"city_development_index\" IS NOT NULL\n AND \"city_development_index\" <> ''\nGROUP BY \"company_size\", \"city_development_index\"\nORDER BY share_within_group DESC;","notes":"Applied the provided Within-Group Share of Total template with group_col=\"company_size\", item_col=\"city_development_index\", and measure_col=\"city_development_index\". Cast the measure from TEXT to REAL for SQLite numeric aggregation and filtered empty/null group and measure values to avoid invalid numeric contributions."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_557d0de19d5251a0/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..5e57503dd015af70157df2d0cac64e9f132c0943 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"target": "0.0", "total_rows": 14381, "missing_rows": 0, "missing_rate": 0.0}, {"target": "1.0", "total_rows": 4777, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..c57a3a99ac630d98add2bef00fb28e291d5994f0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: co_missingness_pattern_consistency +-- intended_facet_id: missing_target_interaction +-- variant_semantic_role: missing_target_interaction +-- template_id: tpl_missing_target_interaction +-- query_record_id: v2q_m9_5657ae760fe9fa94 +-- problem_id: v2p_m9_5db7699c8717ec6a +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "target", + COUNT(*) AS total_rows, + SUM(CASE WHEN "gender" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "gender" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9" +GROUP BY "target" +ORDER BY missing_rate DESC, total_rows DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..50c090ee1258b86360c2fc3a6fbb102f3e229384 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: co_missingness_pattern_consistency\n-- intended_facet_id: missing_target_interaction\n-- variant_semantic_role: missing_target_interaction\n-- template_id: tpl_missing_target_interaction\n-- query_record_id: v2q_m9_5657ae760fe9fa94\n-- problem_id: v2p_m9_5db7699c8717ec6a\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"target\",\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"gender\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"gender\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\"\nGROUP BY \"target\"\nORDER BY missing_rate DESC, total_rows DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: co_missingness_pattern_consistency\\n-- intended_facet_id: missing_target_interaction\\n-- variant_semantic_role: missing_target_interaction\\n-- template_id: tpl_missing_target_interaction\\n-- query_record_id: v2q_m9_5657ae760fe9fa94\\n-- problem_id: v2p_m9_5db7699c8717ec6a\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"target\\\",\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"gender\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"gender\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"target\\\"\\nORDER BY missing_rate DESC, total_rows DESC;\", \"columns\": [\"target\", \"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"target\": \"0.0\", \"total_rows\": 14381, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"target\": \"1.0\", \"total_rows\": 4777, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 7.7}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..59f5902a2a2c6a3e83d49517b6d22e21a5d40657 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/run_manifest.json @@ -0,0 +1,59 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.056531+00:00", + "ended_at": "2026-05-19T16:08:56.064878+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_5657ae760fe9fa94", + "problem_id": "v2p_m9_5db7699c8717ec6a", + "dataset_id": "m9", + "template_id": "tpl_missing_target_interaction", + "template_name": "Missingness-Target Interaction", + "family_id": "missingness_structure", + "canonical_subitem_id": "co_missingness_pattern_consistency", + "intended_facet_id": "missing_target_interaction", + "variant_semantic_role": "missing_target_interaction", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Missingness-Target Interaction to probe co_missingness_pattern_consistency with semantic role missing_target_interaction. Focus on target_col=target, missing_col=gender.", + "bindings": { + "missing_col": "gender", + "target_col": "target" + }, + "binding_roles": [ + "missing_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {target_col},\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {target_col}\nORDER BY missing_rate DESC, total_rows DESC;", + "notes": [ + "default_facets=missing_rate_by_subgroup,missing_target_interaction", + "template_selection_mode=deterministic", + "problem_index_within_template=1", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_5657ae760fe9fa94.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5657ae760fe9fa94/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..77779bced86bcf42ae6b50a53642ff9ecae450f0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "Male", "support": 13221, "support_share": 0.6901033510804886, "cumulative_support": 13221}, {"value_label": "", "support": 4508, "support_share": 0.23530639941538783, "cumulative_support": 17729}, {"value_label": "Female", "support": 1238, "support_share": 0.0646205240630546, "cumulative_support": 18967}, {"value_label": "Other", "support": 191, "support_share": 0.009969725441069005, "cumulative_support": 19158}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..ea43cf50fec818f2510781d501e96bce42aeb30b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/generated_sql.sql @@ -0,0 +1,28 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: value_imbalance_profile +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_cardinality_distinct_share_profile +-- query_record_id: v2q_m9_57d4ee48d966d7de +-- problem_id: v2p_m9_dbd40defc53572b7 +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "gender" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "gender" +), ranked AS ( + SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support + FROM grouped +) +SELECT * +FROM ranked +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..dc459874a8389efad66c64b700dafbfd64b47185 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: value_imbalance_profile\n-- variant_semantic_role: ranked_signal_view\n-- template_id: tpl_cardinality_distinct_share_profile\n-- query_record_id: v2q_m9_57d4ee48d966d7de\n-- problem_id: v2p_m9_dbd40defc53572b7\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"gender\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"gender\"\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: value_imbalance_profile\\n-- variant_semantic_role: ranked_signal_view\\n-- template_id: tpl_cardinality_distinct_share_profile\\n-- query_record_id: v2q_m9_57d4ee48d966d7de\\n-- problem_id: v2p_m9_dbd40defc53572b7\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"gender\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"gender\\\"\\n), ranked AS (\\n SELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\\n FROM grouped\\n)\\nSELECT *\\nFROM ranked\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"cumulative_support\"], \"rows\": [{\"value_label\": \"Male\", \"support\": 13221, \"support_share\": 0.6901033510804886, \"cumulative_support\": 13221}, {\"value_label\": \"\", \"support\": 4508, \"support_share\": 0.23530639941538783, \"cumulative_support\": 17729}, {\"value_label\": \"Female\", \"support\": 1238, \"support_share\": 0.0646205240630546, \"cumulative_support\": 18967}, {\"value_label\": \"Other\", \"support\": 191, \"support_share\": 0.009969725441069005, \"cumulative_support\": 19158}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.89}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..fd9cb87b071bda0e6a1ea36b546c85e749417e92 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.183567+00:00", + "ended_at": "2026-05-19T16:08:56.190251+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_57d4ee48d966d7de", + "problem_id": "v2p_m9_dbd40defc53572b7", + "dataset_id": "m9", + "template_id": "tpl_cardinality_distinct_share_profile", + "template_name": "Cardinality Distinct Share Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "value_imbalance_profile", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Distinct Share Profile to probe support_rank_profile_consistency with semantic role ranked_signal_view. Focus on group_col=gender.", + "bindings": { + "group_col": "gender" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=2", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_57d4ee48d966d7de.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_57d4ee48d966d7de/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5a6f475ca820eda1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5a6f475ca820eda1/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..8e6d6fb125a4f496d99b7b76a1d2b58edc2cfd57 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5a6f475ca820eda1/run_manifest.json @@ -0,0 +1,67 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:03:19.261690+00:00", + "ended_at": "2026-05-19T16:03:26.974544+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_5a6f475ca820eda1", + "problem_id": "v2p_m9_5123deefa11ae46d", + "dataset_id": "m9", + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=city_development_index.", + "bindings": { + "measure_col": "city_development_index", + "top_k": 12, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=1/1", + "binding_index=112" + ], + "template_selection_mode": "rule", + "selected_template_rank": 10, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5a6f475ca820eda1/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5a6f475ca820eda1/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..bb0728d2fd41c8f3431bee6597f86dea879706bb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5a6f475ca820eda1/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:03:22.560705+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3296.39, "started_at": "2026-05-19T16:03:19.263450+00:00", "ended_at": "2026-05-19T16:03:22.559870+00:00", "prompt_metrics": {"chars": 9246, "bytes_utf8": 9246, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fa-3373-7ed0-b179-9ac8c76bd65c\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:03:26.974418+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3411.16, "started_at": "2026-05-19T16:03:23.562208+00:00", "ended_at": "2026-05-19T16:03:26.973419+00:00", "prompt_metrics": {"chars": 9246, "bytes_utf8": 9246, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fa-4447-7171-8d1d-3528f0fc3544\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..a57b5e2b8cbc82e9f5b2c64a3c6d950cce774f50 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=major_discipline, measure_col=training_hours. +Result preview: [{"major_discipline": "STEM", "total_measure": 944971.0}, {"major_discipline": "", "total_measure": 187324.0}, {"major_discipline": "Humanities", "total_measure": 43910.0}, {"major_discipline": "Other", "total_measure": 25165.0}, {"major_discipline": "Business Degree", "total_measure": 21644.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..287c506c8b2f0c78851dd8ac979332b80151556a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_conditional_contrast +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_m9_5b13630789372daa +-- problem_id: v2p_m9_b9dfed4189077979 +-- realization_mode: agent +-- source_kind: agent +SELECT "major_discipline", SUM(CAST("training_hours" AS REAL)) AS "total_measure" +FROM "m9" +GROUP BY "major_discipline" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a05c880cd19a7886006813f0fc9914faf4e3e1b0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"major_discipline\", SUM(CAST(\"training_hours\" AS REAL)) AS \"total_measure\"\nFROM \"m9\"\nGROUP BY \"major_discipline\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"major_discipline\\\", SUM(CAST(\\\"training_hours\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"major_discipline\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"major_discipline\", \"total_measure\"], \"rows\": [{\"major_discipline\": \"STEM\", \"total_measure\": 944971.0}, {\"major_discipline\": \"\", \"total_measure\": 187324.0}, {\"major_discipline\": \"Humanities\", \"total_measure\": 43910.0}, {\"major_discipline\": \"Other\", \"total_measure\": 25165.0}, {\"major_discipline\": \"Business Degree\", \"total_measure\": 21644.0}, {\"major_discipline\": \"Arts\", \"total_measure\": 15249.0}, {\"major_discipline\": \"No Major\", \"total_measure\": 14036.0}], \"row_count_returned\": 7, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.02}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e54b89f8851296d20c4e792a8372cd749a90d831 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:30:32.479365+00:00", + "ended_at": "2026-05-19T15:30:47.059265+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_5b13630789372daa", + "problem_id": "v2p_m9_b9dfed4189077979", + "dataset_id": "m9", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_conditional_contrast", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=major_discipline, measure_col=training_hours.", + "bindings": { + "group_col": "major_discipline", + "measure_col": "training_hours", + "top_k": 10, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=5" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_5b13630789372daa.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_5b13630789372daa", + "api_calls": 0, + "input_tokens": 14648, + "cached_input_tokens": 12032, + "output_tokens": 516, + "total_tokens": 15164, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14566.39, + "sql_execution_elapsed_ms_total": 9.02, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..137756fea0fb6792034f1d764fffaa1cce47bb1f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:30:47.048712+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14566.39, "started_at": "2026-05-19T15:30:32.481343+00:00", "ended_at": "2026-05-19T15:30:47.047763+00:00", "prompt_metrics": {"chars": 9308, "bytes_utf8": 9308, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 393, "bytes_utf8": 393, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14648, "cached_input_tokens": 12032, "output_tokens": 516, "reasoning_output_tokens": 413}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"major_discipline\\\", SUM(CAST(\\\"training_hours\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"major_discipline\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Grouped numeric sum using \\\"major_discipline\\\" as the group column and \\\"training_hours\\\" as the measure; casts \\\"training_hours\\\" from TEXT to REAL for SQLite aggregation.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..6bcfb7f2a057ae29872e1d73088c54e3943dd1f1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_5b13630789372daa", + "api_calls": 0, + "input_tokens": 14648, + "cached_input_tokens": 12032, + "output_tokens": 516, + "total_tokens": 15164, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14566.39, + "sql_execution_elapsed_ms_total": 9.02, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5b13630789372daa/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..8d762b44f7e13df0a5e0b5e4e0049809ba63f6c3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "0.92", "support": 5200, "support_share": 0.27142708007098865, "support_rank": 1}, {"value_label": "0.624", "support": 2702, "support_share": 0.14103768660611754, "support_rank": 2}, {"value_label": "0.91", "support": 1533, "support_share": 0.08001879110554337, "support_rank": 3}, {"value_label": "0.9259999999999999", "support": 1336, "support_share": 0.06973588057208477, "support_rank": 4}, {"value_label": "0.698", "support": 683, "support_share": 0.03565090301701639, "support_rank": 5}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..944ca29f3302dfc4df1c233adb7e158898937b8b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/generated_sql.sql @@ -0,0 +1,25 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: support_concentration +-- variant_semantic_role: count_distribution +-- template_id: tpl_cardinality_support_rank_profile +-- query_record_id: v2q_m9_5f37dad254f68ca7 +-- problem_id: v2p_m9_d28478077355b130 +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "city_development_index" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "city_development_index" +) +SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank +FROM grouped +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c82b0ef8a8e81317b9c4a6ec1d74e6b63869de95 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: count_distribution\n-- template_id: tpl_cardinality_support_rank_profile\n-- query_record_id: v2q_m9_5f37dad254f68ca7\n-- problem_id: v2p_m9_d28478077355b130\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"city_development_index\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"city_development_index\"\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: count_distribution\\n-- template_id: tpl_cardinality_support_rank_profile\\n-- query_record_id: v2q_m9_5f37dad254f68ca7\\n-- problem_id: v2p_m9_d28478077355b130\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"city_development_index\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"city_development_index\\\"\\n)\\nSELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\\nFROM grouped\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"support_rank\"], \"rows\": [{\"value_label\": \"0.92\", \"support\": 5200, \"support_share\": 0.27142708007098865, \"support_rank\": 1}, {\"value_label\": \"0.624\", \"support\": 2702, \"support_share\": 0.14103768660611754, \"support_rank\": 2}, {\"value_label\": \"0.91\", \"support\": 1533, \"support_share\": 0.08001879110554337, \"support_rank\": 3}, {\"value_label\": \"0.9259999999999999\", \"support\": 1336, \"support_share\": 0.06973588057208477, \"support_rank\": 4}, {\"value_label\": \"0.698\", \"support\": 683, \"support_share\": 0.03565090301701639, \"support_rank\": 5}, {\"value_label\": \"0.897\", \"support\": 586, \"support_share\": 0.030587744023384485, \"support_rank\": 6}, {\"value_label\": \"0.9390000000000001\", \"support\": 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\"support\": 182, \"support_share\": 0.009499947802484601, \"support_rank\": 16}, {\"value_label\": \"0.802\", \"support\": 175, \"support_share\": 0.009134565194696732, \"support_rank\": 17}, {\"value_label\": \"0.925\", \"support\": 171, \"support_share\": 0.008925775133103664, \"support_rank\": 18}, {\"value_label\": \"0.893\", \"support\": 160, \"support_share\": 0.008351602463722727, \"support_rank\": 19}, {\"value_label\": \"0.878\", \"support\": 151, \"support_share\": 0.007881824825138323, \"support_rank\": 20}, {\"value_label\": \"0.743\", \"support\": 146, \"support_share\": 0.007620837248146988, \"support_rank\": 21}, {\"value_label\": \"0.9229999999999999\", \"support\": 143, \"support_share\": 0.0074642447019521874, \"support_rank\": 22}, {\"value_label\": \"0.8959999999999999\", \"support\": 140, \"support_share\": 0.007307652155757386, \"support_rank\": 23}, {\"value_label\": \"0.8270000000000001\", \"support\": 137, \"support_share\": 0.007151059609562585, \"support_rank\": 24}, {\"value_label\": \"0.579\", \"support\": 135, \"support_share\": 0.007046664578766051, \"support_rank\": 25}, {\"value_label\": \"0.762\", \"support\": 128, \"support_share\": 0.006681281970978181, \"support_rank\": 26}, {\"value_label\": \"0.767\", \"support\": 128, \"support_share\": 0.006681281970978181, \"support_rank\": 27}, {\"value_label\": \"0.836\", \"support\": 120, \"support_share\": 0.006263701847792045, \"support_rank\": 28}, {\"value_label\": \"0.682\", \"support\": 119, \"support_share\": 0.006211504332393778, \"support_rank\": 29}, {\"value_label\": \"0.6659999999999999\", \"support\": 114, \"support_share\": 0.005950516755402443, \"support_rank\": 30}, {\"value_label\": \"0.89\", \"support\": 113, \"support_share\": 0.005898319240004176, \"support_rank\": 31}, {\"value_label\": \"0.866\", \"support\": 103, \"support_share\": 0.005376344086021506, \"support_rank\": 32}, {\"value_label\": \"0.6890000000000001\", \"support\": 102, \"support_share\": 0.005324146570623238, \"support_rank\": 33}, {\"value_label\": \"0.843\", \"support\": 94, \"support_share\": 0.004906566447437102, \"support_rank\": 34}, {\"value_label\": \"0.915\", \"support\": 94, \"support_share\": 0.004906566447437102, \"support_rank\": 35}, {\"value_label\": \"0.794\", \"support\": 93, \"support_share\": 0.0048543689320388345, \"support_rank\": 36}, {\"value_label\": \"0.527\", \"support\": 92, \"support_share\": 0.004802171416640568, \"support_rank\": 37}, {\"value_label\": \"0.895\", \"support\": 86, \"support_share\": 0.004488986324250966, \"support_rank\": 38}, {\"value_label\": \"0.7759999999999999\", \"support\": 82, \"support_share\": 0.004280196262657897, \"support_rank\": 39}, {\"value_label\": \"0.903\", \"support\": 82, \"support_share\": 0.004280196262657897, \"support_rank\": 40}, {\"value_label\": \"0.738\", \"support\": 79, \"support_share\": 0.004123603716463096, \"support_rank\": 41}, {\"value_label\": \"0.9490000000000001\", \"support\": 79, \"support_share\": 0.004123603716463096, \"support_rank\": 42}, {\"value_label\": \"0.5579999999999999\", \"support\": 75, \"support_share\": 0.0039148136548700285, \"support_rank\": 43}, {\"value_label\": \"0.74\", \"support\": 67, \"support_share\": 0.003497233531683892, \"support_rank\": 44}, {\"value_label\": \"0.555\", \"support\": 63, \"support_share\": 0.0032884434700908237, \"support_rank\": 45}, {\"value_label\": \"0.789\", \"support\": 54, \"support_share\": 0.0028186658315064203, \"support_rank\": 46}, {\"value_label\": \"0.727\", \"support\": 53, \"support_share\": 0.0027664683161081533, \"support_rank\": 47}, {\"value_label\": \"0.7659999999999999\", \"support\": 49, \"support_share\": 0.002557678254515085, \"support_rank\": 48}, {\"value_label\": \"0.848\", \"support\": 47, \"support_share\": 0.002453283223718551, \"support_rank\": 49}, {\"value_label\": \"0.691\", \"support\": 45, \"support_share\": 0.002348888192922017, \"support_rank\": 50}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 7.63}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..87d55f9f75064df246ba33cdad692986b8b7b767 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.270935+00:00", + "ended_at": "2026-05-19T16:08:56.280221+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_5f37dad254f68ca7", + "problem_id": "v2p_m9_d28478077355b130", + "dataset_id": "m9", + "template_id": "tpl_cardinality_support_rank_profile", + "template_name": "Cardinality Support Rank Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "support_concentration", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Support Rank Profile to probe support_rank_profile_consistency with semantic role count_distribution. Focus on group_col=city_development_index.", + "bindings": { + "group_col": "city_development_index" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=1", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_5f37dad254f68ca7.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_5f37dad254f68ca7/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..0d37e484250fd2fb18c67187efb8c8d506e670c6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:08:41.541005+00:00", + "ended_at": "2026-05-19T16:08:44.350768+00:00", + "elapsed_ms": 2809.74, + "returncode": 1, + "prompt_metrics": { + "chars": 9398, + "bytes_utf8": 9398, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..529cc3805b0599359df8c1e626e3f91b6b72978f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:08:45.353004+00:00", + "ended_at": "2026-05-19T16:08:48.592425+00:00", + "elapsed_ms": 3239.37, + "returncode": 1, + "prompt_metrics": { + "chars": 9398, + "bytes_utf8": 9398, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..df45bbe17d8c08901a9b19837b8b5660949f42e8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=company_size, measure_col=city_development_index.", + "planned_template_id": "tpl_m4_window_partition_avg", + "bindings": { + "group_col": "company_size", + "measure_col": "city_development_index", + "top_k": 14, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..df45bbe17d8c08901a9b19837b8b5660949f42e8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=company_size, measure_col=city_development_index.", + "planned_template_id": "tpl_m4_window_partition_avg", + "bindings": { + "group_col": "company_size", + "measure_col": "city_development_index", + "top_k": 14, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..200b19518871f9fb7a84e36e32d5d56af3129c1e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40ff-1e63-7a93-9249-c181aa301799"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..3f75ddcf623cc20b3ae8b155ce95ca18f9114882 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40ff-1e63-7a93-9249-c181aa301799"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..dd7afa1a15a951a93c169821797cd61dd4c30dcf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40ff-2d32-7832-b964-a5eb2f3bd851"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..2f88cbf7e3fad9b70e29c60b6f00051c4288fa69 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40ff-2d32-7832-b964-a5eb2f3bd851"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_614c360713973227/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..ffbd4a6bfd7dd193edb934bcf7059e75bc7876f1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"enrolled_university": "no_enrollment", "total_rows": 13817, "missing_rows": 0, "missing_rate": 0.0}, {"enrolled_university": "Full time course", "total_rows": 3757, "missing_rows": 0, "missing_rate": 0.0}, {"enrolled_university": "Part time course", "total_rows": 1198, "missing_rows": 0, "missing_rate": 0.0}, {"enrolled_university": "", "total_rows": 386, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..364c61576168b5482378203a605ff2a044bb1ca0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: co_missingness_pattern_consistency +-- intended_facet_id: missing_rate_by_subgroup +-- variant_semantic_role: missing_rate_by_subgroup +-- template_id: tpl_missing_rate_by_subgroup +-- query_record_id: v2q_m9_621bdf69106a1056 +-- problem_id: v2p_m9_9c35cd9d5b2564f9 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "enrolled_university", + COUNT(*) AS total_rows, + SUM(CASE WHEN "major_discipline" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "major_discipline" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9" +GROUP BY "enrolled_university" +ORDER BY missing_rate DESC, total_rows DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3cb8b88079bd9b8c0d667240a5d76426c2e05bbd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: co_missingness_pattern_consistency\n-- intended_facet_id: missing_rate_by_subgroup\n-- variant_semantic_role: missing_rate_by_subgroup\n-- template_id: tpl_missing_rate_by_subgroup\n-- query_record_id: v2q_m9_621bdf69106a1056\n-- problem_id: v2p_m9_9c35cd9d5b2564f9\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"enrolled_university\",\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"major_discipline\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"major_discipline\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\"\nGROUP BY \"enrolled_university\"\nORDER BY missing_rate DESC, total_rows DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: co_missingness_pattern_consistency\\n-- intended_facet_id: missing_rate_by_subgroup\\n-- variant_semantic_role: missing_rate_by_subgroup\\n-- template_id: tpl_missing_rate_by_subgroup\\n-- query_record_id: v2q_m9_621bdf69106a1056\\n-- problem_id: v2p_m9_9c35cd9d5b2564f9\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"enrolled_university\\\",\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"major_discipline\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"major_discipline\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"enrolled_university\\\"\\nORDER BY missing_rate DESC, total_rows DESC;\", \"columns\": [\"enrolled_university\", \"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"enrolled_university\": \"no_enrollment\", \"total_rows\": 13817, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"enrolled_university\": \"Full time course\", \"total_rows\": 3757, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"enrolled_university\": \"Part time course\", \"total_rows\": 1198, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"enrolled_university\": \"\", \"total_rows\": 386, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 7.45}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..75527b27c4fa71a3522e0ccbe0307e37ea1fae96 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/run_manifest.json @@ -0,0 +1,59 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:55.986641+00:00", + "ended_at": "2026-05-19T16:08:55.994767+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_621bdf69106a1056", + "problem_id": "v2p_m9_9c35cd9d5b2564f9", + "dataset_id": "m9", + "template_id": "tpl_missing_rate_by_subgroup", + "template_name": "Missing Rate by Subgroup", + "family_id": "missingness_structure", + "canonical_subitem_id": "co_missingness_pattern_consistency", + "intended_facet_id": "missing_rate_by_subgroup", + "variant_semantic_role": "missing_rate_by_subgroup", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Missing Rate by Subgroup to probe co_missingness_pattern_consistency with semantic role missing_rate_by_subgroup. Focus on group_col=enrolled_university, missing_col=major_discipline.", + "bindings": { + "missing_col": "major_discipline", + "group_col": "enrolled_university" + }, + "binding_roles": [ + "missing_col", + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY missing_rate DESC, total_rows DESC;", + "notes": [ + "default_facets=missing_rate_by_subgroup,missing_target_interaction", + "template_selection_mode=deterministic", + "problem_index_within_template=6", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_621bdf69106a1056.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_621bdf69106a1056/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..1e42a3a9767c04c91a98a1b3fe32637a23b86a06 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:06:58.276760+00:00", + "ended_at": "2026-05-19T16:07:01.631261+00:00", + "elapsed_ms": 3354.48, + "returncode": 1, + "prompt_metrics": { + "chars": 9391, + "bytes_utf8": 9391, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..e3ce10f2785ae0cde562142a3ce4cf457c9d4927 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:07:02.632849+00:00", + "ended_at": "2026-05-19T16:07:05.979293+00:00", + "elapsed_ms": 3346.41, + "returncode": 1, + "prompt_metrics": { + "chars": 9391, + "bytes_utf8": 9391, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..69c12800782671afd2e083e689676999cf8a4091 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Window Partition Average to probe direction_consistency with semantic role filtered_stable_view. Focus on group_col=gender, measure_col=city_development_index.", + "planned_template_id": "tpl_m4_window_partition_avg", + "bindings": { + "group_col": "gender", + "measure_col": "city_development_index", + "top_k": 18, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..69c12800782671afd2e083e689676999cf8a4091 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Window Partition Average to probe direction_consistency with semantic role filtered_stable_view. Focus on group_col=gender, measure_col=city_development_index.", + "planned_template_id": "tpl_m4_window_partition_avg", + "bindings": { + "group_col": "gender", + "measure_col": "city_development_index", + "top_k": 18, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..db77c3772dd74344022cd1cb5aa2baf567cac3d3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fd-8ad0-7531-9b95-ae6d008a4ce4"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..987fb3de450334bc3de133146f7acc10c2fabd74 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fd-8ad0-7531-9b95-ae6d008a4ce4"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..9ee27e59ada8f9b2fef98086109089d8b7ccc1ad --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fd-9c00-72d0-822d-06bb5788a8e6"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..3f5e2a5e404aa1f88be523120bb2d2e3421bbc93 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fd-9c00-72d0-822d-06bb5788a8e6"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_63df68013b6c9c7e/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3b5d0436d5a228948430c28c4aea771af52a6c25 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "Male", "support": 13221, "support_share": 0.6901033510804886, "support_rank": 1}, {"value_label": "", "support": 4508, "support_share": 0.23530639941538783, "support_rank": 2}, {"value_label": "Female", "support": 1238, "support_share": 0.0646205240630546, "support_rank": 3}, {"value_label": "Other", "support": 191, "support_share": 0.009969725441069005, "support_rank": 4}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..3cc35072f8ef5e65e45f6937b11dd9df830e854a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/generated_sql.sql @@ -0,0 +1,25 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: value_imbalance_profile +-- variant_semantic_role: count_distribution +-- template_id: tpl_cardinality_support_rank_profile +-- query_record_id: v2q_m9_67062e771bd03332 +-- problem_id: v2p_m9_b1b110ea230102d9 +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "gender" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "gender" +) +SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank +FROM grouped +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..01e5b86d157acd4b8d6241a38dbb681caf7e11c1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: value_imbalance_profile\n-- variant_semantic_role: count_distribution\n-- template_id: tpl_cardinality_support_rank_profile\n-- query_record_id: v2q_m9_67062e771bd03332\n-- problem_id: v2p_m9_b1b110ea230102d9\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"gender\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"gender\"\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: value_imbalance_profile\\n-- variant_semantic_role: count_distribution\\n-- template_id: tpl_cardinality_support_rank_profile\\n-- query_record_id: v2q_m9_67062e771bd03332\\n-- problem_id: v2p_m9_b1b110ea230102d9\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"gender\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"gender\\\"\\n)\\nSELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\\nFROM grouped\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"support_rank\"], \"rows\": [{\"value_label\": \"Male\", \"support\": 13221, \"support_share\": 0.6901033510804886, \"support_rank\": 1}, {\"value_label\": \"\", \"support\": 4508, \"support_share\": 0.23530639941538783, \"support_rank\": 2}, {\"value_label\": \"Female\", \"support\": 1238, \"support_share\": 0.0646205240630546, \"support_rank\": 3}, {\"value_label\": \"Other\", \"support\": 191, \"support_share\": 0.009969725441069005, \"support_rank\": 4}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.84}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..095c219625b90eb08dff1e807b52b3be15cef2af --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.280761+00:00", + "ended_at": "2026-05-19T16:08:56.287526+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_67062e771bd03332", + "problem_id": "v2p_m9_b1b110ea230102d9", + "dataset_id": "m9", + "template_id": "tpl_cardinality_support_rank_profile", + "template_name": "Cardinality Support Rank Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "value_imbalance_profile", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Support Rank Profile to probe support_rank_profile_consistency with semantic role count_distribution. Focus on group_col=gender.", + "bindings": { + "group_col": "gender" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=2", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_67062e771bd03332.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_67062e771bd03332/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0daab5d207ee1427273b266ebab2d19025d2a523 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/conversation.jsonl @@ -0,0 +1,4 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9614, "bytes_utf8": 9614, "lines": 267, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "status": "failed", "error": "AI CLI command failed with exit code 1: "} +{"attempt": 2, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_2.txt", "metrics": {"chars": 9614, "bytes_utf8": 9614, "lines": 267, "estimated_tokens": null}} +{"attempt": 2, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_2.txt", "raw_content_path": "cli/sql_response_attempt_2.raw.txt", "stderr_path": "cli/sql_stderr_attempt_2.txt", "metrics": {"chars": 524, "bytes_utf8": 524, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14721, "cached_input_tokens": 12032, "output_tokens": 213, "reasoning_output_tokens": 79}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..f50912ad3d93e99cf88a4d8f530b74a3af51dc13 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 2, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_6cf5e89b29502c24", + "api_calls": 0, + "input_tokens": 14721, + "cached_input_tokens": 12032, + "output_tokens": 213, + "total_tokens": 14934, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12320.0, + "sql_execution_elapsed_ms_total": 17.9, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..55b217379f8a0c000bfa75fb17698c1294dc4594 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:00:09.151756+00:00", + "ended_at": "2026-05-19T16:00:13.538414+00:00", + "elapsed_ms": 4386.63, + "returncode": 1, + "prompt_metrics": { + "chars": 9614, + "bytes_utf8": 9614, + "lines": 267, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..e99731076785a7f76324a187d1b39869cf64e246 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_attempt_2.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:00:14.540291+00:00", + "ended_at": "2026-05-19T16:00:22.473699+00:00", + "elapsed_ms": 7933.37, + "prompt_metrics": { + "chars": 9614, + "bytes_utf8": 9614, + "lines": 267, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 878, + "bytes_utf8": 878, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 524, + "bytes_utf8": 524, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14721, + "cached_input_tokens": 12032, + "output_tokens": 213, + "reasoning_output_tokens": 79 + } + }, + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..7e1956501cdb37a07997eb3a2b5170322c87b32a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,267 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=relevent_experience, condition_col=enrolled_university.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "relevent_experience", + "condition_col": "enrolled_university", + "condition_value": "Full time course", + "positive_value": "no_enrollment", + "negative_value": "Full time course", + "top_k": 18, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..7e1956501cdb37a07997eb3a2b5170322c87b32a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,267 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=relevent_experience, condition_col=enrolled_university.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "relevent_experience", + "condition_col": "enrolled_university", + "condition_value": "Full time course", + "positive_value": "no_enrollment", + "negative_value": "Full time course", + "top_k": 18, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..5f07ddddca2eeb691d62177ccc74ec36bc527015 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f7-4cc6-7df0-bcf8-ca4534d4c862"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..a98c1440427ea650a825be644866c9ea131f46dc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f7-4cc6-7df0-bcf8-ca4534d4c862"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..ddae357fa40b3d5f21b451a24f9dd325fd58ba40 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f7-61e9-7403-a5c3-78f22a644762"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"relevent_experience\\\",\\n AVG(CASE WHEN \\\"enrolled_university\\\" = 'Full time course' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"relevent_experience\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Uses the planned Grouped Condition Rate template with group_col=\\\"relevent_experience\\\" and condition_col=\\\"enrolled_university\\\", measuring the share of rows where enrolled_university is 'Full time course' within each relevent_experience group.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14721,"cached_input_tokens":12032,"output_tokens":213,"reasoning_output_tokens":79}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..463b4aa33ef1425fbc3b406aa9daf0af1f4d5d47 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_response_attempt_2.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT \"relevent_experience\",\n AVG(CASE WHEN \"enrolled_university\" = 'Full time course' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"m9\"\nGROUP BY \"relevent_experience\"\nORDER BY condition_rate DESC;","notes":"Uses the planned Grouped Condition Rate template with group_col=\"relevent_experience\" and condition_col=\"enrolled_university\", measuring the share of rows where enrolled_university is 'Full time course' within each relevent_experience group."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6cf5e89b29502c24/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..6e9bdc6a891d229383d6f777908c7770971be0c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:05:19.861400+00:00", + "ended_at": "2026-05-19T16:05:23.605088+00:00", + "elapsed_ms": 3743.66, + "returncode": 1, + "prompt_metrics": { + "chars": 9284, + "bytes_utf8": 9284, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..b562edfae44309dca9927d9816b8896982584f54 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=education_level.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "education_level", + "top_k": 14, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..b562edfae44309dca9927d9816b8896982584f54 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=education_level.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "education_level", + "top_k": 14, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..e4585425e87e9cf22d83172f71a6d914e45194ae --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-0a92-7ad0-b62c-9d734a68d272"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e28887ef86c0673f04e3ef9e8efeeb86a4328caf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-0a92-7ad0-b62c-9d734a68d272"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..e81695e907964d96cd66747c179e7b9d24371015 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-1d0d-7ca2-8dc8-fcb36f881db6"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6d398c56a4001f93/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..cf23ea6d7f74c4fc9bfd2ab2afc26f29260aeabc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=enrollee_id. +Result preview: [{"empirical_cdf_at_threshold": 0.7499739012423009}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..13245c8c1d7b12340219c2cf6f8e6cf64a2d7c56 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/generated_sql.sql @@ -0,0 +1,15 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_threshold_rarity_cdf +-- query_record_id: v2q_m9_6e7e6c4413c14105 +-- problem_id: v2p_m9_b68635792aa075da +-- realization_mode: agent +-- source_kind: agent +SELECT AVG(CASE WHEN CAST("enrollee_id" AS REAL) <= 25169.75 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold +FROM "m9"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9b26a68d26f65b9b704192031b10b9f9ccfc94b5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(\"enrollee_id\" AS REAL) <= 25169.75 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM \"m9\";", "result": "{\"query\": \"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"enrollee_id\\\" AS REAL) <= 25169.75 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\\nFROM \\\"m9\\\";\", \"columns\": [\"empirical_cdf_at_threshold\"], \"rows\": [{\"empirical_cdf_at_threshold\": 0.7499739012423009}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 4.45}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..b603309b89be9416cec8b0af400bc67fdd89aea6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:02:31.903091+00:00", + "ended_at": "2026-05-19T16:02:39.810555+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_6e7e6c4413c14105", + "problem_id": "v2p_m9_b68635792aa075da", + "dataset_id": "m9", + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=enrollee_id.", + "bindings": { + "measure_col": "enrollee_id", + "top_k": 13, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/1", + "binding_index=108" + ], + "template_selection_mode": "rule", + "selected_template_rank": 10, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_6e7e6c4413c14105.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_6e7e6c4413c14105", + "api_calls": 0, + "input_tokens": 14639, + "cached_input_tokens": 13696, + "output_tokens": 254, + "total_tokens": 14893, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7897.55, + "sql_execution_elapsed_ms_total": 4.45, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..06ce56488055adc25bbeb9b1adcca775f677fc96 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:02:39.804406+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 7897.55, "started_at": "2026-05-19T16:02:31.905747+00:00", "ended_at": "2026-05-19T16:02:39.803321+00:00", "prompt_metrics": {"chars": 9228, "bytes_utf8": 9228, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 335, "bytes_utf8": 335, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14639, "cached_input_tokens": 13696, "output_tokens": 254, "reasoning_output_tokens": 155}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"enrollee_id\\\" AS REAL) <= 25169.75 THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\\nFROM \\\"m9\\\";\",\"notes\":\"Used the required Threshold Rarity CDF template with measure_col bound to \\\"enrollee_id\\\" and cast it to REAL because the schema stores it as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..550aa75c12fee3f8aabd99c385ad9561c2c08e15 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_6e7e6c4413c14105", + "api_calls": 0, + "input_tokens": 14639, + "cached_input_tokens": 13696, + "output_tokens": 254, + "total_tokens": 14893, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7897.55, + "sql_execution_elapsed_ms_total": 4.45, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e7e6c4413c14105/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..f23c7744aa45374ed91cc6345a7f5504569778aa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=experience, group_col_2=target. +Result preview: [{"experience": ">20", "target": "1.0", "row_count": 503}, {"experience": "3", "target": "1.0", "row_count": 478}, {"experience": "4", "target": "1.0", "row_count": 457}, {"experience": "5", "target": "1.0", "row_count": 412}, {"experience": "2", "target": "1.0", "row_count": 374}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..33baf2ddb854e1ba165d7d739ce85eabbba21052 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: count_distribution +-- template_id: tpl_c2_filtered_group_count_2d +-- query_record_id: v2q_m9_6e80fcf66868f9be +-- problem_id: v2p_m9_f330c76855cfd712 +-- realization_mode: agent +-- source_kind: agent +SELECT "experience", "target", COUNT(*) AS row_count +FROM "m9" +WHERE "target" = '1.0' +GROUP BY "experience", "target" +ORDER BY row_count DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f4e88446beec41a5cf87d598baaea5de8ed20a15 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"experience\", \"target\", COUNT(*) AS row_count\nFROM \"m9\"\nWHERE \"target\" = '1.0'\nGROUP BY \"experience\", \"target\"\nORDER BY row_count DESC;", "result": "{\"query\": \"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"experience\\\", \\\"target\\\", COUNT(*) AS row_count\\nFROM \\\"m9\\\"\\nWHERE \\\"target\\\" = '1.0'\\nGROUP BY \\\"experience\\\", \\\"target\\\"\\nORDER BY row_count DESC;\", \"columns\": [\"experience\", \"target\", \"row_count\"], \"rows\": [{\"experience\": \">20\", \"target\": \"1.0\", \"row_count\": 503}, {\"experience\": \"3\", \"target\": \"1.0\", \"row_count\": 478}, {\"experience\": \"4\", \"target\": \"1.0\", \"row_count\": 457}, {\"experience\": \"5\", \"target\": \"1.0\", \"row_count\": 412}, {\"experience\": \"2\", \"target\": \"1.0\", \"row_count\": 374}, {\"experience\": \"6\", \"target\": \"1.0\", \"row_count\": 343}, {\"experience\": \"7\", \"target\": \"1.0\", \"row_count\": 303}, {\"experience\": \"<1\", \"target\": \"1.0\", \"row_count\": 237}, {\"experience\": \"1\", \"target\": \"1.0\", \"row_count\": 233}, {\"experience\": \"9\", \"target\": \"1.0\", \"row_count\": 213}, {\"experience\": \"10\", \"target\": \"1.0\", \"row_count\": 207}, {\"experience\": \"8\", \"target\": \"1.0\", \"row_count\": 195}, {\"experience\": \"11\", \"target\": \"1.0\", \"row_count\": 151}, {\"experience\": \"15\", \"target\": \"1.0\", \"row_count\": 114}, {\"experience\": \"14\", \"target\": \"1.0\", \"row_count\": 107}, {\"experience\": \"12\", \"target\": \"1.0\", \"row_count\": 92}, {\"experience\": \"13\", \"target\": \"1.0\", \"row_count\": 77}, {\"experience\": \"16\", \"target\": \"1.0\", \"row_count\": 72}, {\"experience\": \"17\", \"target\": \"1.0\", \"row_count\": 57}, {\"experience\": \"19\", \"target\": \"1.0\", \"row_count\": 53}, {\"experience\": \"18\", \"target\": \"1.0\", \"row_count\": 43}, {\"experience\": \"20\", \"target\": \"1.0\", \"row_count\": 33}, {\"experience\": \"\", \"target\": \"1.0\", \"row_count\": 23}], \"row_count_returned\": 23, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.42}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..8ec23d590185d64ea06959f4eda321280bf6dab2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/run_manifest.json @@ -0,0 +1,93 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:43:38.725133+00:00", + "ended_at": "2026-05-19T15:43:47.654577+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_6e80fcf66868f9be", + "problem_id": "v2p_m9_f330c76855cfd712", + "dataset_id": "m9", + "template_id": "tpl_c2_filtered_group_count_2d", + "template_name": "Filtered Two-Dimensional Group Count", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=experience, group_col_2=target.", + "bindings": { + "group_col": "experience", + "group_col_2": "target", + "predicate_col": "target", + "predicate_op": "=", + "predicate_value": "1.0", + "top_k": 10, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "group_col_2", + "predicate_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/1", + "binding_index=55" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_6e80fcf66868f9be.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_6e80fcf66868f9be", + "api_calls": 0, + "input_tokens": 14735, + "cached_input_tokens": 12032, + "output_tokens": 370, + "total_tokens": 15105, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8917.93, + "sql_execution_elapsed_ms_total": 5.42, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..534bc612966b67a0f61c9ff6e1bdd956d07ce935 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:43:47.647662+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8917.93, "started_at": "2026-05-19T15:43:38.728887+00:00", "ended_at": "2026-05-19T15:43:47.646851+00:00", "prompt_metrics": {"chars": 9589, "bytes_utf8": 9589, "lines": 268, "estimated_tokens": null}, "response_metrics": {"chars": 366, "bytes_utf8": 366, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14735, "cached_input_tokens": 12032, "output_tokens": 370, "reasoning_output_tokens": 268}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"experience\\\", \\\"target\\\", COUNT(*) AS row_count\\nFROM \\\"m9\\\"\\nWHERE \\\"target\\\" = '1.0'\\nGROUP BY \\\"experience\\\", \\\"target\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Uses the planned filtered two-dimensional group count template with \\\"experience\\\" and \\\"target\\\", filtering rows where \\\"target\\\" = '1.0'.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..dd8fc8d33c418fe207aaa89214ced5fe922e1aad --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_6e80fcf66868f9be", + "api_calls": 0, + "input_tokens": 14735, + "cached_input_tokens": 12032, + "output_tokens": 370, + "total_tokens": 15105, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8917.93, + "sql_execution_elapsed_ms_total": 5.42, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_6e80fcf66868f9be/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b0163d7cccd469d326d59fe492427c15626c1d23 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9873, "bytes_utf8": 9873, "lines": 264, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 849, "bytes_utf8": 849, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14790, "cached_input_tokens": 13696, "output_tokens": 746, "reasoning_output_tokens": 516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..aabb7aa715de8e607fd9c6fcac7ee93046a0cb0e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_723cc72387b35247", + "api_calls": 0, + "input_tokens": 14790, + "cached_input_tokens": 13696, + "output_tokens": 746, + "total_tokens": 15536, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14710.05, + "sql_execution_elapsed_ms_total": 15.49, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..839713cd0cfbfae94ce28fe0c7ac688a1f082220 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:45:49.429857+00:00", + "ended_at": "2026-05-19T15:46:04.139947+00:00", + "elapsed_ms": 14710.05, + "prompt_metrics": { + "chars": 9873, + "bytes_utf8": 9873, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1277, + "bytes_utf8": 1277, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 849, + "bytes_utf8": 849, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14790, + "cached_input_tokens": 13696, + "output_tokens": 746, + "reasoning_output_tokens": 516 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..dd52b6a3cf45134163ac99925609292f24ec518d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "primary_family": "tail_rarity_structure", + "portability": "partial", + "sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=city_development_index, measure_col=enrollee_id.", + "planned_template_id": "tpl_tpch_relative_total_threshold", + "bindings": { + "group_col": "city_development_index", + "measure_col": "enrollee_id", + "top_k": 12, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..361be65530e1c2ebda69044adbfb8e9be86e3f3e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40ea-2ea0-7f00-b01f-ef56671907fb"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"city_development_index\\\",\\n COUNT(\\\"enrollee_id\\\") AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n GROUP BY \\\"city_development_index\\\"\\n),\\n\\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT\\n g.\\\"city_development_index\\\",\\n g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Applied the requested Relative-to-Total Extreme Threshold template with group_col=\\\"city_development_index\\\". Because the semantic role is count_distribution and \\\"enrollee_id\\\" is an identifier-like text column, the measure was implemented as COUNT(\\\"enrollee_id\\\") rather than SUM(\\\"enrollee_id\\\").\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14790,"cached_input_tokens":13696,"output_tokens":746,"reasoning_output_tokens":516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e0ff332b1aef8e0a62bfe5ccd5ea139d957fe2a0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n SELECT\n \"city_development_index\",\n COUNT(\"enrollee_id\") AS \"group_value\"\n FROM \"m9\"\n GROUP BY \"city_development_index\"\n),\n\"total\" AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM \"grouped\"\n)\nSELECT\n g.\"city_development_index\",\n g.\"group_value\"\nFROM \"grouped\" AS g\nCROSS JOIN \"total\" AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;","notes":"Applied the requested Relative-to-Total Extreme Threshold template with group_col=\"city_development_index\". Because the semantic role is count_distribution and \"enrollee_id\" is an identifier-like text column, the measure was implemented as COUNT(\"enrollee_id\") rather than SUM(\"enrollee_id\")."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_723cc72387b35247/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..645213034d46486eb039f9f2ded27f84b7afdd42 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=last_new_job, measure_col=enrollee_id. +Result preview: [{"last_new_job": "", "training_hours": "46", "total_measure": 179268.0, "share_within_group": 2.8463732034321354}, {"last_new_job": "", "training_hours": "28", "total_measure": 148214.0, "share_within_group": 2.353305430826977}, {"last_new_job": "", "training_hours": "42", "total_measure": 142341.0, "share_within_group": 2.2600553816059397}, {"last_new_job": "", "training_hours": "43", "total_measure": 137044.0, "share_within_group": 2.1759509186868464}, {"last_new_job": "", "training_hours": "18", "total_measure": 134439.0, "share_within_group": 2.1345893695261444}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..9636d0324236c2aefd450556549ee529e2df5235 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_m9_7294117e92cfa6f4 +-- problem_id: v2p_m9_353502513aed335c +-- realization_mode: agent +-- source_kind: agent +SELECT "last_new_job", "training_hours", + SUM(CAST("enrollee_id" AS REAL)) AS total_measure, + SUM(CAST("enrollee_id" AS REAL)) * 100.0 / SUM(SUM(CAST("enrollee_id" AS REAL))) OVER (PARTITION BY "last_new_job") AS share_within_group +FROM "m9" +GROUP BY "last_new_job", "training_hours" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..19df4276d7172dd0b23c5ed2f440f5e7a97a4c87 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT \"last_new_job\", \"training_hours\",\n SUM(CAST(\"enrollee_id\" AS REAL)) AS total_measure,\n SUM(CAST(\"enrollee_id\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"enrollee_id\" AS REAL))) OVER (PARTITION BY \"last_new_job\") AS share_within_group\nFROM \"m9\"\nGROUP BY \"last_new_job\", \"training_hours\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"last_new_job\\\", \\\"training_hours\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"enrollee_id\\\" AS REAL))) OVER (PARTITION BY \\\"last_new_job\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nGROUP BY \\\"last_new_job\\\", \\\"training_hours\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"last_new_job\", \"training_hours\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"last_new_job\": \"\", \"training_hours\": \"46\", \"total_measure\": 179268.0, \"share_within_group\": 2.8463732034321354}, {\"last_new_job\": \"\", \"training_hours\": \"28\", \"total_measure\": 148214.0, \"share_within_group\": 2.353305430826977}, {\"last_new_job\": \"\", \"training_hours\": \"42\", \"total_measure\": 142341.0, \"share_within_group\": 2.2600553816059397}, {\"last_new_job\": \"\", \"training_hours\": \"43\", \"total_measure\": 137044.0, \"share_within_group\": 2.1759509186868464}, {\"last_new_job\": \"\", \"training_hours\": \"18\", \"total_measure\": 134439.0, \"share_within_group\": 2.1345893695261444}, {\"last_new_job\": \"3\", \"training_hours\": \"28\", \"total_measure\": 353092.0, \"share_within_group\": 2.0763516070331756}, {\"last_new_job\": \"4\", \"training_hours\": \"20\", \"total_measure\": 356647.0, \"share_within_group\": 2.0545253079149575}, {\"last_new_job\": \"3\", \"training_hours\": \"34\", \"total_measure\": 349343.0, \"share_within_group\": 2.054305675166219}, {\"last_new_job\": \"\", \"training_hours\": \"12\", \"total_measure\": 128582.0, \"share_within_group\": 2.04159336436905}, {\"last_new_job\": \"4\", \"training_hours\": \"28\", \"total_measure\": 351719.0, \"share_within_group\": 2.0261367312063214}, {\"last_new_job\": \"4\", \"training_hours\": \"4\", \"total_measure\": 340958.0, \"share_within_group\": 1.9641461723667046}, {\"last_new_job\": \"3\", \"training_hours\": \"40\", \"total_measure\": 332913.0, \"share_within_group\": 1.957689334655658}, {\"last_new_job\": \">4\", \"training_hours\": \"24\", \"total_measure\": 1049957.0, \"share_within_group\": 1.954924629821258}, {\"last_new_job\": \"\", \"training_hours\": \"2\", \"total_measure\": 121668.0, \"share_within_group\": 1.931814573237728}, {\"last_new_job\": \"\", \"training_hours\": \"17\", \"total_measure\": 121237.0, \"share_within_group\": 1.9249712612652665}, {\"last_new_job\": \"\", \"training_hours\": \"8\", \"total_measure\": 118474.0, \"share_within_group\": 1.8811010269731285}, {\"last_new_job\": \"4\", \"training_hours\": \"15\", \"total_measure\": 322136.0, \"share_within_group\": 1.855718860919881}, {\"last_new_job\": \"\", \"training_hours\": \"7\", \"total_measure\": 115732.0, \"share_within_group\": 1.8375642255149156}, {\"last_new_job\": \"never\", \"training_hours\": \"17\", \"total_measure\": 743650.0, \"share_within_group\": 1.8062977451992412}, {\"last_new_job\": \"3\", \"training_hours\": \"18\", \"total_measure\": 306290.0, \"share_within_group\": 1.801133227935471}, {\"last_new_job\": \"3\", \"training_hours\": \"6\", \"total_measure\": 304269.0, \"share_within_group\": 1.7892487711995098}, {\"last_new_job\": \"never\", \"training_hours\": \"28\", \"total_measure\": 735126.0, \"share_within_group\": 1.7855932713471894}, {\"last_new_job\": \"\", \"training_hours\": \"21\", \"total_measure\": 112066.0, \"share_within_group\": 1.7793563793640006}, {\"last_new_job\": \"\", \"training_hours\": \"23\", \"total_measure\": 110892.0, \"share_within_group\": 1.7607158961721912}, {\"last_new_job\": \"3\", \"training_hours\": \"10\", \"total_measure\": 296639.0, \"share_within_group\": 1.7443806836708682}, {\"last_new_job\": \"\", \"training_hours\": \"24\", \"total_measure\": 108707.0, \"share_within_group\": 1.72602300368999}, {\"last_new_job\": \"\", \"training_hours\": \"9\", \"total_measure\": 108338.0, \"share_within_group\": 1.720164112465307}, {\"last_new_job\": \">4\", \"training_hours\": \"18\", \"total_measure\": 922245.0, \"share_within_group\": 1.7171364781886365}, {\"last_new_job\": \"2\", \"training_hours\": \"28\", \"total_measure\": 825683.0, \"share_within_group\": 1.7168991119787067}, {\"last_new_job\": \"\", \"training_hours\": \"20\", \"total_measure\": 107753.0, \"share_within_group\": 1.7108756263773952}, {\"last_new_job\": \"never\", \"training_hours\": \"12\", \"total_measure\": 704206.0, \"share_within_group\": 1.7104897599082591}, {\"last_new_job\": \"1\", \"training_hours\": \"28\", \"total_measure\": 2370606.0, \"share_within_group\": 1.697341700124629}, {\"last_new_job\": \"never\", \"training_hours\": \"13\", \"total_measure\": 693355.0, \"share_within_group\": 1.6841330910006318}, {\"last_new_job\": \"\", \"training_hours\": \"48\", \"total_measure\": 106060.0, \"share_within_group\": 1.683994588861438}, {\"last_new_job\": \"2\", \"training_hours\": \"17\", \"total_measure\": 806975.0, \"share_within_group\": 1.6779982885550713}, {\"last_new_job\": \"3\", \"training_hours\": \"23\", \"total_measure\": 283144.0, \"share_within_group\": 1.6650235616264357}, {\"last_new_job\": \"4\", \"training_hours\": \"22\", \"total_measure\": 288841.0, \"share_within_group\": 1.6639173873983637}, {\"last_new_job\": \"never\", \"training_hours\": \"34\", \"total_measure\": 678868.0, \"share_within_group\": 1.6489447155085302}, {\"last_new_job\": \"2\", \"training_hours\": \"12\", \"total_measure\": 788847.0, \"share_within_group\": 1.6403034987847236}, {\"last_new_job\": \"1\", \"training_hours\": \"20\", \"total_measure\": 2268444.0, \"share_within_group\": 1.6241942337096564}, {\"last_new_job\": \"4\", \"training_hours\": \"21\", \"total_measure\": 281518.0, \"share_within_group\": 1.6217320084946825}, {\"last_new_job\": \"\", \"training_hours\": \"10\", \"total_measure\": 101987.0, \"share_within_group\": 1.619324496833976}, {\"last_new_job\": \"never\", \"training_hours\": \"9\", \"total_measure\": 664809.0, \"share_within_group\": 1.6147959358410036}, {\"last_new_job\": \"2\", \"training_hours\": \"21\", \"total_measure\": 774787.0, \"share_within_group\": 1.6110675795343326}, {\"last_new_job\": \"3\", \"training_hours\": \"8\", \"total_measure\": 272495.0, \"share_within_group\": 1.6024022950350199}, {\"last_new_job\": \"2\", \"training_hours\": \"36\", \"total_measure\": 768246.0, \"share_within_group\": 1.5974664310409608}, {\"last_new_job\": \"1\", \"training_hours\": \"50\", \"total_measure\": 2227813.0, \"share_within_group\": 1.5951026467408544}, {\"last_new_job\": \"4\", \"training_hours\": \"18\", \"total_measure\": 273978.0, \"share_within_group\": 1.5782965644234335}, {\"last_new_job\": \"1\", \"training_hours\": \"21\", \"total_measure\": 2197771.0, \"share_within_group\": 1.573592729295634}, {\"last_new_job\": \"2\", \"training_hours\": \"8\", \"total_measure\": 745182.0, \"share_within_group\": 1.5495078790074601}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 45.05}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e4578793fd51453e0fb3d944b583aec3be3b42b2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:39:40.490862+00:00", + "ended_at": "2026-05-19T15:39:55.677292+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_7294117e92cfa6f4", + "problem_id": "v2p_m9_353502513aed335c", + "dataset_id": "m9", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=last_new_job, measure_col=enrollee_id.", + "bindings": { + "group_col": "last_new_job", + "measure_col": "enrollee_id", + "item_col": "training_hours", + "top_k": 18, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=10", + "sql_variant_index=2/2", + "binding_index=33" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 10, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_7294117e92cfa6f4.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_7294117e92cfa6f4", + "api_calls": 0, + "input_tokens": 14771, + "cached_input_tokens": 13696, + "output_tokens": 696, + "total_tokens": 15467, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15134.84, + "sql_execution_elapsed_ms_total": 45.05, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..887eecaa809bae8871de0a8e8fab6c0baf6130fa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:39:55.629781+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15134.84, "started_at": "2026-05-19T15:39:40.493403+00:00", "ended_at": "2026-05-19T15:39:55.628278+00:00", "prompt_metrics": {"chars": 9717, "bytes_utf8": 9717, "lines": 266, "estimated_tokens": null}, "response_metrics": {"chars": 624, "bytes_utf8": 624, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14771, "cached_input_tokens": 13696, "output_tokens": 696, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"last_new_job\\\", \\\"training_hours\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"enrollee_id\\\" AS REAL))) OVER (PARTITION BY \\\"last_new_job\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nGROUP BY \\\"last_new_job\\\", \\\"training_hours\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Uses the required template with group_col=\\\"last_new_job\\\", item_col=\\\"training_hours\\\", and measure_col=\\\"enrollee_id\\\". Since \\\"enrollee_id\\\" is stored as TEXT in SQLite, it is cast to REAL before SUM().\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..39ae5351d5e699d29445f6ce275bdb3c0c3934b6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_7294117e92cfa6f4", + "api_calls": 0, + "input_tokens": 14771, + "cached_input_tokens": 13696, + "output_tokens": 696, + "total_tokens": 15467, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15134.84, + "sql_execution_elapsed_ms_total": 45.05, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7294117e92cfa6f4/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3d04d49045dcece08909f8feca54443bfb1a8f0b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=major_discipline, measure_col=training_hours. +Result preview: [{"major_discipline": "Other", "percentile_measure": 151.0}, {"major_discipline": "Humanities", "percentile_measure": 150.0}, {"major_discipline": "Business Degree", "percentile_measure": 148.80000000000007}, {"major_discipline": "STEM", "percentile_measure": 146.0}, {"major_discipline": "No Major", "percentile_measure": 130.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..d84f489bdb5b522d32c56a2d1557cd6b514cd34e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/generated_sql.sql @@ -0,0 +1,65 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_m9_72b6191fdbae7aa9 +-- problem_id: v2p_m9_d1c73c1ca7ccb610 +-- realization_mode: agent +-- source_kind: agent +WITH "ordered" AS ( + SELECT + "major_discipline", + CAST("training_hours" AS REAL) AS "training_hours_num", + ROW_NUMBER() OVER ( + PARTITION BY "major_discipline" + ORDER BY CAST("training_hours" AS REAL) + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "major_discipline" + ) AS "cnt" + FROM "m9" + WHERE "major_discipline" <> '' + AND "training_hours" <> '' +), +"bounds" AS ( + SELECT DISTINCT + "major_discipline", + (1.0 + 0.9 * ("cnt" - 1)) AS "pos", + CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) AS "lower_rn", + CASE + WHEN (1.0 + 0.9 * ("cnt" - 1)) = CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) + THEN CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) + ELSE CAST((1.0 + 0.9 * ("cnt" - 1)) AS INTEGER) + 1 + END AS "upper_rn" + FROM "ordered" +), +"picked" AS ( + SELECT + b."major_discipline", + b."pos", + b."lower_rn", + b."upper_rn", + MAX(CASE WHEN o."rn" = b."lower_rn" THEN o."training_hours_num" END) AS "lower_val", + MAX(CASE WHEN o."rn" = b."upper_rn" THEN o."training_hours_num" END) AS "upper_val" + FROM "bounds" AS b + JOIN "ordered" AS o + ON o."major_discipline" = b."major_discipline" + GROUP BY + b."major_discipline", + b."pos", + b."lower_rn", + b."upper_rn" +) +SELECT + "major_discipline", + CASE + WHEN "lower_rn" = "upper_rn" THEN "lower_val" + ELSE "lower_val" + ("pos" - "lower_rn") * ("upper_val" - "lower_val") + END AS "percentile_measure" +FROM "picked" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d19dda725af6c1eaf8a8d76bda8f948f8b06795f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ordered\" AS (\n SELECT\n \"major_discipline\",\n CAST(\"training_hours\" AS REAL) AS \"training_hours_num\",\n ROW_NUMBER() OVER (\n PARTITION BY \"major_discipline\"\n ORDER BY CAST(\"training_hours\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (\n PARTITION BY \"major_discipline\"\n ) AS \"cnt\"\n FROM \"m9\"\n WHERE \"major_discipline\" <> ''\n AND \"training_hours\" <> ''\n),\n\"bounds\" AS (\n SELECT DISTINCT\n \"major_discipline\",\n (1.0 + 0.9 * (\"cnt\" - 1)) AS \"pos\",\n CAST((1.0 + 0.9 * (\"cnt\" - 1)) AS INTEGER) AS \"lower_rn\",\n CASE\n WHEN (1.0 + 0.9 * (\"cnt\" - 1)) = CAST((1.0 + 0.9 * (\"cnt\" - 1)) AS INTEGER)\n THEN CAST((1.0 + 0.9 * (\"cnt\" - 1)) AS INTEGER)\n ELSE CAST((1.0 + 0.9 * (\"cnt\" - 1)) AS INTEGER) + 1\n END AS \"upper_rn\"\n FROM \"ordered\"\n),\n\"picked\" AS (\n SELECT\n b.\"major_discipline\",\n b.\"pos\",\n b.\"lower_rn\",\n b.\"upper_rn\",\n MAX(CASE WHEN o.\"rn\" = b.\"lower_rn\" THEN o.\"training_hours_num\" END) AS \"lower_val\",\n MAX(CASE WHEN o.\"rn\" = b.\"upper_rn\" THEN o.\"training_hours_num\" END) AS \"upper_val\"\n FROM \"bounds\" AS b\n JOIN \"ordered\" AS o\n ON o.\"major_discipline\" = b.\"major_discipline\"\n GROUP BY\n b.\"major_discipline\",\n b.\"pos\",\n b.\"lower_rn\",\n b.\"upper_rn\"\n)\nSELECT\n \"major_discipline\",\n CASE\n WHEN \"lower_rn\" = \"upper_rn\" THEN \"lower_val\"\n ELSE \"lower_val\" + (\"pos\" - \"lower_rn\") * (\"upper_val\" - \"lower_val\")\n END AS \"percentile_measure\"\nFROM \"picked\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"major_discipline\\\",\\n CAST(\\\"training_hours\\\" AS REAL) AS \\\"training_hours_num\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"major_discipline\\\"\\n ORDER BY CAST(\\\"training_hours\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"major_discipline\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"major_discipline\\\" <> ''\\n AND \\\"training_hours\\\" <> ''\\n),\\n\\\"bounds\\\" AS (\\n SELECT DISTINCT\\n \\\"major_discipline\\\",\\n (1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS \\\"pos\\\",\\n CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER) AS \\\"lower_rn\\\",\\n CASE\\n WHEN (1.0 + 0.9 * (\\\"cnt\\\" - 1)) = CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n THEN CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n ELSE CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER) + 1\\n END AS \\\"upper_rn\\\"\\n FROM \\\"ordered\\\"\\n),\\n\\\"picked\\\" AS (\\n SELECT\\n b.\\\"major_discipline\\\",\\n b.\\\"pos\\\",\\n b.\\\"lower_rn\\\",\\n b.\\\"upper_rn\\\",\\n MAX(CASE WHEN o.\\\"rn\\\" = b.\\\"lower_rn\\\" THEN o.\\\"training_hours_num\\\" END) AS \\\"lower_val\\\",\\n MAX(CASE WHEN o.\\\"rn\\\" = b.\\\"upper_rn\\\" THEN o.\\\"training_hours_num\\\" END) AS \\\"upper_val\\\"\\n FROM \\\"bounds\\\" AS b\\n JOIN \\\"ordered\\\" AS o\\n ON o.\\\"major_discipline\\\" = b.\\\"major_discipline\\\"\\n GROUP BY\\n b.\\\"major_discipline\\\",\\n b.\\\"pos\\\",\\n b.\\\"lower_rn\\\",\\n b.\\\"upper_rn\\\"\\n)\\nSELECT\\n \\\"major_discipline\\\",\\n CASE\\n WHEN \\\"lower_rn\\\" = \\\"upper_rn\\\" THEN \\\"lower_val\\\"\\n ELSE \\\"lower_val\\\" + (\\\"pos\\\" - \\\"lower_rn\\\") * (\\\"upper_val\\\" - \\\"lower_val\\\")\\n END AS \\\"percentile_measure\\\"\\nFROM \\\"picked\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"major_discipline\", \"percentile_measure\"], \"rows\": [{\"major_discipline\": \"Other\", \"percentile_measure\": 151.0}, {\"major_discipline\": \"Humanities\", \"percentile_measure\": 150.0}, {\"major_discipline\": \"Business Degree\", \"percentile_measure\": 148.80000000000007}, {\"major_discipline\": \"STEM\", \"percentile_measure\": 146.0}, {\"major_discipline\": \"No Major\", \"percentile_measure\": 130.0}, {\"major_discipline\": \"Arts\", \"percentile_measure\": 126.60000000000002}], \"row_count_returned\": 6, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 67.9}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..988f1057aaefd5c33d46ec1e96fe6ebee3df5f98 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:55:16.734255+00:00", + "ended_at": "2026-05-19T15:55:53.599012+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_72b6191fdbae7aa9", + "problem_id": "v2p_m9_d1c73c1ca7ccb610", + "dataset_id": "m9", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=major_discipline, measure_col=training_hours.", + "bindings": { + "group_col": "major_discipline", + "measure_col": "training_hours", + "top_k": 14, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=89" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_72b6191fdbae7aa9.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_72b6191fdbae7aa9", + "api_calls": 0, + "input_tokens": 14686, + "cached_input_tokens": 13696, + "output_tokens": 2479, + "total_tokens": 17165, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 36792.38, + "sql_execution_elapsed_ms_total": 67.9, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6a0886a7eb3738f816f8e1af8b7483d1c4b54f1b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:55:53.529422+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 36792.38, "started_at": "2026-05-19T15:55:16.736181+00:00", "ended_at": "2026-05-19T15:55:53.528585+00:00", "prompt_metrics": {"chars": 9486, "bytes_utf8": 9486, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 1942, "bytes_utf8": 1942, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14686, "cached_input_tokens": 13696, "output_tokens": 2479, "reasoning_output_tokens": 1843}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ordered\\\" AS (\\n SELECT\\n \\\"major_discipline\\\",\\n CAST(\\\"training_hours\\\" AS REAL) AS \\\"training_hours_num\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"major_discipline\\\"\\n ORDER BY CAST(\\\"training_hours\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"major_discipline\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"major_discipline\\\" <> ''\\n AND \\\"training_hours\\\" <> ''\\n),\\n\\\"bounds\\\" AS (\\n SELECT DISTINCT\\n \\\"major_discipline\\\",\\n (1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS \\\"pos\\\",\\n CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER) AS \\\"lower_rn\\\",\\n CASE\\n WHEN (1.0 + 0.9 * (\\\"cnt\\\" - 1)) = CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n THEN CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER)\\n ELSE CAST((1.0 + 0.9 * (\\\"cnt\\\" - 1)) AS INTEGER) + 1\\n END AS \\\"upper_rn\\\"\\n FROM \\\"ordered\\\"\\n),\\n\\\"picked\\\" AS (\\n SELECT\\n b.\\\"major_discipline\\\",\\n b.\\\"pos\\\",\\n b."} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..5e20cfb21aaaaa3ee4b237fa897bcd79294b0049 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_72b6191fdbae7aa9", + "api_calls": 0, + "input_tokens": 14686, + "cached_input_tokens": 13696, + "output_tokens": 2479, + "total_tokens": 17165, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 36792.38, + "sql_execution_elapsed_ms_total": 67.9, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_72b6191fdbae7aa9/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..e5670c00fd307f8c2dac2704428d161faca1b8aa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=city_development_index, measure_col=enrollee_id. +Result preview: [{"city_development_index": "0.92", "total_measure": 88549363.0}, {"city_development_index": "0.624", "total_measure": 48522501.0}, {"city_development_index": "0.91", "total_measure": 26141445.0}, {"city_development_index": "0.9259999999999999", "total_measure": 22746055.0}, {"city_development_index": "0.698", "total_measure": 11041718.0}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..f1f885a26188b3d06db5d82abe9e7f152fb30340 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_m9_73725bcdc4e67730 +-- problem_id: v2p_m9_c4149a698c5ae9a8 +-- realization_mode: agent +-- source_kind: agent +SELECT "city_development_index", SUM(CAST("enrollee_id" AS REAL)) AS total_measure +FROM "m9" +GROUP BY "city_development_index" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6be7ceee69351c1b49539520ec8bc6ea01dbcc9f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"city_development_index\", SUM(CAST(\"enrollee_id\" AS REAL)) AS total_measure\nFROM \"m9\"\nGROUP BY \"city_development_index\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"city_development_index\\\", SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS total_measure\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city_development_index\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"city_development_index\", \"total_measure\"], \"rows\": [{\"city_development_index\": \"0.92\", \"total_measure\": 88549363.0}, {\"city_development_index\": \"0.624\", \"total_measure\": 48522501.0}, {\"city_development_index\": \"0.91\", \"total_measure\": 26141445.0}, {\"city_development_index\": \"0.9259999999999999\", \"total_measure\": 22746055.0}, {\"city_development_index\": \"0.698\", \"total_measure\": 11041718.0}, {\"city_development_index\": \"0.897\", \"total_measure\": 10373970.0}, {\"city_development_index\": \"0.9390000000000001\", \"total_measure\": 8066149.0}, {\"city_development_index\": \"0.855\", \"total_measure\": 6008244.0}, {\"city_development_index\": \"0.804\", \"total_measure\": 4779330.0}, {\"city_development_index\": \"0.924\", \"total_measure\": 4720653.0}, {\"city_development_index\": \"0.754\", \"total_measure\": 4585048.0}, {\"city_development_index\": \"0.884\", \"total_measure\": 4452462.0}, {\"city_development_index\": \"0.887\", \"total_measure\": 4294841.0}, {\"city_development_index\": \"0.55\", \"total_measure\": 4183927.0}, {\"city_development_index\": \"0.9129999999999999\", \"total_measure\": 3280704.0}, {\"city_development_index\": \"0.925\", \"total_measure\": 2814004.0}, {\"city_development_index\": \"0.802\", \"total_measure\": 2743980.0}, {\"city_development_index\": \"0.8959999999999999\", \"total_measure\": 2500352.0}, {\"city_development_index\": \"0.893\", \"total_measure\": 2479389.0}, {\"city_development_index\": \"0.878\", \"total_measure\": 2430870.0}, {\"city_development_index\": \"0.899\", \"total_measure\": 2381588.0}, {\"city_development_index\": \"0.579\", \"total_measure\": 2369834.0}, {\"city_development_index\": \"0.8270000000000001\", \"total_measure\": 2364109.0}, {\"city_development_index\": \"0.9229999999999999\", \"total_measure\": 2296328.0}, {\"city_development_index\": \"0.682\", \"total_measure\": 2231130.0}, {\"city_development_index\": \"0.762\", \"total_measure\": 2190110.0}, {\"city_development_index\": \"0.743\", \"total_measure\": 2181761.0}, {\"city_development_index\": \"0.6659999999999999\", \"total_measure\": 2166567.0}, {\"city_development_index\": \"0.767\", \"total_measure\": 2073302.0}, {\"city_development_index\": \"0.836\", \"total_measure\": 2043336.0}, {\"city_development_index\": \"0.6890000000000001\", \"total_measure\": 1826228.0}, {\"city_development_index\": \"0.527\", \"total_measure\": 1644363.0}, {\"city_development_index\": \"0.843\", \"total_measure\": 1589385.0}, {\"city_development_index\": \"0.866\", \"total_measure\": 1569835.0}, {\"city_development_index\": \"0.89\", \"total_measure\": 1542740.0}, {\"city_development_index\": \"0.915\", \"total_measure\": 1536694.0}, {\"city_development_index\": \"0.794\", \"total_measure\": 1378952.0}, {\"city_development_index\": \"0.903\", \"total_measure\": 1366498.0}, {\"city_development_index\": \"0.895\", \"total_measure\": 1300315.0}, {\"city_development_index\": \"0.7759999999999999\", \"total_measure\": 1287099.0}, {\"city_development_index\": \"0.555\", \"total_measure\": 1274818.0}, {\"city_development_index\": \"0.9490000000000001\", \"total_measure\": 1249400.0}, {\"city_development_index\": \"0.738\", \"total_measure\": 1231326.0}, {\"city_development_index\": \"0.74\", \"total_measure\": 1227806.0}, {\"city_development_index\": \"0.5579999999999999\", \"total_measure\": 1166114.0}, {\"city_development_index\": \"0.789\", \"total_measure\": 901940.0}, {\"city_development_index\": \"0.727\", \"total_measure\": 895117.0}, {\"city_development_index\": \"0.7659999999999999\", \"total_measure\": 875314.0}, {\"city_development_index\": \"0.848\", \"total_measure\": 851173.0}, {\"city_development_index\": \"0.691\", \"total_measure\": 802610.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 13.01}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..33aff6e8aa0021ca6a7a51e68d111047d9355e19 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:28:18.176454+00:00", + "ended_at": "2026-05-19T15:28:32.287161+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_73725bcdc4e67730", + "problem_id": "v2p_m9_c4149a698c5ae9a8", + "dataset_id": "m9", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=city_development_index, measure_col=enrollee_id.", + "bindings": { + "group_col": "city_development_index", + "measure_col": "enrollee_id", + "top_k": 10, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/2", + "binding_index=0" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_73725bcdc4e67730.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_73725bcdc4e67730", + "api_calls": 0, + "input_tokens": 14654, + "cached_input_tokens": 12288, + "output_tokens": 526, + "total_tokens": 15180, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14091.67, + "sql_execution_elapsed_ms_total": 13.01, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..76118e62344871f77e67adcf291e9d990f6998c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:28:32.271418+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14091.67, "started_at": "2026-05-19T15:28:18.178089+00:00", "ended_at": "2026-05-19T15:28:32.269795+00:00", "prompt_metrics": {"chars": 9319, "bytes_utf8": 9319, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 417, "bytes_utf8": 417, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14654, "cached_input_tokens": 12288, "output_tokens": 526, "reasoning_output_tokens": 414}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"city_development_index\\\", SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS total_measure\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city_development_index\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the requested grouped numeric sum template with group_col=\\\"city_development_index\\\" and measure_col=\\\"enrollee_id\\\". CAST is applied because \\\"enrollee_id\\\" is stored as TEXT in the schema.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..4cd893cfc88c511b92597ec96b5878b76a0f0599 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_73725bcdc4e67730", + "api_calls": 0, + "input_tokens": 14654, + "cached_input_tokens": 12288, + "output_tokens": 526, + "total_tokens": 15180, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14091.67, + "sql_execution_elapsed_ms_total": 13.01, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73725bcdc4e67730/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..bbbfbe9a534e7871c61975541143ae051dec33b7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=experience, condition_col=last_new_job. +Result preview: [{"experience": ">20", "condition_rate": 0.45313451004260497}, {"experience": "19", "condition_rate": 0.35855263157894735}, {"experience": "20", "condition_rate": 0.3581081081081081}, {"experience": "18", "condition_rate": 0.3392857142857143}, {"experience": "15", "condition_rate": 0.2944606413994169}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..a71a31a82d78d79baa3b306edaf35b24dee338cb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_m9_73740aaf7c2ea120 +-- problem_id: v2p_m9_c92d2255af37c253 +-- realization_mode: agent +-- source_kind: agent +SELECT "experience", + AVG(CASE WHEN "last_new_job" = '>4' THEN 1 ELSE 0 END) AS "condition_rate" +FROM "m9" +GROUP BY "experience" +ORDER BY "condition_rate" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c368acf42947bb1a70b46ca3236534236c77ddb1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"experience\",\n AVG(CASE WHEN \"last_new_job\" = '>4' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"m9\"\nGROUP BY \"experience\"\nORDER BY \"condition_rate\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"experience\\\",\\n AVG(CASE WHEN \\\"last_new_job\\\" = '>4' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\", \"columns\": [\"experience\", \"condition_rate\"], \"rows\": [{\"experience\": \">20\", \"condition_rate\": 0.45313451004260497}, {\"experience\": \"19\", \"condition_rate\": 0.35855263157894735}, {\"experience\": \"20\", \"condition_rate\": 0.3581081081081081}, {\"experience\": \"18\", \"condition_rate\": 0.3392857142857143}, {\"experience\": \"15\", \"condition_rate\": 0.2944606413994169}, {\"experience\": \"17\", \"condition_rate\": 0.29239766081871343}, {\"experience\": \"16\", \"condition_rate\": 0.2795275590551181}, {\"experience\": \"14\", \"condition_rate\": 0.23208191126279865}, {\"experience\": \"13\", \"condition_rate\": 0.21804511278195488}, {\"experience\": \"12\", \"condition_rate\": 0.19230769230769232}, {\"experience\": \"11\", \"condition_rate\": 0.1822289156626506}, {\"experience\": \"10\", \"condition_rate\": 0.14923857868020304}, {\"experience\": \"9\", \"condition_rate\": 0.14795918367346939}, {\"experience\": \"\", \"condition_rate\": 0.1076923076923077}, {\"experience\": \"8\", \"condition_rate\": 0.09600997506234414}, {\"experience\": \"7\", \"condition_rate\": 0.07879377431906615}, {\"experience\": \"6\", \"condition_rate\": 0.06332236842105263}, {\"experience\": \"5\", \"condition_rate\": 0.04965034965034965}, {\"experience\": \"<1\", \"condition_rate\": 0.040229885057471264}, {\"experience\": \"3\", \"condition_rate\": 0.0258493353028065}, {\"experience\": \"4\", \"condition_rate\": 0.0}, {\"experience\": \"2\", \"condition_rate\": 0.0}, {\"experience\": \"1\", \"condition_rate\": 0.0}], \"row_count_returned\": 23, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 10.18}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..4e4975107ea07b6f189ab0daac3c65d529e15433 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:01:37.975257+00:00", + "ended_at": "2026-05-19T16:01:45.578854+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_73740aaf7c2ea120", + "problem_id": "v2p_m9_c92d2255af37c253", + "dataset_id": "m9", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=experience, condition_col=last_new_job.", + "bindings": { + "group_col": "experience", + "condition_col": "last_new_job", + "condition_value": ">4", + "positive_value": "1", + "negative_value": ">4", + "top_k": 17, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=2/2", + "binding_index=102" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 7, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_73740aaf7c2ea120.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_73740aaf7c2ea120", + "api_calls": 0, + "input_tokens": 14708, + "cached_input_tokens": 12032, + "output_tokens": 261, + "total_tokens": 14969, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7589.23, + "sql_execution_elapsed_ms_total": 10.18, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..bde2eec001f7444ec5541ab9be650bd5b91368ec --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:01:45.566927+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 7589.23, "started_at": "2026-05-19T16:01:37.976863+00:00", "ended_at": "2026-05-19T16:01:45.566123+00:00", "prompt_metrics": {"chars": 9546, "bytes_utf8": 9546, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 395, "bytes_utf8": 395, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14708, "cached_input_tokens": 12032, "output_tokens": 261, "reasoning_output_tokens": 154}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"experience\\\",\\n AVG(CASE WHEN \\\"last_new_job\\\" = '>4' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Applied the Grouped Condition Rate template with group_col=\\\"experience\\\" and condition_col=\\\"last_new_job\\\", using the bound condition_value '>4'.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..cd133b0b601ec82c120de32a6f2670ce6357c0ba --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_73740aaf7c2ea120", + "api_calls": 0, + "input_tokens": 14708, + "cached_input_tokens": 12032, + "output_tokens": 261, + "total_tokens": 14969, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7589.23, + "sql_execution_elapsed_ms_total": 10.18, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_73740aaf7c2ea120/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..06fbb40713c7d59743f7f293c6c4ead6ed99a8e3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9315, "bytes_utf8": 9315, "lines": 264, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 438, "bytes_utf8": 438, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14651, "cached_input_tokens": 12032, "output_tokens": 434, "reasoning_output_tokens": 311}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..5700274da3474a9c520fe96c3e38bc23ca7cfc21 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_743cc92f9aa7631e", + "api_calls": 0, + "input_tokens": 14651, + "cached_input_tokens": 12032, + "output_tokens": 434, + "total_tokens": 15085, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10250.5, + "sql_execution_elapsed_ms_total": 12.1, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..2ccff4e38ceac7799e0fb215286b4a803895a9f4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:29:06.291813+00:00", + "ended_at": "2026-05-19T15:29:16.542345+00:00", + "elapsed_ms": 10250.5, + "prompt_metrics": { + "chars": 9315, + "bytes_utf8": 9315, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 800, + "bytes_utf8": 800, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 438, + "bytes_utf8": 438, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14651, + "cached_input_tokens": 12032, + "output_tokens": 434, + "reasoning_output_tokens": 311 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..8f980b7a5f6dc8ee01bce97c6a1355eda2ee954e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "primary_family": "subgroup_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=relevent_experience, measure_col=training_hours.", + "planned_template_id": "tpl_h2o_group_sum", + "bindings": { + "group_col": "relevent_experience", + "measure_col": "training_hours", + "top_k": 12, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..71f30a37e8831bdb6b5663706015067f6a91768b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40da-e001-78a3-85c4-0e4b489512f8"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"relevent_experience\\\", SUM(CAST(NULLIF(\\\"training_hours\\\", '') AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"relevent_experience\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Applied tpl_h2o_group_sum with \\\"relevent_experience\\\" as the grouping column. \\\"training_hours\\\" is stored as TEXT, so it is cast to REAL for SQLite summation, and empty strings are treated as NULL.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14651,"cached_input_tokens":12032,"output_tokens":434,"reasoning_output_tokens":311}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..5072c3a7a1991b0c88ab0c45dfb95451b609f8a0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"relevent_experience\", SUM(CAST(NULLIF(\"training_hours\", '') AS REAL)) AS \"total_measure\"\nFROM \"m9\"\nGROUP BY \"relevent_experience\"\nORDER BY \"total_measure\" DESC;","notes":"Applied tpl_h2o_group_sum with \"relevent_experience\" as the grouping column. \"training_hours\" is stored as TEXT, so it is cast to REAL for SQLite summation, and empty strings are treated as NULL."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_743cc92f9aa7631e/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..f931d468d2c3243fdcc8850f6b23061cd276de17 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "Graduate", "support": 11598, "support_share": 0.6053867835891011, "support_rank": 1}, {"value_label": "Masters", "support": 4361, "support_share": 0.22763336465184258, "support_rank": 2}, {"value_label": "High School", "support": 2017, "support_share": 0.10528238855830463, "support_rank": 3}, {"value_label": "", "support": 460, "support_share": 0.02401085708320284, "support_rank": 4}, {"value_label": "Phd", "support": 414, "support_share": 0.021609771374882555, "support_rank": 5}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..308b08f0c6126a190911958a3fc8049cd5d385b2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/generated_sql.sql @@ -0,0 +1,25 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: support_concentration +-- variant_semantic_role: count_distribution +-- template_id: tpl_cardinality_support_rank_profile +-- query_record_id: v2q_m9_74b807ac0a624b86 +-- problem_id: v2p_m9_a7b43d248887fd3a +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "education_level" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "education_level" +) +SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank +FROM grouped +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7df0c99eaae9ff92678253f98e39b51f7c1fb727 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: count_distribution\n-- template_id: tpl_cardinality_support_rank_profile\n-- query_record_id: v2q_m9_74b807ac0a624b86\n-- problem_id: v2p_m9_a7b43d248887fd3a\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"education_level\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"education_level\"\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: count_distribution\\n-- template_id: tpl_cardinality_support_rank_profile\\n-- query_record_id: v2q_m9_74b807ac0a624b86\\n-- problem_id: v2p_m9_a7b43d248887fd3a\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"education_level\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"education_level\\\"\\n)\\nSELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\\nFROM grouped\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"support_rank\"], \"rows\": [{\"value_label\": \"Graduate\", \"support\": 11598, \"support_share\": 0.6053867835891011, \"support_rank\": 1}, {\"value_label\": \"Masters\", \"support\": 4361, \"support_share\": 0.22763336465184258, \"support_rank\": 2}, {\"value_label\": \"High School\", \"support\": 2017, \"support_share\": 0.10528238855830463, \"support_rank\": 3}, {\"value_label\": \"\", \"support\": 460, \"support_share\": 0.02401085708320284, \"support_rank\": 4}, {\"value_label\": \"Phd\", \"support\": 414, \"support_share\": 0.021609771374882555, \"support_rank\": 5}, {\"value_label\": \"Primary School\", \"support\": 308, \"support_share\": 0.01607683474266625, \"support_rank\": 6}], \"row_count_returned\": 6, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 6.42}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..4c3f6d4bd34bafef7a4240bb4da4b7f657355b08 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.305833+00:00", + "ended_at": "2026-05-19T16:08:56.313015+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_74b807ac0a624b86", + "problem_id": "v2p_m9_a7b43d248887fd3a", + "dataset_id": "m9", + "template_id": "tpl_cardinality_support_rank_profile", + "template_name": "Cardinality Support Rank Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "support_concentration", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Support Rank Profile to probe support_rank_profile_consistency with semantic role count_distribution. Focus on group_col=education_level.", + "bindings": { + "group_col": "education_level" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=5", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_74b807ac0a624b86.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_74b807ac0a624b86/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7691ffaf871bb445/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7691ffaf871bb445/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..a5c345c5b807ec3bb2d4acbbe9a3cfaf06cde0e6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7691ffaf871bb445/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:11.602239+00:00", + "ended_at": "2026-05-19T16:08:18.987336+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_7691ffaf871bb445", + "problem_id": "v2p_m9_7c3680e0191b7ad0", + "dataset_id": "m9", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=major_discipline, measure_col=training_hours.", + "bindings": { + "group_col": "major_discipline", + "measure_col": "training_hours", + "top_k": 12, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=137" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7691ffaf871bb445/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7691ffaf871bb445/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..766e5f3e2034a5e91d8ded858eeed26485e7d3b0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7691ffaf871bb445/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:08:14.722794+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3117.9, "started_at": "2026-05-19T16:08:11.604071+00:00", "ended_at": "2026-05-19T16:08:14.722034+00:00", "prompt_metrics": {"chars": 9390, "bytes_utf8": 9390, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fe-a944-7763-ad44-0f55b16a6230\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:08:18.987246+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3262.41, "started_at": "2026-05-19T16:08:15.723980+00:00", "ended_at": "2026-05-19T16:08:18.986437+00:00", "prompt_metrics": {"chars": 9390, "bytes_utf8": 9390, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fe-b974-7621-b4d0-2c0e36f4808c\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3c1fbbfc502ce3527f253e3a3e071a2157c198f3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"total_rows": 19158, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..b86e8d153d6197088f639074f34e2db293525004 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: marginal_missing_rate_consistency +-- intended_facet_id: missing_indicator_distribution +-- variant_semantic_role: missing_indicator_view +-- template_id: tpl_missing_marginal_rate_profile +-- query_record_id: v2q_m9_77b490249310f127 +-- problem_id: v2p_m9_4fe58742644c2da1 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + COUNT(*) AS total_rows, + SUM(CASE WHEN "last_new_job" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "last_new_job" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..cdda64f2b88f2153dc4acb54456ab1e6cd832362 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: marginal_missing_rate_consistency\n-- intended_facet_id: missing_indicator_distribution\n-- variant_semantic_role: missing_indicator_view\n-- template_id: tpl_missing_marginal_rate_profile\n-- query_record_id: v2q_m9_77b490249310f127\n-- problem_id: v2p_m9_4fe58742644c2da1\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"last_new_job\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"last_new_job\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\";", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: marginal_missing_rate_consistency\\n-- intended_facet_id: missing_indicator_distribution\\n-- variant_semantic_role: missing_indicator_view\\n-- template_id: tpl_missing_marginal_rate_profile\\n-- query_record_id: v2q_m9_77b490249310f127\\n-- problem_id: v2p_m9_4fe58742644c2da1\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"last_new_job\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"last_new_job\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\";\", \"columns\": [\"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"total_rows\": 19158, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.9}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..ad8df05dfa083d39fcb51321c146c83326db00b5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:55.931072+00:00", + "ended_at": "2026-05-19T16:08:55.934588+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_77b490249310f127", + "problem_id": "v2p_m9_4fe58742644c2da1", + "dataset_id": "m9", + "template_id": "tpl_missing_marginal_rate_profile", + "template_name": "Marginal Missing Rate Profile", + "family_id": "missingness_structure", + "canonical_subitem_id": "marginal_missing_rate_consistency", + "intended_facet_id": "missing_indicator_distribution", + "variant_semantic_role": "missing_indicator_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Marginal Missing Rate Profile to probe marginal_missing_rate_consistency with semantic role missing_indicator_view. Focus on missing_col=last_new_job.", + "bindings": { + "missing_col": "last_new_job" + }, + "binding_roles": [ + "missing_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table};", + "notes": [ + "default_facets=missing_indicator_distribution", + "template_selection_mode=deterministic", + "problem_index_within_template=8", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_77b490249310f127.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_77b490249310f127/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..57e6e50e137558d62189d7a04633f687fe8dc560 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=education_level, measure_col=city_development_index. +Result preview: [{"education_level": "Primary School", "training_hours": "15", "total_measure": 9.905000000000001, "share_within_group": 3.781559124800996}, {"education_level": "Primary School", "training_hours": "14", "total_measure": 7.992, "share_within_group": 3.051208533610253}, {"education_level": "Phd", "training_hours": "11", "total_measure": 9.813, "share_within_group": 2.684147038630601}, {"education_level": "Phd", "training_hours": "28", "total_measure": 9.071, "share_within_group": 2.4811879942339936}, {"education_level": "Primary School", "training_hours": "28", "total_measure": 6.146, "share_within_group": 2.346437393339416}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..15ead9cef61a100df698600b08ab012cda05d338 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_m9_7917a66b4fa7b3ce +-- problem_id: v2p_m9_5f15db5e3a3eb851 +-- realization_mode: agent +-- source_kind: agent +SELECT + "education_level", + "training_hours", + SUM(CAST("city_development_index" AS REAL)) AS total_measure, + SUM(CAST("city_development_index" AS REAL)) * 100.0 / + SUM(SUM(CAST("city_development_index" AS REAL))) OVER (PARTITION BY "education_level") AS share_within_group +FROM "m9" +WHERE "education_level" <> '' + AND "training_hours" <> '' + AND "city_development_index" <> '' +GROUP BY "education_level", "training_hours" +ORDER BY share_within_group DESC +LIMIT 13; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d3a65bc946b66c740183146f7246d7f86c93136a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"education_level\",\n \"training_hours\",\n SUM(CAST(\"city_development_index\" AS REAL)) AS total_measure,\n SUM(CAST(\"city_development_index\" AS REAL)) * 100.0 /\n SUM(SUM(CAST(\"city_development_index\" AS REAL))) OVER (PARTITION BY \"education_level\") AS share_within_group\nFROM \"m9\"\nWHERE \"education_level\" <> ''\n AND \"training_hours\" <> ''\n AND \"city_development_index\" <> ''\nGROUP BY \"education_level\", \"training_hours\"\nORDER BY share_within_group DESC\nLIMIT 13;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"education_level\\\",\\n \\\"training_hours\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) * 100.0 /\\n SUM(SUM(CAST(\\\"city_development_index\\\" AS REAL))) OVER (PARTITION BY \\\"education_level\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nWHERE \\\"education_level\\\" <> ''\\n AND \\\"training_hours\\\" <> ''\\n AND \\\"city_development_index\\\" <> ''\\nGROUP BY \\\"education_level\\\", \\\"training_hours\\\"\\nORDER BY share_within_group DESC\\nLIMIT 13;\", \"columns\": [\"education_level\", \"training_hours\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"education_level\": \"Primary School\", \"training_hours\": \"15\", \"total_measure\": 9.905000000000001, \"share_within_group\": 3.781559124800996}, {\"education_level\": \"Primary School\", \"training_hours\": \"14\", \"total_measure\": 7.992, \"share_within_group\": 3.051208533610253}, {\"education_level\": \"Phd\", \"training_hours\": \"11\", \"total_measure\": 9.813, \"share_within_group\": 2.684147038630601}, {\"education_level\": \"Phd\", \"training_hours\": \"28\", \"total_measure\": 9.071, \"share_within_group\": 2.4811879942339936}, {\"education_level\": \"Primary School\", \"training_hours\": \"28\", \"total_measure\": 6.146, \"share_within_group\": 2.346437393339416}, {\"education_level\": \"Primary School\", \"training_hours\": \"17\", \"total_measure\": 6.042, \"share_within_group\": 2.3067319769861294}, {\"education_level\": \"Phd\", \"training_hours\": \"13\", \"total_measure\": 8.326, \"share_within_group\": 2.2774083607090985}, {\"education_level\": \"Primary School\", \"training_hours\": \"22\", \"total_measure\": 5.91, \"share_within_group\": 2.2563366408454195}, {\"education_level\": \"Primary School\", \"training_hours\": \"7\", \"total_measure\": 5.864, \"share_within_group\": 2.2387746297660813}, {\"education_level\": \"Primary School\", \"training_hours\": \"9\", \"total_measure\": 5.822, \"share_within_group\": 2.2227397500849464}, {\"education_level\": \"Primary School\", \"training_hours\": \"34\", \"total_measure\": 5.755, \"share_within_group\": 2.1971602991650405}, {\"education_level\": \"High School\", \"training_hours\": \"12\", \"total_measure\": 35.265, \"share_within_group\": 2.096666024557123}, {\"education_level\": \"Primary School\", \"training_hours\": \"11\", \"total_measure\": 5.289, \"share_within_group\": 2.0192494912743526}], \"row_count_returned\": 13, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 46.67}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..ecc1a424e6b4c47e4963c0970e943671bf2db52a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:36:11.538237+00:00", + "ended_at": "2026-05-19T15:36:24.918625+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_7917a66b4fa7b3ce", + "problem_id": "v2p_m9_5f15db5e3a3eb851", + "dataset_id": "m9", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=education_level, measure_col=city_development_index.", + "bindings": { + "group_col": "education_level", + "measure_col": "city_development_index", + "item_col": "training_hours", + "top_k": 13, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=1/2", + "binding_index=28" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_7917a66b4fa7b3ce.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_7917a66b4fa7b3ce", + "api_calls": 0, + "input_tokens": 14769, + "cached_input_tokens": 12032, + "output_tokens": 731, + "total_tokens": 15500, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13327.65, + "sql_execution_elapsed_ms_total": 46.67, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..94982bf891dbff70d98505b80cb86113e9b5493b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:36:24.869681+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13327.65, "started_at": "2026-05-19T15:36:11.540429+00:00", "ended_at": "2026-05-19T15:36:24.868114+00:00", "prompt_metrics": {"chars": 9739, "bytes_utf8": 9739, "lines": 266, "estimated_tokens": null}, "response_metrics": {"chars": 812, "bytes_utf8": 812, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14769, "cached_input_tokens": 12032, "output_tokens": 731, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"education_level\\\",\\n \\\"training_hours\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) * 100.0 /\\n SUM(SUM(CAST(\\\"city_development_index\\\" AS REAL))) OVER (PARTITION BY \\\"education_level\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nWHERE \\\"education_level\\\" <> ''\\n AND \\\"training_hours\\\" <> ''\\n AND \\\"city_development_index\\\" <> ''\\nGROUP BY \\\"education_level\\\", \\\"training_hours\\\"\\nORDER BY share_within_group DESC\\nLIMIT 13;\",\"notes\":\"Filled the Within-Group Share of Total template with group_col=education_level, item_col=training_hours, and measure_col=city_development_index, casting the TEXT measure to REAL and excluding empty strings to avoid zero-like artifacts.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..71b30bf2f303ff3dac3e60e1b66012c249cb0fcc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_7917a66b4fa7b3ce", + "api_calls": 0, + "input_tokens": 14769, + "cached_input_tokens": 12032, + "output_tokens": 731, + "total_tokens": 15500, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13327.65, + "sql_execution_elapsed_ms_total": 46.67, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7917a66b4fa7b3ce/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..6fd51d11a58f94bcd082bd8eace43c78631ca540 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=city_development_index. +Result preview: [{"city_development_index": "0.9490000000000001"}, {"city_development_index": "0.9490000000000001"}, {"city_development_index": "0.9490000000000001"}, {"city_development_index": "0.9490000000000001"}, {"city_development_index": "0.9490000000000001"}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..73915d7f1f6b4de265e02020dd8146236d9a6adb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_m9_7f9287843a434536 +-- problem_id: v2p_m9_6f46d4d36e4dbb19 +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT + "city_development_index", + NTILE(10) OVER ( + ORDER BY CAST(NULLIF("city_development_index", '') AS REAL) DESC + ) AS "tail_bucket" + FROM "m9" + WHERE NULLIF("city_development_index", '') IS NOT NULL +) +SELECT "city_development_index" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY CAST("city_development_index" AS REAL) DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ebc9a4848e257c6e891d39e46b9184bacfe1bc87 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH \"buckets\" AS (\n SELECT\n \"city_development_index\",\n NTILE(10) OVER (\n ORDER BY CAST(NULLIF(\"city_development_index\", '') AS REAL) DESC\n ) AS \"tail_bucket\"\n FROM \"m9\"\n WHERE NULLIF(\"city_development_index\", '') IS NOT NULL\n)\nSELECT \"city_development_index\"\nFROM \"buckets\"\nWHERE \"tail_bucket\" = 1\nORDER BY CAST(\"city_development_index\" AS REAL) DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT\\n \\\"city_development_index\\\",\\n NTILE(10) OVER (\\n ORDER BY CAST(NULLIF(\\\"city_development_index\\\", '') AS REAL) DESC\\n ) AS \\\"tail_bucket\\\"\\n FROM \\\"m9\\\"\\n WHERE NULLIF(\\\"city_development_index\\\", '') IS NOT NULL\\n)\\nSELECT \\\"city_development_index\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY CAST(\\\"city_development_index\\\" AS REAL) DESC;\", \"columns\": [\"city_development_index\"], \"rows\": [{\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}, {\"city_development_index\": \"0.9490000000000001\"}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 37.18}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..163843333bb57b9521f7353d3c5ef0b4031658c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:44:15.334650+00:00", + "ended_at": "2026-05-19T15:44:32.679700+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_7f9287843a434536", + "problem_id": "v2p_m9_6f46d4d36e4dbb19", + "dataset_id": "m9", + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=city_development_index.", + "bindings": { + "measure_col": "city_development_index", + "top_k": 11, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/1", + "binding_index=61" + ], + "template_selection_mode": "rule", + "selected_template_rank": 6, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_7f9287843a434536.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_7f9287843a434536", + "api_calls": 0, + "input_tokens": 14703, + "cached_input_tokens": 13696, + "output_tokens": 653, + "total_tokens": 15356, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17302.96, + "sql_execution_elapsed_ms_total": 37.18, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..cd98bfd815ddcbf6c266efcd6992bbe363c74cf8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:44:32.640852+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 17302.96, "started_at": "2026-05-19T15:44:15.337095+00:00", "ended_at": "2026-05-19T15:44:32.640085+00:00", "prompt_metrics": {"chars": 9479, "bytes_utf8": 9479, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 691, "bytes_utf8": 691, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14703, "cached_input_tokens": 13696, "output_tokens": 653, "reasoning_output_tokens": 468}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT\\n \\\"city_development_index\\\",\\n NTILE(10) OVER (\\n ORDER BY CAST(NULLIF(\\\"city_development_index\\\", '') AS REAL) DESC\\n ) AS \\\"tail_bucket\\\"\\n FROM \\\"m9\\\"\\n WHERE NULLIF(\\\"city_development_index\\\", '') IS NOT NULL\\n)\\nSELECT \\\"city_development_index\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY CAST(\\\"city_development_index\\\" AS REAL) DESC;\",\"notes\":\"Uses the requested Quantile Tail Slice template with measure_col bound to \\\"city_development_index\\\" and num_tiles=10. Casts the TEXT field to REAL for correct numeric tail ordering and excludes blank values before bucketing.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..265867177b44a56620231fd800b3e6e5049f5b50 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_7f9287843a434536", + "api_calls": 0, + "input_tokens": 14703, + "cached_input_tokens": 13696, + "output_tokens": 653, + "total_tokens": 15356, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17302.96, + "sql_execution_elapsed_ms_total": 37.18, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_7f9287843a434536/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..0e53f0c94259ee18316249c1108a4f951bba6999 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=company_size, measure_col=city_development_index. +Result preview: [{"company_size": "", "total_measure": 4840.433}, {"company_size": "50-99", "total_measure": 2556.904}, {"company_size": "100-500", "total_measure": 2147.117}, {"company_size": "10000+", "total_measure": 1708.489}, {"company_size": "10/49", "total_measure": 1197.287}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..5f0468a8aed43e1931b3b7bfc0c8211236a00e3b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_m9_82ef950d3fba8a15 +-- problem_id: v2p_m9_00b524d8e6e4c3d5 +-- realization_mode: agent +-- source_kind: agent +SELECT "company_size", SUM(CAST("city_development_index" AS REAL)) AS total_measure +FROM "m9" +GROUP BY "company_size" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2a94398a74e2cf6f85be83a663283ee8a18b8325 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"company_size\", SUM(CAST(\"city_development_index\" AS REAL)) AS total_measure\nFROM \"m9\"\nGROUP BY \"company_size\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"company_size\\\", SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS total_measure\\nFROM \\\"m9\\\"\\nGROUP BY \\\"company_size\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"company_size\", \"total_measure\"], \"rows\": [{\"company_size\": \"\", \"total_measure\": 4840.433}, {\"company_size\": \"50-99\", \"total_measure\": 2556.904}, {\"company_size\": \"100-500\", \"total_measure\": 2147.117}, {\"company_size\": \"10000+\", \"total_measure\": 1708.489}, {\"company_size\": \"10/49\", \"total_measure\": 1197.287}, {\"company_size\": \"1000-4999\", \"total_measure\": 1138.266}, {\"company_size\": \"<10\", \"total_measure\": 1078.606}, {\"company_size\": \"500-999\", \"total_measure\": 733.945}, {\"company_size\": \"5000-9999\", \"total_measure\": 478.023}], \"row_count_returned\": 9, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 15.08}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..f5202cdf552fea228ecb06babc1a405f5eaeffcb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:31:42.229941+00:00", + "ended_at": "2026-05-19T15:31:57.917007+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_82ef950d3fba8a15", + "problem_id": "v2p_m9_00b524d8e6e4c3d5", + "dataset_id": "m9", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_rank_order", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=company_size, measure_col=city_development_index.", + "bindings": { + "group_col": "company_size", + "measure_col": "city_development_index", + "top_k": 12, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/2", + "binding_index=7" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_82ef950d3fba8a15.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_82ef950d3fba8a15", + "api_calls": 0, + "input_tokens": 14650, + "cached_input_tokens": 13696, + "output_tokens": 387, + "total_tokens": 15037, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15667.09, + "sql_execution_elapsed_ms_total": 15.08, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0f22f2dba8f6570bbd13487632d3a228370259af --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:31:57.899965+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15667.09, "started_at": "2026-05-19T15:31:42.231791+00:00", "ended_at": "2026-05-19T15:31:57.898919+00:00", "prompt_metrics": {"chars": 9316, "bytes_utf8": 9316, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 410, "bytes_utf8": 410, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14650, "cached_input_tokens": 13696, "output_tokens": 387, "reasoning_output_tokens": 284}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"company_size\\\", SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS total_measure\\nFROM \\\"m9\\\"\\nGROUP BY \\\"company_size\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the provided grouped numeric sum template with \\\"company_size\\\" as the grouping column and CAST(\\\"city_development_index\\\" AS REAL) because the column is stored as TEXT in the schema snapshot.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..bec59f44e2f6acdd94cde19bae4f3b35efed9dd8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_82ef950d3fba8a15", + "api_calls": 0, + "input_tokens": 14650, + "cached_input_tokens": 13696, + "output_tokens": 387, + "total_tokens": 15037, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15667.09, + "sql_execution_elapsed_ms_total": 15.08, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_82ef950d3fba8a15/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..38c29dc0e2255e83a5a94166439c69c4e93d30c1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=experience, condition_col=last_new_job. +Result preview: [{"experience": "1", "condition_rate": 0.5701275045537341}, {"experience": "2", "condition_rate": 0.5261756876663709}, {"experience": "4", "condition_rate": 0.5245901639344263}, {"experience": "5", "condition_rate": 0.5146853146853146}, {"experience": "6", "condition_rate": 0.5115131578947368}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..2fc68325284c1fbcce2ff3b13c0e5135869b8b38 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_m9_830dffe61f3471d1 +-- problem_id: v2p_m9_5c4afe90ed8f0a01 +-- realization_mode: agent +-- source_kind: agent +SELECT "experience", + AVG(CASE WHEN "last_new_job" = '1' THEN 1 ELSE 0 END) AS "condition_rate" +FROM "m9" +GROUP BY "experience" +ORDER BY "condition_rate" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8d6d37a9cbb78687154b139f515640f2f15f031b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"experience\",\n AVG(CASE WHEN \"last_new_job\" = '1' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"m9\"\nGROUP BY \"experience\"\nORDER BY \"condition_rate\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"experience\\\",\\n AVG(CASE WHEN \\\"last_new_job\\\" = '1' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\", \"columns\": [\"experience\", \"condition_rate\"], \"rows\": [{\"experience\": \"1\", \"condition_rate\": 0.5701275045537341}, {\"experience\": \"2\", \"condition_rate\": 0.5261756876663709}, {\"experience\": \"4\", \"condition_rate\": 0.5245901639344263}, {\"experience\": \"5\", \"condition_rate\": 0.5146853146853146}, {\"experience\": \"6\", \"condition_rate\": 0.5115131578947368}, {\"experience\": \"3\", \"condition_rate\": 0.4881831610044313}, {\"experience\": \"8\", \"condition_rate\": 0.4763092269326683}, {\"experience\": \"7\", \"condition_rate\": 0.4659533073929961}, {\"experience\": \"<1\", \"condition_rate\": 0.4482758620689655}, {\"experience\": \"11\", \"condition_rate\": 0.4397590361445783}, {\"experience\": \"10\", \"condition_rate\": 0.4385786802030457}, {\"experience\": \"9\", \"condition_rate\": 0.4306122448979592}, {\"experience\": \"14\", \"condition_rate\": 0.40102389078498296}, {\"experience\": \"12\", \"condition_rate\": 0.3967611336032389}, {\"experience\": \"13\", \"condition_rate\": 0.37092731829573933}, {\"experience\": \"17\", \"condition_rate\": 0.35964912280701755}, {\"experience\": \"20\", \"condition_rate\": 0.3310810810810811}, {\"experience\": \"15\", \"condition_rate\": 0.33090379008746357}, {\"experience\": \"\", \"condition_rate\": 0.3230769230769231}, {\"experience\": \"18\", \"condition_rate\": 0.32142857142857145}, {\"experience\": \"16\", \"condition_rate\": 0.32086614173228345}, {\"experience\": \"19\", \"condition_rate\": 0.3092105263157895}, {\"experience\": \">20\", \"condition_rate\": 0.24102251978088862}], \"row_count_returned\": 23, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.96}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..a8494556c2c349d2abd75e910757c84eb91b48bf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:01:30.041190+00:00", + "ended_at": "2026-05-19T16:01:37.974727+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_830dffe61f3471d1", + "problem_id": "v2p_m9_5c4afe90ed8f0a01", + "dataset_id": "m9", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=experience, condition_col=last_new_job.", + "bindings": { + "group_col": "experience", + "condition_col": "last_new_job", + "condition_value": "1", + "positive_value": "1", + "negative_value": ">4", + "top_k": 12, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/2", + "binding_index=102" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_830dffe61f3471d1.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_830dffe61f3471d1", + "api_calls": 0, + "input_tokens": 14709, + "cached_input_tokens": 12032, + "output_tokens": 248, + "total_tokens": 14957, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7919.63, + "sql_execution_elapsed_ms_total": 9.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..22cf29e934c868707c5876b402d1d89f4d2e4fe3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:01:37.963314+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 7919.63, "started_at": "2026-05-19T16:01:30.042848+00:00", "ended_at": "2026-05-19T16:01:37.962505+00:00", "prompt_metrics": {"chars": 9548, "bytes_utf8": 9548, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 371, "bytes_utf8": 371, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14709, "cached_input_tokens": 12032, "output_tokens": 248, "reasoning_output_tokens": 146}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"experience\\\",\\n AVG(CASE WHEN \\\"last_new_job\\\" = '1' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Grouped condition rate over \\\"experience\\\", measuring the within-group proportion of rows where \\\"last_new_job\\\" equals '1'.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..3b4c446d80a2698d5d7ef9420d9301d655305442 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_830dffe61f3471d1", + "api_calls": 0, + "input_tokens": 14709, + "cached_input_tokens": 12032, + "output_tokens": 248, + "total_tokens": 14957, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7919.63, + "sql_execution_elapsed_ms_total": 9.96, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_830dffe61f3471d1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..a9c58a632a5e820ef4663f03976453038038bfb3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "28", "support": 329, "support_share": 0.017172982566029858, "support_rank": 1}, {"value_label": "12", "support": 292, "support_share": 0.015241674496293977, "support_rank": 2}, {"value_label": "18", "support": 291, "support_share": 0.015189476980895709, "support_rank": 3}, {"value_label": "22", "support": 282, "support_share": 0.014719699342311305, "support_rank": 4}, {"value_label": "50", "support": 279, "support_share": 0.014563106796116505, "support_rank": 5}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..77362ee351630fb7f0cebc18d08b87a4b5dfe075 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/generated_sql.sql @@ -0,0 +1,25 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: support_concentration +-- variant_semantic_role: count_distribution +-- template_id: tpl_cardinality_support_rank_profile +-- query_record_id: v2q_m9_84a228608f5fb357 +-- problem_id: v2p_m9_0facee1738c58fa6 +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "training_hours" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "training_hours" +) +SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank +FROM grouped +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2f3742dd624f29dce9a011388ea447d9aeb96e55 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: count_distribution\n-- template_id: tpl_cardinality_support_rank_profile\n-- query_record_id: v2q_m9_84a228608f5fb357\n-- problem_id: v2p_m9_0facee1738c58fa6\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"training_hours\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"training_hours\"\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: count_distribution\\n-- template_id: tpl_cardinality_support_rank_profile\\n-- query_record_id: v2q_m9_84a228608f5fb357\\n-- problem_id: v2p_m9_0facee1738c58fa6\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"training_hours\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"training_hours\\\"\\n)\\nSELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\\nFROM grouped\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"support_rank\"], \"rows\": [{\"value_label\": \"28\", \"support\": 329, \"support_share\": 0.017172982566029858, \"support_rank\": 1}, {\"value_label\": \"12\", \"support\": 292, \"support_share\": 0.015241674496293977, \"support_rank\": 2}, {\"value_label\": \"18\", \"support\": 291, \"support_share\": 0.015189476980895709, \"support_rank\": 3}, {\"value_label\": \"22\", \"support\": 282, \"support_share\": 0.014719699342311305, \"support_rank\": 4}, {\"value_label\": \"50\", \"support\": 279, \"support_share\": 0.014563106796116505, \"support_rank\": 5}, {\"value_label\": \"20\", \"support\": 278, \"support_share\": 0.014510909280718238, \"support_rank\": 6}, {\"value_label\": \"17\", \"support\": 273, \"support_share\": 0.014249921703726902, \"support_rank\": 7}, {\"value_label\": \"24\", \"support\": 273, \"support_share\": 0.014249921703726902, \"support_rank\": 8}, {\"value_label\": \"34\", \"support\": 261, \"support_share\": 0.013623551518947698, \"support_rank\": 9}, {\"value_label\": \"6\", \"support\": 261, \"support_share\": 0.013623551518947698, \"support_rank\": 10}, {\"value_label\": \"23\", \"support\": 258, \"support_share\": 0.013466958972752897, \"support_rank\": 11}, {\"value_label\": \"21\", \"support\": 256, \"support_share\": 0.013362563941956363, \"support_rank\": 12}, {\"value_label\": \"26\", \"support\": 254, \"support_share\": 0.013258168911159829, \"support_rank\": 13}, {\"value_label\": \"56\", \"support\": 250, \"support_share\": 0.013049378849566761, \"support_rank\": 14}, {\"value_label\": \"42\", \"support\": 242, \"support_share\": 0.012631798726380624, \"support_rank\": 15}, {\"value_label\": \"10\", \"support\": 241, \"support_share\": 0.012579601210982358, \"support_rank\": 16}, {\"value_label\": \"11\", \"support\": 237, \"support_share\": 0.01237081114938929, \"support_rank\": 17}, {\"value_label\": \"48\", \"support\": 237, \"support_share\": 0.01237081114938929, \"support_rank\": 18}, {\"value_label\": \"9\", \"support\": 234, \"support_share\": 0.012214218603194488, \"support_rank\": 19}, {\"value_label\": \"14\", \"support\": 231, \"support_share\": 0.012057626056999686, \"support_rank\": 20}, {\"value_label\": \"15\", \"support\": 230, \"support_share\": 0.01200542854160142, \"support_rank\": 21}, {\"value_label\": \"8\", \"support\": 227, \"support_share\": 0.011848835995406619, \"support_rank\": 22}, {\"value_label\": \"4\", \"support\": 224, \"support_share\": 0.011692243449211817, \"support_rank\": 23}, {\"value_label\": \"46\", \"support\": 223, \"support_share\": 0.01164004593381355, \"support_rank\": 24}, {\"value_label\": \"13\", \"support\": 213, \"support_share\": 0.01111807077983088, \"support_rank\": 25}, {\"value_label\": \"36\", \"support\": 211, \"support_share\": 0.011013675749034346, \"support_rank\": 26}, {\"value_label\": \"7\", \"support\": 209, \"support_share\": 0.010909280718237812, \"support_rank\": 27}, {\"value_label\": \"32\", \"support\": 207, \"support_share\": 0.010804885687441278, \"support_rank\": 28}, {\"value_label\": \"44\", \"support\": 205, \"support_share\": 0.010700490656644744, \"support_rank\": 29}, {\"value_label\": \"25\", \"support\": 199, \"support_share\": 0.010387305564255142, \"support_rank\": 30}, {\"value_label\": \"43\", \"support\": 199, \"support_share\": 0.010387305564255142, \"support_rank\": 31}, {\"value_label\": \"52\", \"support\": 196, \"support_share\": 0.01023071301806034, \"support_rank\": 32}, {\"value_label\": \"16\", \"support\": 192, \"support_share\": 0.010021922956467273, \"support_rank\": 33}, {\"value_label\": \"40\", \"support\": 192, \"support_share\": 0.010021922956467273, \"support_rank\": 34}, {\"value_label\": \"30\", \"support\": 187, \"support_share\": 0.009760935379475937, \"support_rank\": 35}, {\"value_label\": \"31\", \"support\": 184, \"support_share\": 0.009604342833281135, \"support_rank\": 36}, {\"value_label\": \"29\", \"support\": 179, \"support_share\": 0.009343355256289801, \"support_rank\": 37}, {\"value_label\": \"39\", \"support\": 178, \"support_share\": 0.009291157740891533, \"support_rank\": 38}, {\"value_label\": \"51\", \"support\": 176, \"support_share\": 0.009186762710095, \"support_rank\": 39}, {\"value_label\": \"45\", \"support\": 175, \"support_share\": 0.009134565194696732, \"support_rank\": 40}, {\"value_label\": \"55\", \"support\": 171, \"support_share\": 0.008925775133103664, \"support_rank\": 41}, {\"value_label\": \"78\", \"support\": 165, \"support_share\": 0.008612590040714062, \"support_rank\": 42}, {\"value_label\": \"19\", \"support\": 163, \"support_share\": 0.008508195009917528, \"support_rank\": 43}, {\"value_label\": \"37\", \"support\": 163, \"support_share\": 0.008508195009917528, \"support_rank\": 44}, {\"value_label\": \"35\", \"support\": 162, \"support_share\": 0.00845599749451926, \"support_rank\": 45}, {\"value_label\": \"54\", \"support\": 161, \"support_share\": 0.008403799979120994, \"support_rank\": 46}, {\"value_label\": \"47\", \"support\": 157, \"support_share\": 0.008195009917527927, \"support_rank\": 47}, {\"value_label\": \"72\", \"support\": 153, \"support_share\": 0.007986219855934857, \"support_rank\": 48}, {\"value_label\": \"33\", \"support\": 150, \"support_share\": 0.007829627309740057, \"support_rank\": 49}, {\"value_label\": \"41\", \"support\": 145, \"support_share\": 0.007568639732748721, \"support_rank\": 50}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 8.99}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..45f45323124ad23cc90e4b47116e95fa995c27b4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.355128+00:00", + "ended_at": "2026-05-19T16:08:56.364953+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_84a228608f5fb357", + "problem_id": "v2p_m9_0facee1738c58fa6", + "dataset_id": "m9", + "template_id": "tpl_cardinality_support_rank_profile", + "template_name": "Cardinality Support Rank Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "support_concentration", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Support Rank Profile to probe support_rank_profile_consistency with semantic role count_distribution. Focus on group_col=training_hours.", + "bindings": { + "group_col": "training_hours" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=11", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 11, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_84a228608f5fb357.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_84a228608f5fb357/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..b25a491ff0938c9eca85f43bf040618bce865fb9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:06:51.715855+00:00", + "ended_at": "2026-05-19T16:06:54.417836+00:00", + "elapsed_ms": 2701.95, + "returncode": 1, + "prompt_metrics": { + "chars": 9386, + "bytes_utf8": 9386, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..865a8a26d5ee4f4771ef64e5d8d78630313b9142 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:06:55.419850+00:00", + "ended_at": "2026-05-19T16:06:58.273166+00:00", + "elapsed_ms": 2853.28, + "returncode": 1, + "prompt_metrics": { + "chars": 9386, + "bytes_utf8": 9386, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..00fe363cf9dd9f293cb6e5af590664deb1208682 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=gender, measure_col=city_development_index.", + "planned_template_id": "tpl_m4_window_partition_avg", + "bindings": { + "group_col": "gender", + "measure_col": "city_development_index", + "top_k": 13, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..00fe363cf9dd9f293cb6e5af590664deb1208682 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=gender, measure_col=city_development_index.", + "planned_template_id": "tpl_m4_window_partition_avg", + "bindings": { + "group_col": "gender", + "measure_col": "city_development_index", + "top_k": 13, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..5c7d9ee24ae500dfb09d32d4a73691d81f86c6ff --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fd-713b-7b40-9539-fbff04487dd2"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e151cfab7931d0e7c914648ad9b0b78a8608d758 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fd-713b-7b40-9539-fbff04487dd2"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..517b92ac58a880f7398a0f137f538d6f8cde527a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fd-7fb8-7ca3-88b8-30f5b91bf526"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..19361fac3f884dd11057eb7602ed0eea0561c085 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fd-7fb8-7ca3-88b8-30f5b91bf526"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8724da76d607f6f3/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..8e266c73810018c16686732d6d8489e54421e4f6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=city_development_index. +Result preview: [{"empirical_cdf_at_threshold": 0.8675749034345965}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..6662897c588bbdbe518e99e99e75e1093d2081da --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/generated_sql.sql @@ -0,0 +1,15 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_threshold_rarity_cdf +-- query_record_id: v2q_m9_87b197a7201ecee2 +-- problem_id: v2p_m9_3fb04db5d5566b3a +-- realization_mode: agent +-- source_kind: agent +SELECT AVG(CASE WHEN CAST(NULLIF("city_development_index", '') AS REAL) <= 0.92 THEN 1.0 WHEN NULLIF("city_development_index", '') IS NOT NULL THEN 0.0 END) AS "empirical_cdf_at_threshold" +FROM "m9"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f7bc75bfe59d07de38a44e7064be1aca3711d6a5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(NULLIF(\"city_development_index\", '') AS REAL) <= 0.92 THEN 1.0 WHEN NULLIF(\"city_development_index\", '') IS NOT NULL THEN 0.0 END) AS \"empirical_cdf_at_threshold\"\nFROM \"m9\";", "result": "{\"query\": \"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(NULLIF(\\\"city_development_index\\\", '') AS REAL) <= 0.92 THEN 1.0 WHEN NULLIF(\\\"city_development_index\\\", '') IS NOT NULL THEN 0.0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"m9\\\";\", \"columns\": [\"empirical_cdf_at_threshold\"], \"rows\": [{\"empirical_cdf_at_threshold\": 0.8675749034345965}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 6.02}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..46d9587417ab4cbd9427a1afd47d8c77b73920a5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:02:39.811085+00:00", + "ended_at": "2026-05-19T16:02:50.796958+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_87b197a7201ecee2", + "problem_id": "v2p_m9_3fb04db5d5566b3a", + "dataset_id": "m9", + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=city_development_index.", + "bindings": { + "measure_col": "city_development_index", + "top_k": 14, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/1", + "binding_index=109" + ], + "template_selection_mode": "rule", + "selected_template_rank": 10, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_87b197a7201ecee2.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_87b197a7201ecee2", + "api_calls": 0, + "input_tokens": 14639, + "cached_input_tokens": 13696, + "output_tokens": 449, + "total_tokens": 15088, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10975.84, + "sql_execution_elapsed_ms_total": 6.02, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5811c5a8739b15e37f7b42c4784c21ad2c3677dd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:02:50.789484+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10975.84, "started_at": "2026-05-19T16:02:39.812826+00:00", "ended_at": "2026-05-19T16:02:50.788693+00:00", "prompt_metrics": {"chars": 9245, "bytes_utf8": 9245, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 495, "bytes_utf8": 495, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14639, "cached_input_tokens": 13696, "output_tokens": 449, "reasoning_output_tokens": 313}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(NULLIF(\\\"city_development_index\\\", '') AS REAL) <= 0.92 THEN 1.0 WHEN NULLIF(\\\"city_development_index\\\", '') IS NOT NULL THEN 0.0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"m9\\\";\",\"notes\":\"Uses the planned Threshold Rarity CDF template with measure_col bound to \\\"city_development_index\\\" and threshold 0.92. Because the column is stored as TEXT, the query casts nonblank values to REAL and ignores blank entries.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..e271c9611dae50820bd919c40fab6a4f51e425b2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_87b197a7201ecee2", + "api_calls": 0, + "input_tokens": 14639, + "cached_input_tokens": 13696, + "output_tokens": 449, + "total_tokens": 15088, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10975.84, + "sql_execution_elapsed_ms_total": 6.02, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87b197a7201ecee2/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7adae627fe02e4cf6ad63e360332c37518a75df2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9872, "bytes_utf8": 9872, "lines": 264, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 898, "bytes_utf8": 898, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14788, "cached_input_tokens": 13696, "output_tokens": 616, "reasoning_output_tokens": 385}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..ac41c9eb876224504a949aa80866414ad96d04d8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_87c5d58615f920e6", + "api_calls": 0, + "input_tokens": 14788, + "cached_input_tokens": 13696, + "output_tokens": 616, + "total_tokens": 15404, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13265.63, + "sql_execution_elapsed_ms_total": 9.47, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..f115daf0b88ffb05b6720b43039f6c7936e60ba0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:49:24.732561+00:00", + "ended_at": "2026-05-19T15:49:37.998217+00:00", + "elapsed_ms": 13265.63, + "prompt_metrics": { + "chars": 9872, + "bytes_utf8": 9872, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1313, + "bytes_utf8": 1313, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 898, + "bytes_utf8": 898, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14788, + "cached_input_tokens": 13696, + "output_tokens": 616, + "reasoning_output_tokens": 385 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..1706974a3ea3b2e87d22caac6140556c1de6a26c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "primary_family": "tail_rarity_structure", + "portability": "partial", + "sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=company_size, measure_col=city_development_index.", + "planned_template_id": "tpl_tpch_relative_total_threshold", + "bindings": { + "group_col": "company_size", + "measure_col": "city_development_index", + "top_k": 14, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..210f38dde54a168107161d23142ebe826c0e9143 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40ed-77ac-7503-ad31-9a1b773a9f21"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"company_size\\\", SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"company_size\\\" IS NOT NULL\\n AND \\\"company_size\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n GROUP BY \\\"company_size\\\"\\n), total AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM grouped\\n)\\nSELECT g.\\\"company_size\\\", g.\\\"group_value\\\"\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Uses the requested template with group_col=\\\"company_size\\\" and measure_col=\\\"city_development_index\\\", casting the TEXT measure to REAL for SQLite aggregation and filtering out blank group/measure values to keep the grouped view stable.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14788,"cached_input_tokens":13696,"output_tokens":616,"reasoning_output_tokens":385}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..f95ea408ea618d54d367d9fef543e3b78268cbda --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT \"company_size\", SUM(CAST(\"city_development_index\" AS REAL)) AS \"group_value\"\n FROM \"m9\"\n WHERE \"company_size\" IS NOT NULL\n AND \"company_size\" <> ''\n AND \"city_development_index\" IS NOT NULL\n AND \"city_development_index\" <> ''\n GROUP BY \"company_size\"\n), total AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM grouped\n)\nSELECT g.\"company_size\", g.\"group_value\"\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;","notes":"Uses the requested template with group_col=\"company_size\" and measure_col=\"city_development_index\", casting the TEXT measure to REAL for SQLite aggregation and filtering out blank group/measure values to keep the grouped view stable."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_87c5d58615f920e6/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..baaa5ad350875c4f8ff7a1877f54c96cae526d85 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9869, "bytes_utf8": 9869, "lines": 264, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 817, "bytes_utf8": 817, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14789, "cached_input_tokens": 13696, "output_tokens": 740, "reasoning_output_tokens": 516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..d49a1202d6dc7e0b4035d7a5226d41a9dc995711 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_893dba06558177eb", + "api_calls": 0, + "input_tokens": 14789, + "cached_input_tokens": 13696, + "output_tokens": 740, + "total_tokens": 15529, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 22540.83, + "sql_execution_elapsed_ms_total": 17.36, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..89020a47037609b4cebe1d235b7cfc202d6d0deb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:47:35.310513+00:00", + "ended_at": "2026-05-19T15:47:57.851395+00:00", + "elapsed_ms": 22540.83, + "prompt_metrics": { + "chars": 9869, + "bytes_utf8": 9869, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1906, + "bytes_utf8": 1906, + "lines": 6, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 817, + "bytes_utf8": 817, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14789, + "cached_input_tokens": 13696, + "output_tokens": 740, + "reasoning_output_tokens": 516 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..7c7193d2b233d9f6329f538dc00e0000af3f8f4a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "primary_family": "tail_rarity_structure", + "portability": "partial", + "sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=enrolled_university, measure_col=enrollee_id.", + "planned_template_id": "tpl_tpch_relative_total_threshold", + "bindings": { + "group_col": "enrolled_university", + "measure_col": "enrollee_id", + "top_k": 15, + "top_n": 7, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..ff90706c143f6ccb47513ec010fe84e2a3a06edb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,6 @@ +{"type":"thread.started","thread_id":"019e40eb-cc8c-7552-9e89-257414aaefca"} +{"type":"turn.started"} +{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1990052, Requested 15424. Please try again in 164ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"error","message":"Reconnecting... 3/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1998835, Requested 15424. Please try again in 427ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"enrolled_university\\\",\\n COUNT(\\\"enrollee_id\\\") AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n GROUP BY \\\"enrolled_university\\\"\\n), \\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT\\n g.\\\"enrolled_university\\\",\\n g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.05\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Applied the requested template structure with group_col=\\\"enrolled_university\\\" and a 0.05 relative-to-total threshold. Used COUNT(\\\"enrollee_id\\\") instead of SUM(\\\"enrollee_id\\\") because the prompt specifies count_distribution and enrollee_id is an identifier-like TEXT field.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14789,"cached_input_tokens":13696,"output_tokens":740,"reasoning_output_tokens":516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..bbeafa81cb39a6e553ecc2a6dec22e32055d7983 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n SELECT\n \"enrolled_university\",\n COUNT(\"enrollee_id\") AS \"group_value\"\n FROM \"m9\"\n GROUP BY \"enrolled_university\"\n), \"total\" AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM \"grouped\"\n)\nSELECT\n g.\"enrolled_university\",\n g.\"group_value\"\nFROM \"grouped\" AS g\nCROSS JOIN \"total\" AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.05\nORDER BY g.\"group_value\" DESC;","notes":"Applied the requested template structure with group_col=\"enrolled_university\" and a 0.05 relative-to-total threshold. Used COUNT(\"enrollee_id\") instead of SUM(\"enrollee_id\") because the prompt specifies count_distribution and enrollee_id is an identifier-like TEXT field."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_893dba06558177eb/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..cf937b4754aedc1841e87ac6c4641944b1efff03 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"experience": ">20", "support": 3286, "avg_response": 0.8922550213024956}, {"experience": "5", "support": 1430, "avg_response": 0.8020965034965035}, {"experience": "4", "support": 1403, "avg_response": 0.793791874554526}, {"experience": "3", "support": 1354, "avg_response": 0.7813271787296897}, {"experience": "6", "support": 1216, "avg_response": 0.8045674342105263}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..3bfd0e0ef24755fbf022b3a7872bdbc8d8c5b8ea --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: high_cardinality_response_stability +-- intended_facet_id: target_cardinality_cross_section +-- variant_semantic_role: focused_target_view +-- template_id: tpl_cardinality_high_card_response_stability +-- query_record_id: v2q_m9_89ee3c52650d6acc +-- problem_id: v2p_m9_ec460733570c96eb +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "experience", + COUNT(*) AS support, + AVG("city_development_index") AS avg_response +FROM "m9" +GROUP BY "experience" +HAVING COUNT(*) >= 5.0 +ORDER BY support DESC, avg_response DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5675e8226fe71057376be94c123b0f57509ccfc4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: high_cardinality_response_stability\n-- intended_facet_id: target_cardinality_cross_section\n-- variant_semantic_role: focused_target_view\n-- template_id: tpl_cardinality_high_card_response_stability\n-- query_record_id: v2q_m9_89ee3c52650d6acc\n-- problem_id: v2p_m9_ec460733570c96eb\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"experience\",\n COUNT(*) AS support,\n AVG(\"city_development_index\") AS avg_response\nFROM \"m9\"\nGROUP BY \"experience\"\nHAVING COUNT(*) >= 5.0\nORDER BY support DESC, avg_response DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: high_cardinality_response_stability\\n-- intended_facet_id: target_cardinality_cross_section\\n-- variant_semantic_role: focused_target_view\\n-- template_id: tpl_cardinality_high_card_response_stability\\n-- query_record_id: v2q_m9_89ee3c52650d6acc\\n-- problem_id: v2p_m9_ec460733570c96eb\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"experience\\\",\\n COUNT(*) AS support,\\n AVG(\\\"city_development_index\\\") AS avg_response\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\"\\nHAVING COUNT(*) >= 5.0\\nORDER BY support DESC, avg_response DESC;\", \"columns\": [\"experience\", \"support\", \"avg_response\"], \"rows\": [{\"experience\": \">20\", \"support\": 3286, \"avg_response\": 0.8922550213024956}, {\"experience\": \"5\", \"support\": 1430, \"avg_response\": 0.8020965034965035}, {\"experience\": \"4\", \"support\": 1403, \"avg_response\": 0.793791874554526}, {\"experience\": \"3\", \"support\": 1354, \"avg_response\": 0.7813271787296897}, {\"experience\": \"6\", \"support\": 1216, \"avg_response\": 0.8045674342105263}, {\"experience\": \"2\", \"support\": 1127, \"avg_response\": 0.7780372670807453}, {\"experience\": \"7\", \"support\": 1028, \"avg_response\": 0.8079163424124514}, {\"experience\": \"10\", \"support\": 985, \"avg_response\": 0.8401543147208123}, {\"experience\": \"9\", \"support\": 980, \"avg_response\": 0.8325908163265305}, {\"experience\": \"8\", \"support\": 802, \"avg_response\": 0.8175049875311721}, {\"experience\": \"15\", \"support\": 686, \"avg_response\": 0.8662521865889213}, {\"experience\": \"11\", \"support\": 664, \"avg_response\": 0.8463599397590361}, {\"experience\": \"14\", \"support\": 586, \"avg_response\": 0.8570392491467577}, {\"experience\": \"1\", \"support\": 549, \"avg_response\": 0.7706265938069217}, {\"experience\": \"<1\", \"support\": 522, \"avg_response\": 0.7405306513409962}, {\"experience\": \"16\", \"support\": 508, \"avg_response\": 0.8670157480314961}, {\"experience\": \"12\", \"support\": 494, \"avg_response\": 0.8389190283400809}, {\"experience\": \"13\", \"support\": 399, \"avg_response\": 0.8544586466165415}, {\"experience\": \"17\", \"support\": 342, \"avg_response\": 0.8586461988304093}, {\"experience\": \"19\", \"support\": 304, \"avg_response\": 0.8707730263157896}, {\"experience\": \"18\", \"support\": 280, \"avg_response\": 0.8650571428571429}, {\"experience\": \"20\", \"support\": 148, \"avg_response\": 0.871945945945946}, {\"experience\": \"\", \"support\": 65, \"avg_response\": 0.7711076923076923}], \"row_count_returned\": 23, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 10.54}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..3225ecaae86b4cc6dd63a0f90fb4839e60b8c943 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/run_manifest.json @@ -0,0 +1,60 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.468574+00:00", + "ended_at": "2026-05-19T16:08:56.479870+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_89ee3c52650d6acc", + "problem_id": "v2p_m9_ec460733570c96eb", + "dataset_id": "m9", + "template_id": "tpl_cardinality_high_card_response_stability", + "template_name": "High-Cardinality Response Stability", + "family_id": "cardinality_structure", + "canonical_subitem_id": "high_cardinality_response_stability", + "intended_facet_id": "target_cardinality_cross_section", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template High-Cardinality Response Stability to probe high_cardinality_response_stability with semantic role focused_target_view. Focus on measure_col=city_development_index, key_col=experience.", + "bindings": { + "key_col": "experience", + "measure_col": "city_development_index", + "min_support": 5 + }, + "binding_roles": [ + "key_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {key_col},\n COUNT(*) AS support,\n AVG({measure_col}) AS avg_response\nFROM {table}\nGROUP BY {key_col}\nHAVING COUNT(*) >= {min_support}\nORDER BY support DESC, avg_response DESC;", + "notes": [ + "default_facets=target_cardinality_cross_section", + "template_selection_mode=deterministic", + "problem_index_within_template=9", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 9, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_89ee3c52650d6acc.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_89ee3c52650d6acc/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..92615c7062d93f3b786e8083e05f1cb3656be702 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=city_development_index, condition_col=gender. +Result preview: [{"city_development_index": "0.73", "condition_rate": 1.0}, {"city_development_index": "0.693", "condition_rate": 1.0}, {"city_development_index": "0.898", "condition_rate": 0.9090909090909091}, {"city_development_index": "0.83", "condition_rate": 0.90625}, {"city_development_index": "0.9209999999999999", "condition_rate": 0.9}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..212298ada4ec776fc4ad42fb5c4deef436dbb5b1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_m9_8daba880f1fffdde +-- problem_id: v2p_m9_9552c166356fa58e +-- realization_mode: agent +-- source_kind: agent +SELECT "city_development_index", + AVG(CASE WHEN "gender" = 'Male' THEN 1 ELSE 0 END) AS condition_rate +FROM "m9" +GROUP BY "city_development_index" +ORDER BY condition_rate DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..36d7883dec164c29807a4a46d680d6a14df2264f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"city_development_index\",\n AVG(CASE WHEN \"gender\" = 'Male' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"m9\"\nGROUP BY \"city_development_index\"\nORDER BY condition_rate DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"city_development_index\\\",\\n AVG(CASE WHEN \\\"gender\\\" = 'Male' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city_development_index\\\"\\nORDER BY condition_rate DESC;\", \"columns\": [\"city_development_index\", \"condition_rate\"], \"rows\": [{\"city_development_index\": \"0.73\", \"condition_rate\": 1.0}, {\"city_development_index\": \"0.693\", \"condition_rate\": 1.0}, {\"city_development_index\": \"0.898\", \"condition_rate\": 0.9090909090909091}, {\"city_development_index\": \"0.83\", \"condition_rate\": 0.90625}, {\"city_development_index\": \"0.9209999999999999\", \"condition_rate\": 0.9}, {\"city_development_index\": \"0.78\", \"condition_rate\": 0.8333333333333334}, {\"city_development_index\": \"0.8959999999999999\", \"condition_rate\": 0.8285714285714286}, {\"city_development_index\": \"0.866\", \"condition_rate\": 0.8252427184466019}, {\"city_development_index\": \"0.836\", \"condition_rate\": 0.8083333333333333}, {\"city_development_index\": \"0.865\", \"condition_rate\": 0.8076923076923077}, {\"city_development_index\": \"0.742\", \"condition_rate\": 0.8}, {\"city_development_index\": \"0.847\", \"condition_rate\": 0.7804878048780488}, {\"city_development_index\": \"0.68\", \"condition_rate\": 0.7777777777777778}, {\"city_development_index\": \"0.878\", \"condition_rate\": 0.7748344370860927}, {\"city_development_index\": \"0.9129999999999999\", \"condition_rate\": 0.7715736040609137}, {\"city_development_index\": \"0.893\", \"condition_rate\": 0.76875}, {\"city_development_index\": \"0.924\", \"condition_rate\": 0.7674418604651163}, {\"city_development_index\": \"0.848\", \"condition_rate\": 0.7659574468085106}, {\"city_development_index\": \"0.9390000000000001\", \"condition_rate\": 0.7565392354124748}, {\"city_development_index\": \"0.89\", \"condition_rate\": 0.7522123893805309}, {\"city_development_index\": \"0.795\", \"condition_rate\": 0.75}, {\"city_development_index\": \"0.649\", \"condition_rate\": 0.75}, {\"city_development_index\": \"0.91\", \"condition_rate\": 0.7475538160469667}, {\"city_development_index\": \"0.895\", \"condition_rate\": 0.7441860465116279}, {\"city_development_index\": \"0.802\", \"condition_rate\": 0.7428571428571429}, {\"city_development_index\": \"0.9259999999999999\", \"condition_rate\": 0.7425149700598802}, {\"city_development_index\": \"0.9490000000000001\", \"condition_rate\": 0.7341772151898734}, {\"city_development_index\": \"0.74\", \"condition_rate\": 0.7313432835820896}, {\"city_development_index\": \"0.887\", \"condition_rate\": 0.730909090909091}, {\"city_development_index\": \"0.8270000000000001\", \"condition_rate\": 0.7299270072992701}, {\"city_development_index\": \"0.9229999999999999\", \"condition_rate\": 0.7272727272727273}, {\"city_development_index\": \"0.769\", \"condition_rate\": 0.7272727272727273}, {\"city_development_index\": \"0.762\", \"condition_rate\": 0.7265625}, {\"city_development_index\": \"0.925\", \"condition_rate\": 0.7251461988304093}, {\"city_development_index\": \"0.5579999999999999\", \"condition_rate\": 0.72}, {\"city_development_index\": \"0.754\", \"condition_rate\": 0.7178571428571429}, {\"city_development_index\": \"0.92\", \"condition_rate\": 0.713076923076923}, {\"city_development_index\": \"0.6659999999999999\", \"condition_rate\": 0.7105263157894737}, {\"city_development_index\": \"0.722\", \"condition_rate\": 0.7037037037037037}, {\"city_development_index\": \"0.843\", \"condition_rate\": 0.7021276595744681}, {\"city_development_index\": \"0.884\", \"condition_rate\": 0.6992481203007519}, {\"city_development_index\": \"0.899\", \"condition_rate\": 0.6978021978021978}, {\"city_development_index\": \"0.897\", \"condition_rate\": 0.6945392491467577}, {\"city_development_index\": \"0.64\", \"condition_rate\": 0.6923076923076923}, {\"city_development_index\": \"0.915\", \"condition_rate\": 0.6914893617021277}, {\"city_development_index\": \"0.794\", \"condition_rate\": 0.6881720430107527}, {\"city_development_index\": \"0.804\", \"condition_rate\": 0.6875}, {\"city_development_index\": \"0.855\", \"condition_rate\": 0.6867749419953596}, {\"city_development_index\": \"0.743\", \"condition_rate\": 0.684931506849315}, {\"city_development_index\": \"0.764\", \"condition_rate\": 0.6666666666666666}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 15.75}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..3db4a3ac5cdfcb62a254a7c166fe4fb626729fe4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:59:08.724316+00:00", + "ended_at": "2026-05-19T15:59:21.951094+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_8daba880f1fffdde", + "problem_id": "v2p_m9_9552c166356fa58e", + "dataset_id": "m9", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=city_development_index, condition_col=gender.", + "bindings": { + "group_col": "city_development_index", + "condition_col": "gender", + "condition_value": "Male", + "positive_value": "Male", + "negative_value": "", + "top_k": 11, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/2", + "binding_index=96" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_8daba880f1fffdde.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_8daba880f1fffdde", + "api_calls": 0, + "input_tokens": 14709, + "cached_input_tokens": 13696, + "output_tokens": 325, + "total_tokens": 15034, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12202.57, + "sql_execution_elapsed_ms_total": 15.75, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0cf92ccbedc2b65c27c15b390f7a697e599c6489 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:59:12.110244+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3383.09, "started_at": "2026-05-19T15:59:08.726384+00:00", "ended_at": "2026-05-19T15:59:12.109499+00:00", "prompt_metrics": {"chars": 9564, "bytes_utf8": 9564, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f6-60c6-7ae2-8904-803d93138940\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:59:21.932789+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8819.48, "started_at": "2026-05-19T15:59:13.111736+00:00", "ended_at": "2026-05-19T15:59:21.931267+00:00", "prompt_metrics": {"chars": 9564, "bytes_utf8": 9564, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 405, "bytes_utf8": 405, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14709, "cached_input_tokens": 13696, "output_tokens": 325, "reasoning_output_tokens": 221}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"city_development_index\\\",\\n AVG(CASE WHEN \\\"gender\\\" = 'Male' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city_development_index\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Computes the within-group proportion of rows where gender is Male for each city_development_index, following the Grouped Condition Rate template.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..82619e899c83df9d89985226cc3bcfc3d8d4feb7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_8daba880f1fffdde", + "api_calls": 0, + "input_tokens": 14709, + "cached_input_tokens": 13696, + "output_tokens": 325, + "total_tokens": 15034, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12202.57, + "sql_execution_elapsed_ms_total": 15.75, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8daba880f1fffdde/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..a98d02c2520c5aeb011c7cfa2c43c6f8259092db --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"last_new_job": "1", "total_rows": 8040, "missing_rows": 0, "missing_rate": 0.0}, {"last_new_job": ">4", "total_rows": 3290, "missing_rows": 0, "missing_rate": 0.0}, {"last_new_job": "2", "total_rows": 2900, "missing_rows": 0, "missing_rate": 0.0}, {"last_new_job": "never", "total_rows": 2452, "missing_rows": 0, "missing_rate": 0.0}, {"last_new_job": "4", "total_rows": 1029, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..29c50e00cdb7ffd654f59d9044e87bc6a36b7c9f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: co_missingness_pattern_consistency +-- intended_facet_id: missing_target_interaction +-- variant_semantic_role: missing_target_interaction +-- template_id: tpl_missing_target_interaction +-- query_record_id: v2q_m9_8f0dbc1969c2a7aa +-- problem_id: v2p_m9_257d6e3076babd19 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "last_new_job", + COUNT(*) AS total_rows, + SUM(CASE WHEN "company_size" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "company_size" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9" +GROUP BY "last_new_job" +ORDER BY missing_rate DESC, total_rows DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..47c58c01a76a789858d7fee0636e8dff3a937f60 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: co_missingness_pattern_consistency\n-- intended_facet_id: missing_target_interaction\n-- variant_semantic_role: missing_target_interaction\n-- template_id: tpl_missing_target_interaction\n-- query_record_id: v2q_m9_8f0dbc1969c2a7aa\n-- problem_id: v2p_m9_257d6e3076babd19\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"last_new_job\",\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"company_size\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"company_size\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\"\nGROUP BY \"last_new_job\"\nORDER BY missing_rate DESC, total_rows DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: co_missingness_pattern_consistency\\n-- intended_facet_id: missing_target_interaction\\n-- variant_semantic_role: missing_target_interaction\\n-- template_id: tpl_missing_target_interaction\\n-- query_record_id: v2q_m9_8f0dbc1969c2a7aa\\n-- problem_id: v2p_m9_257d6e3076babd19\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"last_new_job\\\",\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"company_size\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"company_size\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"last_new_job\\\"\\nORDER BY missing_rate DESC, total_rows DESC;\", \"columns\": [\"last_new_job\", \"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"last_new_job\": \"1\", \"total_rows\": 8040, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"last_new_job\": \">4\", \"total_rows\": 3290, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"last_new_job\": \"2\", \"total_rows\": 2900, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"last_new_job\": \"never\", \"total_rows\": 2452, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"last_new_job\": \"4\", \"total_rows\": 1029, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"last_new_job\": \"3\", \"total_rows\": 1024, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"last_new_job\": \"\", \"total_rows\": 423, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 7, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.09}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e8d96e36d889c1ba425a575513728c42676e41d4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/run_manifest.json @@ -0,0 +1,59 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.144980+00:00", + "ended_at": "2026-05-19T16:08:56.154792+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_8f0dbc1969c2a7aa", + "problem_id": "v2p_m9_257d6e3076babd19", + "dataset_id": "m9", + "template_id": "tpl_missing_target_interaction", + "template_name": "Missingness-Target Interaction", + "family_id": "missingness_structure", + "canonical_subitem_id": "co_missingness_pattern_consistency", + "intended_facet_id": "missing_target_interaction", + "variant_semantic_role": "missing_target_interaction", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Missingness-Target Interaction to probe co_missingness_pattern_consistency with semantic role missing_target_interaction. Focus on target_col=last_new_job, missing_col=company_size.", + "bindings": { + "missing_col": "company_size", + "target_col": "last_new_job" + }, + "binding_roles": [ + "missing_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {target_col},\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {target_col}\nORDER BY missing_rate DESC, total_rows DESC;", + "notes": [ + "default_facets=missing_rate_by_subgroup,missing_target_interaction", + "template_selection_mode=deterministic", + "problem_index_within_template=10", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 10, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_8f0dbc1969c2a7aa.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_8f0dbc1969c2a7aa/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9256061188839702/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9256061188839702/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..5214e81b5fa95626db4c41aef269222896ca9fb7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9256061188839702/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:53:52.440423+00:00", + "ended_at": "2026-05-19T15:53:59.874304+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_9256061188839702", + "problem_id": "v2p_m9_a1276bc7f03968a5", + "dataset_id": "m9", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=relevent_experience, measure_col=training_hours.", + "bindings": { + "group_col": "relevent_experience", + "measure_col": "training_hours", + "top_k": 16, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 70.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=2/2", + "binding_index=86" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 3, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9256061188839702/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9256061188839702/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..680759cb4ec0eccd18344b26eee0429837b24d7c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9256061188839702/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:53:55.694954+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3251.74, "started_at": "2026-05-19T15:53:52.442409+00:00", "ended_at": "2026-05-19T15:53:55.694175+00:00", "prompt_metrics": {"chars": 9494, "bytes_utf8": 9494, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f1-8d46-7a71-a14f-eb53732b4da5\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:53:59.874171+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3176.61, "started_at": "2026-05-19T15:53:56.696534+00:00", "ended_at": "2026-05-19T15:53:59.873196+00:00", "prompt_metrics": {"chars": 9494, "bytes_utf8": 9494, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f1-9df6-7622-a5b1-79cc9c84eaf0\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5398a8e7f2626ec2dae695bdc4c57a335ac19b6c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9706, "bytes_utf8": 9706, "lines": 266, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 774, "bytes_utf8": 774, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14765, "cached_input_tokens": 12032, "output_tokens": 915, "reasoning_output_tokens": 703}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..a7d9388797b77ce429930544e847c3cb9bab7fc5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_929285095c6e54d3", + "api_calls": 0, + "input_tokens": 14765, + "cached_input_tokens": 12032, + "output_tokens": 915, + "total_tokens": 15680, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18644.51, + "sql_execution_elapsed_ms_total": 19.59, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..7b8ffe38267fc994548f566834cdfca64755e428 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:34:33.023034+00:00", + "ended_at": "2026-05-19T15:34:51.667573+00:00", + "elapsed_ms": 18644.51, + "prompt_metrics": { + "chars": 9706, + "bytes_utf8": 9706, + "lines": 266, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1171, + "bytes_utf8": 1171, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 774, + "bytes_utf8": 774, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14765, + "cached_input_tokens": 12032, + "output_tokens": 915, + "reasoning_output_tokens": 703 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..db6573b504e0e02c92fa987d298dd3ad8b7468fd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,266 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "required_roles": [ + "group_col", + "item_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=gender, measure_col=city_development_index.", + "planned_template_id": "tpl_tpcds_within_group_share", + "bindings": { + "group_col": "gender", + "measure_col": "city_development_index", + "item_col": "city", + "top_k": 10, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..2e24e5ab24fb2694b1fcaaa629ddf2785c19228e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40df-dc52-71e2-82fb-8e25cc1cb1c9"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"gender\\\",\\n \\\"city\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"city_development_index\\\" AS REAL))) OVER (PARTITION BY \\\"gender\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nWHERE \\\"gender\\\" <> ''\\n AND \\\"city\\\" <> ''\\n AND \\\"city_development_index\\\" <> ''\\nGROUP BY \\\"gender\\\", \\\"city\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Instantiated the Within-Group Share of Total template with group_col=\\\"gender\\\", item_col=\\\"city\\\", and measure_col=\\\"city_development_index\\\". Cast the measure to REAL because it is stored as TEXT in SQLite, and filtered out empty-string values for cleaner within-group shares.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14765,"cached_input_tokens":12032,"output_tokens":915,"reasoning_output_tokens":703}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..d9d5d37899370c7aa580e6d977bd2c3b00f60c5d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"gender\",\n \"city\",\n SUM(CAST(\"city_development_index\" AS REAL)) AS total_measure,\n SUM(CAST(\"city_development_index\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"city_development_index\" AS REAL))) OVER (PARTITION BY \"gender\") AS share_within_group\nFROM \"m9\"\nWHERE \"gender\" <> ''\n AND \"city\" <> ''\n AND \"city_development_index\" <> ''\nGROUP BY \"gender\", \"city\"\nORDER BY share_within_group DESC;","notes":"Instantiated the Within-Group Share of Total template with group_col=\"gender\", item_col=\"city\", and measure_col=\"city_development_index\". Cast the measure to REAL because it is stored as TEXT in SQLite, and filtered out empty-string values for cleaner within-group shares."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_929285095c6e54d3/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..568f986e7d442ee7c7cb2425be61bbde1acaf7ad --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:06:16.839403+00:00", + "ended_at": "2026-05-19T16:06:20.110867+00:00", + "elapsed_ms": 3271.44, + "returncode": 1, + "prompt_metrics": { + "chars": 9278, + "bytes_utf8": 9278, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..e94a23518b57721fbb888baef1a8880ad7cde72e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:06:21.113123+00:00", + "ended_at": "2026-05-19T16:06:24.440169+00:00", + "elapsed_ms": 3327.01, + "returncode": 1, + "prompt_metrics": { + "chars": 9278, + "bytes_utf8": 9278, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..3db3b695101453fb429ae0c9e6b7e506a8e70d9b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=company_size.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "company_size", + "top_k": 12, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..3db3b695101453fb429ae0c9e6b7e506a8e70d9b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=company_size.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "company_size", + "top_k": 12, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..a8f11fc84d0b3c53afa1b6287e1fb3d38c747d8b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-e901-7571-bfae-a501223487ad"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e96b7ca7246e6fa18905fc23be6ed5982036c7a6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-e901-7571-bfae-a501223487ad"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..c95643283a677611d69fce5a2ea555376b734d4e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-f9b1-76c2-8c91-db04f28fd0e7"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..b6b4e98c18fa384bbf82af300c4fe5fbf928f3fb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-f9b1-76c2-8c91-db04f28fd0e7"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_953875ed74da25ce/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..160dba8a1a365da0eb3f5585c24748320d3eec14 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=gender, measure_col=city_development_index. +Result preview: [{"gender": "Male", "group_value": 11093.115}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..5e9974964f9c41ffaa9a5883164b80b01f86166e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/generated_sql.sql @@ -0,0 +1,35 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_m9_95a13eb726323bed +-- problem_id: v2p_m9_9cf23e4558adc1d5 +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT + "gender", + SUM(CAST("city_development_index" AS REAL)) AS "group_value" + FROM "m9" + WHERE "gender" IS NOT NULL + AND "gender" <> '' + AND "city_development_index" IS NOT NULL + AND "city_development_index" <> '' + GROUP BY "gender" +), +"total" AS ( + SELECT SUM("group_value") AS "total_value" + FROM "grouped" +) +SELECT + g."gender", + g."group_value" +FROM "grouped" AS g +CROSS JOIN "total" AS t +WHERE g."group_value" > t."total_value" * 0.1 +ORDER BY g."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..25ec023ec416e76835338a84fc448cb02345de48 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n SELECT\n \"gender\",\n SUM(CAST(\"city_development_index\" AS REAL)) AS \"group_value\"\n FROM \"m9\"\n WHERE \"gender\" IS NOT NULL\n AND \"gender\" <> ''\n AND \"city_development_index\" IS NOT NULL\n AND \"city_development_index\" <> ''\n GROUP BY \"gender\"\n),\n\"total\" AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM \"grouped\"\n)\nSELECT\n g.\"gender\",\n g.\"group_value\"\nFROM \"grouped\" AS g\nCROSS JOIN \"total\" AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"gender\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"gender\\\" IS NOT NULL\\n AND \\\"gender\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n GROUP BY \\\"gender\\\"\\n),\\n\\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT\\n g.\\\"gender\\\",\\n g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\", \"columns\": [\"gender\", \"group_value\"], \"rows\": [{\"gender\": \"Male\", \"group_value\": 11093.115}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.67}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..ca276dc4cbdb95ef8521266f42676c2939811c0b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:46:18.397406+00:00", + "ended_at": "2026-05-19T15:46:31.998923+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_95a13eb726323bed", + "problem_id": "v2p_m9_9cf23e4558adc1d5", + "dataset_id": "m9", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=gender, measure_col=city_development_index.", + "bindings": { + "group_col": "gender", + "measure_col": "city_development_index", + "top_k": 13, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/2", + "binding_index=73" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_95a13eb726323bed.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_95a13eb726323bed", + "api_calls": 0, + "input_tokens": 14786, + "cached_input_tokens": 13696, + "output_tokens": 755, + "total_tokens": 15541, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13587.17, + "sql_execution_elapsed_ms_total": 9.67, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e2a40389f5bbc19a0301d0b71b748df4ab5b5005 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:46:31.987732+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13587.17, "started_at": "2026-05-19T15:46:18.399717+00:00", "ended_at": "2026-05-19T15:46:31.986921+00:00", "prompt_metrics": {"chars": 9860, "bytes_utf8": 9860, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 926, "bytes_utf8": 926, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14786, "cached_input_tokens": 13696, "output_tokens": 755, "reasoning_output_tokens": 493}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"gender\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"gender\\\" IS NOT NULL\\n AND \\\"gender\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n GROUP BY \\\"gender\\\"\\n),\\n\\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT\\n g.\\\"gender\\\",\\n g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Uses the requested template with group_col=gender and measure_col=city_development_index. Because city_development_index is stored as TEXT, it is cast to REAL before summation. Empty and NULL gender/city_development_index values are filtered out to form a stable grouped view.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..6d979c7b16b6e58bc7160e576cffd225db19b401 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_95a13eb726323bed", + "api_calls": 0, + "input_tokens": 14786, + "cached_input_tokens": 13696, + "output_tokens": 755, + "total_tokens": 15541, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13587.17, + "sql_execution_elapsed_ms_total": 9.67, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_95a13eb726323bed/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..24e6b98f4d2cb21aa869e44649e9d6640c417dc9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9614, "bytes_utf8": 9614, "lines": 268, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 467, "bytes_utf8": 467, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14739, "cached_input_tokens": 12032, "output_tokens": 250, "reasoning_output_tokens": 132}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..9d7de07dddbcc4c24af90e3735b8bf1cfe9a0108 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_96674019d933c5a1", + "api_calls": 0, + "input_tokens": 14739, + "cached_input_tokens": 12032, + "output_tokens": 250, + "total_tokens": 14989, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 7812.69, + "sql_execution_elapsed_ms_total": 5.21, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..3a14eb153ed72018e26a04c13555c6e8b7000758 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:42:40.654832+00:00", + "ended_at": "2026-05-19T15:42:48.467555+00:00", + "elapsed_ms": 7812.69, + "prompt_metrics": { + "chars": 9614, + "bytes_utf8": 9614, + "lines": 268, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 830, + "bytes_utf8": 830, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 467, + "bytes_utf8": 467, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14739, + "cached_input_tokens": 12032, + "output_tokens": 250, + "reasoning_output_tokens": 132 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..850c045726ff8d5deeae8e3b99c926ed134c7d1e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,268 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_c2_filtered_group_count_2d", + "template_name": "Filtered Two-Dimensional Group Count", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;", + "required_roles": [ + "group_col", + "group_col_2", + "predicate_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=experience, group_col_2=company_size.", + "planned_template_id": "tpl_c2_filtered_group_count_2d", + "bindings": { + "group_col": "experience", + "group_col_2": "company_size", + "predicate_col": "company_size", + "predicate_op": "=", + "predicate_value": "10000+", + "top_k": 11, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..8d2548645d3678628e19971cbaec1c0708ebcc08 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40e7-4d23-7a42-b22b-3fb23e83a22d"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"experience\\\", \\\"company_size\\\", COUNT(*) AS row_count\\nFROM \\\"m9\\\"\\nWHERE \\\"company_size\\\" = '10000+'\\nGROUP BY \\\"experience\\\", \\\"company_size\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Used the required template and fixed bindings exactly as provided. Because the filter is on \\\"company_size\\\" = '10000+' while also grouping by \\\"company_size\\\", the second grouping column will be constant in the result.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14739,"cached_input_tokens":12032,"output_tokens":250,"reasoning_output_tokens":132}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..1a2fd9a0d55fcfd415cf7397ffca69e56548e21a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"experience\", \"company_size\", COUNT(*) AS row_count\nFROM \"m9\"\nWHERE \"company_size\" = '10000+'\nGROUP BY \"experience\", \"company_size\"\nORDER BY row_count DESC;","notes":"Used the required template and fixed bindings exactly as provided. Because the filter is on \"company_size\" = '10000+' while also grouping by \"company_size\", the second grouping column will be constant in the result."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96674019d933c5a1/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..b13469284d135a9a0400de8aea0e7ba716e0a523 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=relevent_experience, measure_col=training_hours. +Result preview: [{"relevent_experience": "Has relevent experience", "total_measure": 907516.0}, {"relevent_experience": "No relevent experience", "total_measure": 344783.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..1c508c53d281b387543c10877de71a287b233220 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_m9_96766205f49fc86e +-- problem_id: v2p_m9_2edbebef2f7d323b +-- realization_mode: agent +-- source_kind: agent +SELECT "relevent_experience", SUM(CAST(NULLIF("training_hours", '') AS REAL)) AS total_measure +FROM "m9" +GROUP BY "relevent_experience" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7199b8b05666d897bbec6e9099ae76cd61394f7a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"relevent_experience\", SUM(CAST(NULLIF(\"training_hours\", '') AS REAL)) AS total_measure\nFROM \"m9\"\nGROUP BY \"relevent_experience\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"relevent_experience\\\", SUM(CAST(NULLIF(\\\"training_hours\\\", '') AS REAL)) AS total_measure\\nFROM \\\"m9\\\"\\nGROUP BY \\\"relevent_experience\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"relevent_experience\", \"total_measure\"], \"rows\": [{\"relevent_experience\": \"Has relevent experience\", \"total_measure\": 907516.0}, {\"relevent_experience\": \"No relevent experience\", \"total_measure\": 344783.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 19.07}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..0ddbb2c79de9210f5ae96b4bf5988748326a38ab --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:29:16.558177+00:00", + "ended_at": "2026-05-19T15:29:26.259526+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_96766205f49fc86e", + "problem_id": "v2p_m9_2edbebef2f7d323b", + "dataset_id": "m9", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=relevent_experience, measure_col=training_hours.", + "bindings": { + "group_col": "relevent_experience", + "measure_col": "training_hours", + "top_k": 17, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 70.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=2/2", + "binding_index=2" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 3, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_96766205f49fc86e.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_96766205f49fc86e", + "api_calls": 0, + "input_tokens": 14651, + "cached_input_tokens": 12032, + "output_tokens": 372, + "total_tokens": 15023, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9675.01, + "sql_execution_elapsed_ms_total": 19.07, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f1e40368287146e934dbeba65dd15a5e541bb3e7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:29:26.237408+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9675.01, "started_at": "2026-05-19T15:29:16.560518+00:00", "ended_at": "2026-05-19T15:29:26.235561+00:00", "prompt_metrics": {"chars": 9316, "bytes_utf8": 9316, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 409, "bytes_utf8": 409, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14651, "cached_input_tokens": 12032, "output_tokens": 372, "reasoning_output_tokens": 265}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"relevent_experience\\\", SUM(CAST(NULLIF(\\\"training_hours\\\", '') AS REAL)) AS total_measure\\nFROM \\\"m9\\\"\\nGROUP BY \\\"relevent_experience\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the provided grouped numeric sum template with \\\"relevent_experience\\\" as the grouping column and cast text-based \\\"training_hours\\\" to REAL, treating empty strings as NULL.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..372f410ed28cf8e81b4fac85ccdb5b9f2d1221c4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_96766205f49fc86e", + "api_calls": 0, + "input_tokens": 14651, + "cached_input_tokens": 12032, + "output_tokens": 372, + "total_tokens": 15023, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9675.01, + "sql_execution_elapsed_ms_total": 19.07, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96766205f49fc86e/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..04ee871a8b889386bd4884abb2635dfd3bff5d49 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=relevent_experience, measure_col=training_hours. +Result preview: [{"relevent_experience": "Has relevent experience", "group_value": 907516.0}, {"relevent_experience": "No relevent experience", "group_value": 344783.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..4982b952b38c2299d37f35ab9b69f64e80dd63aa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/generated_sql.sql @@ -0,0 +1,30 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_m9_96bd9dabe9b751c0 +-- problem_id: v2p_m9_51677d8fa7b9dbab +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "relevent_experience", SUM(CAST("training_hours" AS REAL)) AS group_value + FROM "m9" + WHERE "relevent_experience" IS NOT NULL + AND TRIM("relevent_experience") <> '' + AND "training_hours" IS NOT NULL + AND TRIM("training_hours") <> '' + GROUP BY "relevent_experience" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."relevent_experience", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.05 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..028399ed4454a982a1e8ae7be93b89cce8f65c10 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT \"relevent_experience\", SUM(CAST(\"training_hours\" AS REAL)) AS group_value\n FROM \"m9\"\n WHERE \"relevent_experience\" IS NOT NULL\n AND TRIM(\"relevent_experience\") <> ''\n AND \"training_hours\" IS NOT NULL\n AND TRIM(\"training_hours\") <> ''\n GROUP BY \"relevent_experience\"\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.\"relevent_experience\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.05\nORDER BY g.group_value DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"relevent_experience\\\", SUM(CAST(\\\"training_hours\\\" AS REAL)) AS group_value\\n FROM \\\"m9\\\"\\n WHERE \\\"relevent_experience\\\" IS NOT NULL\\n AND TRIM(\\\"relevent_experience\\\") <> ''\\n AND \\\"training_hours\\\" IS NOT NULL\\n AND TRIM(\\\"training_hours\\\") <> ''\\n GROUP BY \\\"relevent_experience\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"relevent_experience\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\", \"columns\": [\"relevent_experience\", \"group_value\"], \"rows\": [{\"relevent_experience\": \"Has relevent experience\", \"group_value\": 907516.0}, {\"relevent_experience\": \"No relevent experience\", \"group_value\": 344783.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 27.76}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..69aa3f9ae8d80482e62696ca28c32d51ca8f011d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:46:53.511189+00:00", + "ended_at": "2026-05-19T15:47:12.749753+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_96bd9dabe9b751c0", + "problem_id": "v2p_m9_51677d8fa7b9dbab", + "dataset_id": "m9", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=relevent_experience, measure_col=training_hours.", + "bindings": { + "group_col": "relevent_experience", + "measure_col": "training_hours", + "top_k": 19, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 70.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=2/2", + "binding_index=74" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 3, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_96bd9dabe9b751c0.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_96bd9dabe9b751c0", + "api_calls": 0, + "input_tokens": 14789, + "cached_input_tokens": 13696, + "output_tokens": 717, + "total_tokens": 15506, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 19202.66, + "sql_execution_elapsed_ms_total": 27.76, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2dcf39d6bc15ed96f9376f286e18b3e6c0a05d4c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:47:12.718266+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 19202.66, "started_at": "2026-05-19T15:46:53.513745+00:00", "ended_at": "2026-05-19T15:47:12.716448+00:00", "prompt_metrics": {"chars": 9872, "bytes_utf8": 9872, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 905, "bytes_utf8": 905, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14789, "cached_input_tokens": 13696, "output_tokens": 717, "reasoning_output_tokens": 480}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"relevent_experience\\\", SUM(CAST(\\\"training_hours\\\" AS REAL)) AS group_value\\n FROM \\\"m9\\\"\\n WHERE \\\"relevent_experience\\\" IS NOT NULL\\n AND TRIM(\\\"relevent_experience\\\") <> ''\\n AND \\\"training_hours\\\" IS NOT NULL\\n AND TRIM(\\\"training_hours\\\") <> ''\\n GROUP BY \\\"relevent_experience\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"relevent_experience\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\",\"notes\":\"Uses the required template with group_col=\\\"relevent_experience\\\" and measure_col=\\\"training_hours\\\", casting the text measure to REAL and filtering null/blank values to form a stable grouped view before applying the 5% relative-to-total threshold.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..c8af68884f34b5749d74019a72d22c345f708c82 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_96bd9dabe9b751c0", + "api_calls": 0, + "input_tokens": 14789, + "cached_input_tokens": 13696, + "output_tokens": 717, + "total_tokens": 15506, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 19202.66, + "sql_execution_elapsed_ms_total": 27.76, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_96bd9dabe9b751c0/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..fb6b63879a01a2868a155036bb0c71e048a9514f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=major_discipline, group_col_2=last_new_job. +Result preview: [{"major_discipline": "STEM", "last_new_job": "1", "row_count": 4557}, {"major_discipline": "STEM", "last_new_job": ">4", "row_count": 1730}, {"major_discipline": "STEM", "last_new_job": "2", "row_count": 1600}, {"major_discipline": "STEM", "last_new_job": "never", "row_count": 990}, {"major_discipline": "STEM", "last_new_job": "4", "row_count": 581}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..18a4a5ed41ce5cca1c63c7da0c133ef748d362ef --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: count_distribution +-- template_id: tpl_c2_filtered_group_count_2d +-- query_record_id: v2q_m9_97769e99c5051056 +-- problem_id: v2p_m9_c0d3b471062c277c +-- realization_mode: agent +-- source_kind: agent +SELECT "major_discipline", "last_new_job", COUNT(*) AS "row_count" +FROM "m9" +WHERE "education_level" = 'Graduate' +GROUP BY "major_discipline", "last_new_job" +ORDER BY "row_count" DESC +LIMIT 13; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e2018cd7ebc2fdc5b459ee40ad287f7804c73d5d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"major_discipline\", \"last_new_job\", COUNT(*) AS \"row_count\"\nFROM \"m9\"\nWHERE \"education_level\" = 'Graduate'\nGROUP BY \"major_discipline\", \"last_new_job\"\nORDER BY \"row_count\" DESC\nLIMIT 13;", "result": "{\"query\": \"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"major_discipline\\\", \\\"last_new_job\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m9\\\"\\nWHERE \\\"education_level\\\" = 'Graduate'\\nGROUP BY \\\"major_discipline\\\", \\\"last_new_job\\\"\\nORDER BY \\\"row_count\\\" DESC\\nLIMIT 13;\", \"columns\": [\"major_discipline\", \"last_new_job\", \"row_count\"], \"rows\": [{\"major_discipline\": \"STEM\", \"last_new_job\": \"1\", \"row_count\": 4557}, {\"major_discipline\": \"STEM\", \"last_new_job\": \">4\", \"row_count\": 1730}, {\"major_discipline\": \"STEM\", \"last_new_job\": \"2\", \"row_count\": 1600}, {\"major_discipline\": \"STEM\", \"last_new_job\": \"never\", \"row_count\": 990}, {\"major_discipline\": \"STEM\", \"last_new_job\": \"4\", \"row_count\": 581}, {\"major_discipline\": \"STEM\", \"last_new_job\": \"3\", \"row_count\": 578}, {\"major_discipline\": \"STEM\", \"last_new_job\": \"\", \"row_count\": 208}, {\"major_discipline\": \"Humanities\", \"last_new_job\": \"1\", \"row_count\": 191}, {\"major_discipline\": \"Other\", \"last_new_job\": \"1\", \"row_count\": 116}, {\"major_discipline\": \"Business Degree\", \"last_new_job\": \"1\", \"row_count\": 108}, {\"major_discipline\": \"Humanities\", \"last_new_job\": \">4\", \"row_count\": 92}, {\"major_discipline\": \"Arts\", \"last_new_job\": \"1\", \"row_count\": 87}, {\"major_discipline\": \"No Major\", \"last_new_job\": \"1\", \"row_count\": 76}], \"row_count_returned\": 13, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.37}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..a19f05ed4acb2d6d79a0d607365039a2ac11a620 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/run_manifest.json @@ -0,0 +1,93 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:42:05.848088+00:00", + "ended_at": "2026-05-19T15:42:17.709378+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_97769e99c5051056", + "problem_id": "v2p_m9_c0d3b471062c277c", + "dataset_id": "m9", + "template_id": "tpl_c2_filtered_group_count_2d", + "template_name": "Filtered Two-Dimensional Group Count", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=major_discipline, group_col_2=last_new_job.", + "bindings": { + "group_col": "major_discipline", + "group_col_2": "last_new_job", + "predicate_col": "education_level", + "predicate_op": "=", + "predicate_value": "Graduate", + "top_k": 13, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "group_col_2", + "predicate_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/1", + "binding_index=48" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_97769e99c5051056.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_97769e99c5051056", + "api_calls": 0, + "input_tokens": 14743, + "cached_input_tokens": 12032, + "output_tokens": 590, + "total_tokens": 15333, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11847.5, + "sql_execution_elapsed_ms_total": 9.37, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ef1a458eadc87d3cfda8785ba673dd4b242a34cd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:42:17.698543+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11847.5, "started_at": "2026-05-19T15:42:05.850215+00:00", "ended_at": "2026-05-19T15:42:17.697745+00:00", "prompt_metrics": {"chars": 9632, "bytes_utf8": 9632, "lines": 268, "estimated_tokens": null}, "response_metrics": {"chars": 464, "bytes_utf8": 464, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14743, "cached_input_tokens": 12032, "output_tokens": 590, "reasoning_output_tokens": 468}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"major_discipline\\\", \\\"last_new_job\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m9\\\"\\nWHERE \\\"education_level\\\" = 'Graduate'\\nGROUP BY \\\"major_discipline\\\", \\\"last_new_job\\\"\\nORDER BY \\\"row_count\\\" DESC\\nLIMIT 13;\",\"notes\":\"Uses the requested template with group_col=\\\"major_discipline\\\", group_col_2=\\\"last_new_job\\\", and predicate education_level='Graduate', returning the highest-count graduate slices.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..d9e3bd9871c41b3c5c97898b83ec3cab927329db --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_97769e99c5051056", + "api_calls": 0, + "input_tokens": 14743, + "cached_input_tokens": 12032, + "output_tokens": 590, + "total_tokens": 15333, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11847.5, + "sql_execution_elapsed_ms_total": 9.37, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97769e99c5051056/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..e688778ba2a394fb37e0fb4ed7ea824c289ebd43 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=experience, measure_col=enrollee_id. +Result preview: [{"experience": ">20", "total_measure": 54456108}, {"experience": "5", "total_measure": 24561810}, {"experience": "4", "total_measure": 23932474}, {"experience": "3", "total_measure": 23669243}, {"experience": "6", "total_measure": 20681608}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..49831e5c07d4cd01d6d4bd94733c1e2f69272e76 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_m9_97d9e1b7f3691dce +-- problem_id: v2p_m9_bdf23f7f790c6bc1 +-- realization_mode: agent +-- source_kind: agent +SELECT "experience", SUM(CAST("enrollee_id" AS NUMERIC)) AS total_measure +FROM "m9" +GROUP BY "experience" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c2f3e80c48414ed2f2a315efe1f906b8e26f1e64 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"experience\", SUM(CAST(\"enrollee_id\" AS NUMERIC)) AS total_measure\nFROM \"m9\"\nGROUP BY \"experience\"\nORDER BY total_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"experience\\\", SUM(CAST(\\\"enrollee_id\\\" AS NUMERIC)) AS total_measure\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\"\\nORDER BY total_measure DESC;\", \"columns\": [\"experience\", \"total_measure\"], \"rows\": [{\"experience\": \">20\", \"total_measure\": 54456108}, {\"experience\": \"5\", \"total_measure\": 24561810}, {\"experience\": \"4\", \"total_measure\": 23932474}, {\"experience\": \"3\", \"total_measure\": 23669243}, {\"experience\": \"6\", \"total_measure\": 20681608}, {\"experience\": \"2\", \"total_measure\": 19864312}, {\"experience\": \"7\", \"total_measure\": 17338063}, {\"experience\": \"9\", \"total_measure\": 16457366}, {\"experience\": \"10\", \"total_measure\": 16341566}, {\"experience\": \"8\", \"total_measure\": 13002052}, {\"experience\": \"11\", \"total_measure\": 11045782}, {\"experience\": \"15\", \"total_measure\": 10915167}, {\"experience\": \"1\", \"total_measure\": 9957720}, {\"experience\": \"14\", \"total_measure\": 9299253}, {\"experience\": \"<1\", \"total_measure\": 9290184}, {\"experience\": \"16\", \"total_measure\": 8960468}, {\"experience\": \"12\", \"total_measure\": 7954619}, {\"experience\": \"13\", \"total_measure\": 6671468}, {\"experience\": \"17\", \"total_measure\": 5665127}, {\"experience\": \"19\", \"total_measure\": 5086860}, {\"experience\": \"18\", \"total_measure\": 4726565}, {\"experience\": \"20\", \"total_measure\": 2402446}, {\"experience\": \"\", \"total_measure\": 1017851}], \"row_count_returned\": 23, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 20.79}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..5e809d7d11cf6a7b6848bb7ae5d28eeab0e9981c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:31:03.461177+00:00", + "ended_at": "2026-05-19T15:31:30.903320+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_97d9e1b7f3691dce", + "problem_id": "v2p_m9_bdf23f7f790c6bc1", + "dataset_id": "m9", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=experience, measure_col=enrollee_id.", + "bindings": { + "group_col": "experience", + "measure_col": "enrollee_id", + "top_k": 11, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/2", + "binding_index=6" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_97d9e1b7f3691dce.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_97d9e1b7f3691dce", + "api_calls": 0, + "input_tokens": 14648, + "cached_input_tokens": 13696, + "output_tokens": 636, + "total_tokens": 15284, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 27413.66, + "sql_execution_elapsed_ms_total": 20.79, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7027a3f577f6ffd10aa15ae99102ca2e31d53203 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:31:30.880124+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 27413.66, "started_at": "2026-05-19T15:31:03.464759+00:00", "ended_at": "2026-05-19T15:31:30.878471+00:00", "prompt_metrics": {"chars": 9295, "bytes_utf8": 9295, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 470, "bytes_utf8": 470, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14648, "cached_input_tokens": 13696, "output_tokens": 636, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"experience\\\", SUM(CAST(\\\"enrollee_id\\\" AS NUMERIC)) AS total_measure\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Uses the required grouped numeric sum template with \\\"experience\\\" as the group column. \\\"enrollee_id\\\" is stored as TEXT, so it is cast to NUMERIC for SQLite aggregation; this is syntactically valid, though the measure is identifier-like rather than a business metric.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..e5431bcd5e974f5854db4aa81acdf1e018c2e74d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_97d9e1b7f3691dce", + "api_calls": 0, + "input_tokens": 14648, + "cached_input_tokens": 13696, + "output_tokens": 636, + "total_tokens": 15284, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 27413.66, + "sql_execution_elapsed_ms_total": 20.79, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_97d9e1b7f3691dce/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a672e9db250e6eca2f3c1737a8a9869807885289 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9480, "bytes_utf8": 9480, "lines": 262, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 737, "bytes_utf8": 737, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14703, "cached_input_tokens": 12032, "output_tokens": 473, "reasoning_output_tokens": 287}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..0e802da1c6762436feee618f508cbc35d9081040 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_9971366f73dfa4e0", + "api_calls": 0, + "input_tokens": 14703, + "cached_input_tokens": 12032, + "output_tokens": 473, + "total_tokens": 15176, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12630.45, + "sql_execution_elapsed_ms_total": 48.21, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..e7207fc6543bd52b1f92e1fc7fe01c5c40e9cde2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:44:55.362423+00:00", + "ended_at": "2026-05-19T15:45:07.992910+00:00", + "elapsed_ms": 12630.45, + "prompt_metrics": { + "chars": 9480, + "bytes_utf8": 9480, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1114, + "bytes_utf8": 1114, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 737, + "bytes_utf8": 737, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14703, + "cached_input_tokens": 12032, + "output_tokens": 473, + "reasoning_output_tokens": 287 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..7d29eb0798793445e3b74a37b3c54f05f7717f50 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "primary_family": "tail_rarity_structure", + "portability": "partial", + "sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "required_roles": [ + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=city_development_index.", + "planned_template_id": "tpl_m4_quantile_tail_slice", + "bindings": { + "measure_col": "city_development_index", + "top_k": 14, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..f43a112c9200762ed6e9136a79bad54d1da8b93e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40e9-5b42-7851-988e-35829c99bb5a"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH buckets AS (\\n SELECT CAST(\\\"city_development_index\\\" AS REAL) AS \\\"city_development_index\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"city_development_index\\\" AS REAL) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n)\\nSELECT \\\"city_development_index\\\"\\nFROM buckets\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"city_development_index\\\" DESC;\",\"notes\":\"Applied the requested Quantile Tail Slice template with measure_col bound to city_development_index. Cast to REAL because the column is stored as TEXT in SQLite, and excluded empty values so the top decile reflects numeric tail values.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14703,"cached_input_tokens":12032,"output_tokens":473,"reasoning_output_tokens":287}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..5a2cb8767435306320439e0a42c37d7d738caf0e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_quantile_tail_slice\nWITH buckets AS (\n SELECT CAST(\"city_development_index\" AS REAL) AS \"city_development_index\",\n NTILE(10) OVER (ORDER BY CAST(\"city_development_index\" AS REAL) DESC) AS \"tail_bucket\"\n FROM \"m9\"\n WHERE \"city_development_index\" IS NOT NULL\n AND \"city_development_index\" <> ''\n)\nSELECT \"city_development_index\"\nFROM buckets\nWHERE \"tail_bucket\" = 1\nORDER BY \"city_development_index\" DESC;","notes":"Applied the requested Quantile Tail Slice template with measure_col bound to city_development_index. Cast to REAL because the column is stored as TEXT in SQLite, and excluded empty values so the top decile reflects numeric tail values."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9971366f73dfa4e0/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..356b047632e682937534566506133e79e6333b9b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=gender, condition_col=relevent_experience. +Result preview: [{"gender": "Other", "condition_rate": 0.4397905759162304}, {"gender": "", "condition_rate": 0.3657941437444543}, {"gender": "Female", "condition_rate": 0.2964458804523425}, {"gender": "Male", "condition_rate": 0.24703123818168066}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..da17de272eb21820a4898d21068d8ec000e8b59d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_m9_9b7e8c4cff94b0a1 +-- problem_id: v2p_m9_edfde1818c947604 +-- realization_mode: agent +-- source_kind: agent +SELECT "gender", + AVG(CASE WHEN "relevent_experience" = 'No relevent experience' THEN 1 ELSE 0 END) AS "condition_rate" +FROM "m9" +GROUP BY "gender" +ORDER BY "condition_rate" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9ab27d8f915bf01cbfd0fc0d58ad4ab74b0b27cf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"gender\",\n AVG(CASE WHEN \"relevent_experience\" = 'No relevent experience' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"m9\"\nGROUP BY \"gender\"\nORDER BY \"condition_rate\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"gender\\\",\\n AVG(CASE WHEN \\\"relevent_experience\\\" = 'No relevent experience' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"gender\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\", \"columns\": [\"gender\", \"condition_rate\"], \"rows\": [{\"gender\": \"Other\", \"condition_rate\": 0.4397905759162304}, {\"gender\": \"\", \"condition_rate\": 0.3657941437444543}, {\"gender\": \"Female\", \"condition_rate\": 0.2964458804523425}, {\"gender\": \"Male\", \"condition_rate\": 0.24703123818168066}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 21.76}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..bfe30e9856af444916ba70257c2013e5ecf81252 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:59:45.751470+00:00", + "ended_at": "2026-05-19T15:59:56.085611+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_9b7e8c4cff94b0a1", + "problem_id": "v2p_m9_edfde1818c947604", + "dataset_id": "m9", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role within_group_proportion. Focus on group_col=gender, condition_col=relevent_experience.", + "bindings": { + "group_col": "gender", + "condition_col": "relevent_experience", + "condition_value": "No relevent experience", + "positive_value": "Has relevent experience", + "negative_value": "No relevent experience", + "top_k": 17, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=2/2", + "binding_index=97" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 2, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_9b7e8c4cff94b0a1.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_9b7e8c4cff94b0a1", + "api_calls": 0, + "input_tokens": 14720, + "cached_input_tokens": 12032, + "output_tokens": 452, + "total_tokens": 15172, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10303.23, + "sql_execution_elapsed_ms_total": 21.76, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..99f81d6c54c49d81daadd353a81a6b677ceae69b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:59:56.059897+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10303.23, "started_at": "2026-05-19T15:59:45.754884+00:00", "ended_at": "2026-05-19T15:59:56.058167+00:00", "prompt_metrics": {"chars": 9606, "bytes_utf8": 9606, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 508, "bytes_utf8": 508, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14720, "cached_input_tokens": 12032, "output_tokens": 452, "reasoning_output_tokens": 319}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"gender\\\",\\n AVG(CASE WHEN \\\"relevent_experience\\\" = 'No relevent experience' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"gender\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Uses the planned Grouped Condition Rate template with \\\"gender\\\" as the group and the within-group proportion of rows where \\\"relevent_experience\\\" is 'No relevent experience'. Empty gender values, if present, will appear as their own group.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..1db9b032a56abc0533760208b34089a04e7ca47e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_9b7e8c4cff94b0a1", + "api_calls": 0, + "input_tokens": 14720, + "cached_input_tokens": 12032, + "output_tokens": 452, + "total_tokens": 15172, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10303.23, + "sql_execution_elapsed_ms_total": 21.76, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9b7e8c4cff94b0a1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..0b6b9195b5866f1c383508bbaadc41e89a6cdb5e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=gender, measure_col=city_development_index. +Result preview: [{"gender": "Male", "total_measure": 11093.115}, {"gender": "", "total_measure": 3574.709}, {"gender": "Female", "total_measure": 1045.788}, {"gender": "Other", "total_measure": 165.458}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..5c48ed8d742fc754adeed44bca1251432dc2eb71 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_conditional_contrast +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_m9_9be8234aca961fde +-- problem_id: v2p_m9_39fd41c86fa5d183 +-- realization_mode: agent +-- source_kind: agent +SELECT "gender", SUM(CAST("city_development_index" AS REAL)) AS "total_measure" +FROM "m9" +GROUP BY "gender" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e00dff1bad8cdfdf83644f24046bcd11ced5f40b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum.\nSELECT \"gender\", SUM(CAST(\"city_development_index\" AS REAL)) AS \"total_measure\"\nFROM \"m9\"\nGROUP BY \"gender\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum.\\nSELECT \\\"gender\\\", SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"gender\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"gender\", \"total_measure\"], \"rows\": [{\"gender\": \"Male\", \"total_measure\": 11093.115}, {\"gender\": \"\", \"total_measure\": 3574.709}, {\"gender\": \"Female\", \"total_measure\": 1045.788}, {\"gender\": \"Other\", \"total_measure\": 165.458}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 14.95}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..141d4558c335ee3166697366798787239c60a34e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:28:52.248579+00:00", + "ended_at": "2026-05-19T15:29:06.288593+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_9be8234aca961fde", + "problem_id": "v2p_m9_39fd41c86fa5d183", + "dataset_id": "m9", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_conditional_contrast", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=gender, measure_col=city_development_index.", + "bindings": { + "group_col": "gender", + "measure_col": "city_development_index", + "top_k": 16, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=2/2", + "binding_index=1" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 2, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_9be8234aca961fde.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_9be8234aca961fde", + "api_calls": 0, + "input_tokens": 14648, + "cached_input_tokens": 12032, + "output_tokens": 428, + "total_tokens": 15076, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14019.11, + "sql_execution_elapsed_ms_total": 14.95, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1013610a92887c4533209d2d6836d3f3f3daa3e8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:29:06.271554+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14019.11, "started_at": "2026-05-19T15:28:52.250947+00:00", "ended_at": "2026-05-19T15:29:06.270088+00:00", "prompt_metrics": {"chars": 9307, "bytes_utf8": 9307, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 383, "bytes_utf8": 383, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14648, "cached_input_tokens": 12032, "output_tokens": 428, "reasoning_output_tokens": 326}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum.\\nSELECT \\\"gender\\\", SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"gender\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Used the required grouped numeric sum template with \\\"gender\\\" as the grouping column and cast \\\"city_development_index\\\" from TEXT to REAL so SQLite can sum it numerically.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..d1b5e883c8f895895d69afdc80410130602426cc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_9be8234aca961fde", + "api_calls": 0, + "input_tokens": 14648, + "cached_input_tokens": 12032, + "output_tokens": 428, + "total_tokens": 15076, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14019.11, + "sql_execution_elapsed_ms_total": 14.95, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9be8234aca961fde/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..cce364fc58ec74048d9bf664c51d412479bfdd94 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=major_discipline, condition_col=relevent_experience. +Result preview: [{"major_discipline": "STEM", "condition_ratio": 3.722059302704464}, {"major_discipline": "Arts", "condition_ratio": 3.3620689655172415}, {"major_discipline": "No Major", "condition_ratio": 2.328358208955224}, {"major_discipline": "Humanities", "condition_ratio": 2.2794117647058822}, {"major_discipline": "Other", "condition_ratio": 2.175}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..76f818f1613a994b277d8751e6a6357eb514d7c6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_m9_9c716372c8e53d66 +-- problem_id: v2p_m9_12773869fbbe36b2 +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT + "major_discipline", + SUM(CASE WHEN "relevent_experience" = 'Has relevent experience' THEN 1 ELSE 0 END) AS "numerator_count", + SUM(CASE WHEN "relevent_experience" = 'No relevent experience' THEN 1 ELSE 0 END) AS "denominator_count" + FROM "m9" + GROUP BY "major_discipline" +) +SELECT + "major_discipline", + CAST("numerator_count" AS FLOAT) / NULLIF("denominator_count", 0) AS "condition_ratio" +FROM "grouped" +ORDER BY "condition_ratio" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7ed3c2fe205a61f64c56363eb9ed33b452519d99 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_ratio_two_conditions\nWITH \"grouped\" AS (\n SELECT\n \"major_discipline\",\n SUM(CASE WHEN \"relevent_experience\" = 'Has relevent experience' THEN 1 ELSE 0 END) AS \"numerator_count\",\n SUM(CASE WHEN \"relevent_experience\" = 'No relevent experience' THEN 1 ELSE 0 END) AS \"denominator_count\"\n FROM \"m9\"\n GROUP BY \"major_discipline\"\n)\nSELECT\n \"major_discipline\",\n CAST(\"numerator_count\" AS FLOAT) / NULLIF(\"denominator_count\", 0) AS \"condition_ratio\"\nFROM \"grouped\"\nORDER BY \"condition_ratio\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"major_discipline\\\",\\n SUM(CASE WHEN \\\"relevent_experience\\\" = 'Has relevent experience' THEN 1 ELSE 0 END) AS \\\"numerator_count\\\",\\n SUM(CASE WHEN \\\"relevent_experience\\\" = 'No relevent experience' THEN 1 ELSE 0 END) AS \\\"denominator_count\\\"\\n FROM \\\"m9\\\"\\n GROUP BY \\\"major_discipline\\\"\\n)\\nSELECT\\n \\\"major_discipline\\\",\\n CAST(\\\"numerator_count\\\" AS FLOAT) / NULLIF(\\\"denominator_count\\\", 0) AS \\\"condition_ratio\\\"\\nFROM \\\"grouped\\\"\\nORDER BY \\\"condition_ratio\\\" DESC;\", \"columns\": [\"major_discipline\", \"condition_ratio\"], \"rows\": [{\"major_discipline\": \"STEM\", \"condition_ratio\": 3.722059302704464}, {\"major_discipline\": \"Arts\", \"condition_ratio\": 3.3620689655172415}, {\"major_discipline\": \"No Major\", \"condition_ratio\": 2.328358208955224}, {\"major_discipline\": \"Humanities\", \"condition_ratio\": 2.2794117647058822}, {\"major_discipline\": \"Other\", \"condition_ratio\": 2.175}, {\"major_discipline\": \"Business Degree\", \"condition_ratio\": 1.9727272727272727}, {\"major_discipline\": \"\", \"condition_ratio\": 0.6185270425776754}], \"row_count_returned\": 7, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 8.58}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e46874fae40c048a21117d8c0535036b6c5b4de0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:41:12.528108+00:00", + "ended_at": "2026-05-19T15:41:26.718607+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_9c716372c8e53d66", + "problem_id": "v2p_m9_12773869fbbe36b2", + "dataset_id": "m9", + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "contrastive_conditional_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=major_discipline, condition_col=relevent_experience.", + "bindings": { + "group_col": "major_discipline", + "condition_col": "relevent_experience", + "condition_value": "Has relevent experience", + "positive_value": "Has relevent experience", + "negative_value": "No relevent experience", + "top_k": 11, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/1", + "binding_index=41" + ], + "template_selection_mode": "rule", + "selected_template_rank": 4, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_9c716372c8e53d66.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_9c716372c8e53d66", + "api_calls": 0, + "input_tokens": 14871, + "cached_input_tokens": 12032, + "output_tokens": 687, + "total_tokens": 15558, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14177.5, + "sql_execution_elapsed_ms_total": 8.58, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..16e561d4395ca4f78a91d9076235bbf2c9da1f79 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:41:26.708569+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14177.5, "started_at": "2026-05-19T15:41:12.530224+00:00", "ended_at": "2026-05-19T15:41:26.707758+00:00", "prompt_metrics": {"chars": 10189, "bytes_utf8": 10189, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 797, "bytes_utf8": 797, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14871, "cached_input_tokens": 12032, "output_tokens": 687, "reasoning_output_tokens": 469}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"major_discipline\\\",\\n SUM(CASE WHEN \\\"relevent_experience\\\" = 'Has relevent experience' THEN 1 ELSE 0 END) AS \\\"numerator_count\\\",\\n SUM(CASE WHEN \\\"relevent_experience\\\" = 'No relevent experience' THEN 1 ELSE 0 END) AS \\\"denominator_count\\\"\\n FROM \\\"m9\\\"\\n GROUP BY \\\"major_discipline\\\"\\n)\\nSELECT\\n \\\"major_discipline\\\",\\n CAST(\\\"numerator_count\\\" AS FLOAT) / NULLIF(\\\"denominator_count\\\", 0) AS \\\"condition_ratio\\\"\\nFROM \\\"grouped\\\"\\nORDER BY \\\"condition_ratio\\\" DESC;\",\"notes\":\"Uses the planned grouped ratio template with group_col=\\\"major_discipline\\\" and condition_col=\\\"relevent_experience\\\", comparing 'Has relevent experience' to 'No relevent experience'.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..6ddd397d57bedf2345e14318a472af18aaae62a7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_9c716372c8e53d66", + "api_calls": 0, + "input_tokens": 14871, + "cached_input_tokens": 12032, + "output_tokens": 687, + "total_tokens": 15558, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14177.5, + "sql_execution_elapsed_ms_total": 8.58, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9c716372c8e53d66/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..dbc97c88ca42f0c30d454b7d91c91d25b40389a9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=city_development_index, measure_col=enrollee_id. +Result preview: [{"city_development_index": "0.92", "group_value": 88549363.0}, {"city_development_index": "0.624", "group_value": 48522501.0}, {"city_development_index": "0.91", "group_value": 26141445.0}, {"city_development_index": "0.9259999999999999", "group_value": 22746055.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..21c44b3323d9fe54483857d9703f38e83db44bc8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/generated_sql.sql @@ -0,0 +1,35 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_m9_9d6bb29cc5632186 +-- problem_id: v2p_m9_57bddf78ca6eea19 +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT + "city_development_index", + SUM(CAST("enrollee_id" AS REAL)) AS "group_value" + FROM "m9" + WHERE "city_development_index" IS NOT NULL + AND "city_development_index" <> '' + AND "enrollee_id" IS NOT NULL + AND "enrollee_id" <> '' + GROUP BY "city_development_index" +), +"total" AS ( + SELECT SUM("group_value") AS "total_value" + FROM "grouped" +) +SELECT + g."city_development_index", + g."group_value" +FROM "grouped" AS g +CROSS JOIN "total" AS t +WHERE g."group_value" > t."total_value" * 0.05 +ORDER BY g."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b2052fe8e2e5dbc60b9a72302d00c0231e1ce649 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n SELECT\n \"city_development_index\",\n SUM(CAST(\"enrollee_id\" AS REAL)) AS \"group_value\"\n FROM \"m9\"\n WHERE \"city_development_index\" IS NOT NULL\n AND \"city_development_index\" <> ''\n AND \"enrollee_id\" IS NOT NULL\n AND \"enrollee_id\" <> ''\n GROUP BY \"city_development_index\"\n),\n\"total\" AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM \"grouped\"\n)\nSELECT\n g.\"city_development_index\",\n g.\"group_value\"\nFROM \"grouped\" AS g\nCROSS JOIN \"total\" AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.05\nORDER BY g.\"group_value\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"city_development_index\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\n GROUP BY \\\"city_development_index\\\"\\n),\\n\\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT\\n g.\\\"city_development_index\\\",\\n g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.05\\nORDER BY g.\\\"group_value\\\" DESC;\", \"columns\": [\"city_development_index\", \"group_value\"], \"rows\": [{\"city_development_index\": \"0.92\", \"group_value\": 88549363.0}, {\"city_development_index\": \"0.624\", \"group_value\": 48522501.0}, {\"city_development_index\": \"0.91\", \"group_value\": 26141445.0}, {\"city_development_index\": \"0.9259999999999999\", \"group_value\": 22746055.0}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 14.29}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..c206dba099e82c8ec67de9d0a273f41a801ece90 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:46:04.160095+00:00", + "ended_at": "2026-05-19T15:46:18.396779+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_9d6bb29cc5632186", + "problem_id": "v2p_m9_57bddf78ca6eea19", + "dataset_id": "m9", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=city_development_index, measure_col=enrollee_id.", + "bindings": { + "group_col": "city_development_index", + "measure_col": "enrollee_id", + "top_k": 17, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=2/2", + "binding_index=72" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 1, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_9d6bb29cc5632186.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_9d6bb29cc5632186", + "api_calls": 0, + "input_tokens": 14792, + "cached_input_tokens": 12032, + "output_tokens": 762, + "total_tokens": 15554, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14217.25, + "sql_execution_elapsed_ms_total": 14.29, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..511595b1bdd69f309ab974d108f4b62b4243964d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:46:18.380815+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14217.25, "started_at": "2026-05-19T15:46:04.162638+00:00", "ended_at": "2026-05-19T15:46:18.379920+00:00", "prompt_metrics": {"chars": 9876, "bytes_utf8": 9876, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 932, "bytes_utf8": 932, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14792, "cached_input_tokens": 12032, "output_tokens": 762, "reasoning_output_tokens": 494}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"city_development_index\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\n GROUP BY \\\"city_development_index\\\"\\n),\\n\\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT\\n g.\\\"city_development_index\\\",\\n g.\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS g\\nCROSS JOIN \\\"total\\\" AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.05\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Uses the planned relative-to-total threshold template with \\\"city_development_index\\\" as the grouping column and a numeric cast of \\\"enrollee_id\\\" as the measure. Blank and null values are filtered out to keep the grouped view stable.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..76dff7c1d96940b6cc59441d420fac97a70b1c0a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_9d6bb29cc5632186", + "api_calls": 0, + "input_tokens": 14792, + "cached_input_tokens": 12032, + "output_tokens": 762, + "total_tokens": 15554, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14217.25, + "sql_execution_elapsed_ms_total": 14.29, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_9d6bb29cc5632186/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..128985752d54ee1c34d41a163902476984b2b553 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=major_discipline. +Result preview: [{"major_discipline": "No Major", "support": 223}, {"major_discipline": "Arts", "support": 253}, {"major_discipline": "Business Degree", "support": 327}, {"major_discipline": "Other", "support": 381}, {"major_discipline": "Humanities", "support": 669}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..6c7c126964a87b2d75766451844491964cb950b1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/generated_sql.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_m9_a146e3f95ebe57d9 +-- problem_id: v2p_m9_45cae1b64b0db0fe +-- realization_mode: agent +-- source_kind: agent +SELECT + "major_discipline", + COUNT(*) AS "support" +FROM "m9" +GROUP BY "major_discipline" +ORDER BY "support" ASC, "major_discipline" +LIMIT 10; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6a7a9bad342bf5f190fa6419f376e4f5a4110075 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n \"major_discipline\",\n COUNT(*) AS \"support\"\nFROM \"m9\"\nGROUP BY \"major_discipline\"\nORDER BY \"support\" ASC, \"major_discipline\"\nLIMIT 10;", "result": "{\"query\": \"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"major_discipline\\\",\\n COUNT(*) AS \\\"support\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"major_discipline\\\"\\nORDER BY \\\"support\\\" ASC, \\\"major_discipline\\\"\\nLIMIT 10;\", \"columns\": [\"major_discipline\", \"support\"], \"rows\": [{\"major_discipline\": \"No Major\", \"support\": 223}, {\"major_discipline\": \"Arts\", \"support\": 253}, {\"major_discipline\": \"Business Degree\", \"support\": 327}, {\"major_discipline\": \"Other\", \"support\": 381}, {\"major_discipline\": \"Humanities\", \"support\": 669}, {\"major_discipline\": \"\", \"support\": 2813}, {\"major_discipline\": \"STEM\", \"support\": 14492}], \"row_count_returned\": 7, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 8.37}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..586bb83bbcab067ae535c439da5033405e021121 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:05:35.431245+00:00", + "ended_at": "2026-05-19T16:05:48.117471+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_a146e3f95ebe57d9", + "problem_id": "v2p_m9_45cae1b64b0db0fe", + "dataset_id": "m9", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=major_discipline.", + "bindings": { + "group_col": "major_discipline", + "top_k": 10, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=1/2", + "binding_index=125" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_a146e3f95ebe57d9.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_a146e3f95ebe57d9", + "api_calls": 0, + "input_tokens": 14656, + "cached_input_tokens": 13696, + "output_tokens": 285, + "total_tokens": 14941, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11669.21, + "sql_execution_elapsed_ms_total": 8.37, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..191f74e6ff26d3375d29e602a1037b17e32c4e69 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:05:38.362726+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2927.68, "started_at": "2026-05-19T16:05:35.433649+00:00", "ended_at": "2026-05-19T16:05:38.361363+00:00", "prompt_metrics": {"chars": 9286, "bytes_utf8": 9286, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fc-4769-72d1-b199-b880bf10fa93\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:05:48.107264+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8741.53, "started_at": "2026-05-19T16:05:39.363952+00:00", "ended_at": "2026-05-19T16:05:48.105520+00:00", "prompt_metrics": {"chars": 9286, "bytes_utf8": 9286, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 393, "bytes_utf8": 393, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14656, "cached_input_tokens": 13696, "output_tokens": 285, "reasoning_output_tokens": 178}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"major_discipline\\\",\\n COUNT(*) AS \\\"support\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"major_discipline\\\"\\nORDER BY \\\"support\\\" ASC, \\\"major_discipline\\\"\\nLIMIT 10;\",\"notes\":\"Uses the Low-Support Group Count template with group_col bound to \\\"major_discipline\\\" and top_k=10 to return the least-supported major_discipline groups.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..0a3f058738665bd65a7a17e6ee6e3bc8ae9f9ecd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_a146e3f95ebe57d9", + "api_calls": 0, + "input_tokens": 14656, + "cached_input_tokens": 13696, + "output_tokens": 285, + "total_tokens": 14941, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11669.21, + "sql_execution_elapsed_ms_total": 8.37, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a146e3f95ebe57d9/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..fdf69649f6bd0c3ba4943a2d66c6c6b4230cd968 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=major_discipline, group_col_2=training_hours. +Result preview: [{"major_discipline": "STEM", "training_hours": "28", "row_count": 248}, {"major_discipline": "STEM", "training_hours": "18", "row_count": 224}, {"major_discipline": "STEM", "training_hours": "24", "row_count": 223}, {"major_discipline": "STEM", "training_hours": "12", "row_count": 211}, {"major_discipline": "STEM", "training_hours": "22", "row_count": 209}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..63f794987a38affdcdec0590916d984e74ee7048 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: count_distribution +-- template_id: tpl_c2_filtered_group_count_2d +-- query_record_id: v2q_m9_a20d7d5089630fd8 +-- problem_id: v2p_m9_450169c249142504 +-- realization_mode: agent +-- source_kind: agent +SELECT "major_discipline", "training_hours", COUNT(*) AS row_count +FROM "m9" +WHERE "major_discipline" = 'STEM' +GROUP BY "major_discipline", "training_hours" +ORDER BY row_count DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c7482a4af2df6b707e195930dbcf3240d941479e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_c2_filtered_group_count_2d\nSELECT \"major_discipline\", \"training_hours\", COUNT(*) AS row_count\nFROM \"m9\"\nWHERE \"major_discipline\" = 'STEM'\nGROUP BY \"major_discipline\", \"training_hours\"\nORDER BY row_count DESC;", "result": "{\"query\": \"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"major_discipline\\\", \\\"training_hours\\\", COUNT(*) AS row_count\\nFROM \\\"m9\\\"\\nWHERE \\\"major_discipline\\\" = 'STEM'\\nGROUP BY \\\"major_discipline\\\", \\\"training_hours\\\"\\nORDER BY row_count DESC;\", \"columns\": [\"major_discipline\", \"training_hours\", \"row_count\"], \"rows\": [{\"major_discipline\": \"STEM\", \"training_hours\": \"28\", \"row_count\": 248}, {\"major_discipline\": \"STEM\", \"training_hours\": \"18\", \"row_count\": 224}, {\"major_discipline\": \"STEM\", \"training_hours\": \"24\", \"row_count\": 223}, {\"major_discipline\": \"STEM\", \"training_hours\": \"12\", \"row_count\": 211}, {\"major_discipline\": \"STEM\", \"training_hours\": \"22\", \"row_count\": 209}, {\"major_discipline\": \"STEM\", \"training_hours\": \"50\", \"row_count\": 209}, {\"major_discipline\": \"STEM\", \"training_hours\": \"20\", \"row_count\": 206}, {\"major_discipline\": \"STEM\", \"training_hours\": \"17\", \"row_count\": 201}, {\"major_discipline\": \"STEM\", \"training_hours\": \"6\", \"row_count\": 200}, {\"major_discipline\": \"STEM\", \"training_hours\": \"21\", \"row_count\": 195}, {\"major_discipline\": \"STEM\", \"training_hours\": \"23\", \"row_count\": 194}, {\"major_discipline\": \"STEM\", \"training_hours\": \"26\", \"row_count\": 193}, {\"major_discipline\": \"STEM\", \"training_hours\": \"10\", \"row_count\": 191}, {\"major_discipline\": \"STEM\", \"training_hours\": \"11\", \"row_count\": 189}, {\"major_discipline\": \"STEM\", \"training_hours\": \"34\", \"row_count\": 185}, {\"major_discipline\": \"STEM\", \"training_hours\": \"9\", \"row_count\": 185}, {\"major_discipline\": \"STEM\", \"training_hours\": \"42\", \"row_count\": 181}, {\"major_discipline\": \"STEM\", \"training_hours\": \"56\", \"row_count\": 179}, {\"major_discipline\": \"STEM\", \"training_hours\": \"15\", \"row_count\": 172}, {\"major_discipline\": \"STEM\", \"training_hours\": \"8\", \"row_count\": 170}, {\"major_discipline\": \"STEM\", \"training_hours\": \"36\", \"row_count\": 169}, {\"major_discipline\": \"STEM\", \"training_hours\": \"4\", \"row_count\": 168}, {\"major_discipline\": \"STEM\", \"training_hours\": \"7\", \"row_count\": 168}, {\"major_discipline\": \"STEM\", \"training_hours\": \"14\", \"row_count\": 167}, {\"major_discipline\": \"STEM\", \"training_hours\": \"46\", \"row_count\": 166}, {\"major_discipline\": \"STEM\", \"training_hours\": \"48\", \"row_count\": 165}, {\"major_discipline\": \"STEM\", \"training_hours\": \"44\", \"row_count\": 162}, {\"major_discipline\": \"STEM\", \"training_hours\": \"16\", \"row_count\": 159}, {\"major_discipline\": \"STEM\", \"training_hours\": \"13\", \"row_count\": 154}, {\"major_discipline\": \"STEM\", \"training_hours\": \"32\", \"row_count\": 153}, {\"major_discipline\": \"STEM\", \"training_hours\": \"25\", \"row_count\": 150}, {\"major_discipline\": \"STEM\", \"training_hours\": \"31\", \"row_count\": 149}, {\"major_discipline\": \"STEM\", \"training_hours\": \"40\", \"row_count\": 148}, {\"major_discipline\": \"STEM\", \"training_hours\": \"52\", \"row_count\": 146}, {\"major_discipline\": \"STEM\", \"training_hours\": \"55\", \"row_count\": 144}, {\"major_discipline\": \"STEM\", \"training_hours\": \"30\", \"row_count\": 141}, {\"major_discipline\": \"STEM\", \"training_hours\": \"29\", \"row_count\": 140}, {\"major_discipline\": \"STEM\", \"training_hours\": \"39\", \"row_count\": 137}, {\"major_discipline\": \"STEM\", \"training_hours\": \"43\", \"row_count\": 137}, {\"major_discipline\": \"STEM\", \"training_hours\": \"19\", \"row_count\": 136}, {\"major_discipline\": \"STEM\", \"training_hours\": \"51\", \"row_count\": 134}, {\"major_discipline\": \"STEM\", \"training_hours\": \"45\", \"row_count\": 129}, {\"major_discipline\": \"STEM\", \"training_hours\": \"54\", \"row_count\": 127}, {\"major_discipline\": \"STEM\", \"training_hours\": \"47\", \"row_count\": 125}, {\"major_discipline\": \"STEM\", \"training_hours\": \"78\", \"row_count\": 121}, {\"major_discipline\": \"STEM\", \"training_hours\": \"37\", \"row_count\": 119}, {\"major_discipline\": \"STEM\", \"training_hours\": \"35\", \"row_count\": 116}, {\"major_discipline\": \"STEM\", \"training_hours\": \"72\", \"row_count\": 116}, {\"major_discipline\": \"STEM\", \"training_hours\": \"80\", \"row_count\": 110}, {\"major_discipline\": \"STEM\", \"training_hours\": \"33\", \"row_count\": 109}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 13.18}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..8df836e99b007e7e38509af4de0147724b2a70ba --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/run_manifest.json @@ -0,0 +1,93 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:42:17.709908+00:00", + "ended_at": "2026-05-19T15:42:31.322948+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_a20d7d5089630fd8", + "problem_id": "v2p_m9_450169c249142504", + "dataset_id": "m9", + "template_id": "tpl_c2_filtered_group_count_2d", + "template_name": "Filtered Two-Dimensional Group Count", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=major_discipline, group_col_2=training_hours.", + "bindings": { + "group_col": "major_discipline", + "group_col_2": "training_hours", + "predicate_col": "major_discipline", + "predicate_op": "=", + "predicate_value": "STEM", + "top_k": 14, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "group_col_2", + "predicate_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/1", + "binding_index=49" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_a20d7d5089630fd8.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_a20d7d5089630fd8", + "api_calls": 0, + "input_tokens": 14742, + "cached_input_tokens": 13696, + "output_tokens": 464, + "total_tokens": 15206, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13595.62, + "sql_execution_elapsed_ms_total": 13.18, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..17e6ec87648bc701c90aee7c2b7a19d182426753 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:42:31.308200+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13595.62, "started_at": "2026-05-19T15:42:17.711691+00:00", "ended_at": "2026-05-19T15:42:31.307336+00:00", "prompt_metrics": {"chars": 9628, "bytes_utf8": 9628, "lines": 268, "estimated_tokens": null}, "response_metrics": {"chars": 437, "bytes_utf8": 437, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14742, "cached_input_tokens": 13696, "output_tokens": 464, "reasoning_output_tokens": 350}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d\\nSELECT \\\"major_discipline\\\", \\\"training_hours\\\", COUNT(*) AS row_count\\nFROM \\\"m9\\\"\\nWHERE \\\"major_discipline\\\" = 'STEM'\\nGROUP BY \\\"major_discipline\\\", \\\"training_hours\\\"\\nORDER BY row_count DESC;\",\"notes\":\"Uses the requested filtered two-dimensional group count template with \\\"major_discipline\\\" and \\\"training_hours\\\", restricted to rows where \\\"major_discipline\\\" is 'STEM'.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..c2c286a0b4ef340c23482be6a8bd39c9a0891a17 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_a20d7d5089630fd8", + "api_calls": 0, + "input_tokens": 14742, + "cached_input_tokens": 13696, + "output_tokens": 464, + "total_tokens": 15206, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13595.62, + "sql_execution_elapsed_ms_total": 13.18, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a20d7d5089630fd8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0048a44763aeca56c86f8a848821aad62aaee392 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 10102, "bytes_utf8": 10102, "lines": 267, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 750, "bytes_utf8": 750, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14851, "cached_input_tokens": 12032, "output_tokens": 490, "reasoning_output_tokens": 303}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..c8913f4aa700023c58ed10b214374b8eb0c9ab48 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_a2d687442580ddb8", + "api_calls": 0, + "input_tokens": 14851, + "cached_input_tokens": 12032, + "output_tokens": 490, + "total_tokens": 15341, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 19936.68, + "sql_execution_elapsed_ms_total": 10.41, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..c1b20169d0fca59469e45008d7fa5f8792c00547 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:40:52.577856+00:00", + "ended_at": "2026-05-19T15:41:12.514562+00:00", + "elapsed_ms": 19936.68, + "prompt_metrics": { + "chars": 10102, + "bytes_utf8": 10102, + "lines": 267, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 2118, + "bytes_utf8": 2118, + "lines": 7, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 750, + "bytes_utf8": 750, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14851, + "cached_input_tokens": 12032, + "output_tokens": 490, + "reasoning_output_tokens": 303 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..cbed7f0f378a3188a2724eda46cb1f8e15ea972f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,267 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=education_level, condition_col=gender.", + "planned_template_id": "tpl_m4_group_ratio_two_conditions", + "bindings": { + "group_col": "education_level", + "condition_col": "gender", + "condition_value": "Male", + "positive_value": "Male", + "negative_value": "", + "top_k": 10, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..1ae8c0cf345474bad85c69c7418efa49cb6a776d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,7 @@ +{"type":"thread.started","thread_id":"019e40e5-a6fb-7970-89fd-bc4de4cd467f"} +{"type":"turn.started"} +{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1995977, Requested 15486. Please try again in 343ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"error","message":"Reconnecting... 3/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1995388, Requested 15486. Please try again in 326ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"error","message":"Reconnecting... 4/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1995808, Requested 15486. Please try again in 338ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"education_level\\\",\\n SUM(CASE WHEN \\\"gender\\\" = 'Male' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"gender\\\" = '' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"m9\\\"\\n GROUP BY \\\"education_level\\\"\\n)\\nSELECT \\\"education_level\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Uses the planned grouped-ratio template with group_col=\\\"education_level\\\" and condition_col=\\\"gender\\\", computing the ratio of 'Male' rows to rows where gender is the empty string within each education level. NULLIF prevents division-by-zero.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14851,"cached_input_tokens":12032,"output_tokens":490,"reasoning_output_tokens":303}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..c46f2a0e53ef44229ddcc1fc4332632c39365e40 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n SELECT \"education_level\",\n SUM(CASE WHEN \"gender\" = 'Male' THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN \"gender\" = '' THEN 1 ELSE 0 END) AS denominator_count\n FROM \"m9\"\n GROUP BY \"education_level\"\n)\nSELECT \"education_level\",\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;","notes":"Uses the planned grouped-ratio template with group_col=\"education_level\" and condition_col=\"gender\", computing the ratio of 'Male' rows to rows where gender is the empty string within each education level. NULLIF prevents division-by-zero."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a2d687442580ddb8/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..51295e1aadd058cd61d1b0caeaa25c4a4f2f4ad1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=company_type, measure_col=training_hours. +Result preview: [{"company_type": "Pvt Ltd", "group_value": 640827.0}, {"company_type": "Funded Startup", "group_value": 67064.0}, {"company_type": "Public Sector", "group_value": 59258.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..5b9faa76a834496d3f544737832a7704f6e8348c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/generated_sql.sql @@ -0,0 +1,33 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_m9_a324887aa577ef52 +-- problem_id: v2p_m9_85349abb956d915a +-- realization_mode: agent +-- source_kind: agent +WITH "grouped" AS ( + SELECT + "company_type", + SUM(CAST("training_hours" AS REAL)) AS "group_value" + FROM "m9" + WHERE TRIM(COALESCE("company_type", '')) <> '' + AND TRIM(COALESCE("training_hours", '')) <> '' + GROUP BY "company_type" +), +"total" AS ( + SELECT SUM("group_value") AS "total_value" + FROM "grouped" +) +SELECT + "g"."company_type", + "g"."group_value" +FROM "grouped" AS "g" +CROSS JOIN "total" AS "t" +WHERE "g"."group_value" > "t"."total_value" * 0.05 +ORDER BY "g"."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0afc0b2622820a094d6733ff594dcf376e1ba6eb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH \"grouped\" AS (\n SELECT\n \"company_type\",\n SUM(CAST(\"training_hours\" AS REAL)) AS \"group_value\"\n FROM \"m9\"\n WHERE TRIM(COALESCE(\"company_type\", '')) <> ''\n AND TRIM(COALESCE(\"training_hours\", '')) <> ''\n GROUP BY \"company_type\"\n),\n\"total\" AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM \"grouped\"\n)\nSELECT\n \"g\".\"company_type\",\n \"g\".\"group_value\"\nFROM \"grouped\" AS \"g\"\nCROSS JOIN \"total\" AS \"t\"\nWHERE \"g\".\"group_value\" > \"t\".\"total_value\" * 0.05\nORDER BY \"g\".\"group_value\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"company_type\\\",\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n WHERE TRIM(COALESCE(\\\"company_type\\\", '')) <> ''\\n AND TRIM(COALESCE(\\\"training_hours\\\", '')) <> ''\\n GROUP BY \\\"company_type\\\"\\n),\\n\\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT\\n \\\"g\\\".\\\"company_type\\\",\\n \\\"g\\\".\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS \\\"g\\\"\\nCROSS JOIN \\\"total\\\" AS \\\"t\\\"\\nWHERE \\\"g\\\".\\\"group_value\\\" > \\\"t\\\".\\\"total_value\\\" * 0.05\\nORDER BY \\\"g\\\".\\\"group_value\\\" DESC;\", \"columns\": [\"company_type\", \"group_value\"], \"rows\": [{\"company_type\": \"Pvt Ltd\", \"group_value\": 640827.0}, {\"company_type\": \"Funded Startup\", \"group_value\": 67064.0}, {\"company_type\": \"Public Sector\", \"group_value\": 59258.0}], \"row_count_returned\": 3, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 14.12}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..f2f8d5298e687b69d2258d03a50a898ba4fc009d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:50:09.388290+00:00", + "ended_at": "2026-05-19T15:50:33.233944+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_a324887aa577ef52", + "problem_id": "v2p_m9_85349abb956d915a", + "dataset_id": "m9", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=company_type, measure_col=training_hours.", + "bindings": { + "group_col": "company_type", + "measure_col": "training_hours", + "top_k": 15, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 70.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=9", + "sql_variant_index=2/2", + "binding_index=80" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 9, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_a324887aa577ef52.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_a324887aa577ef52", + "api_calls": 0, + "input_tokens": 14784, + "cached_input_tokens": 12032, + "output_tokens": 1075, + "total_tokens": 15859, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 23826.38, + "sql_execution_elapsed_ms_total": 14.12, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a4f4f7a578173b490d2735b4863c6f3f5968369f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:50:33.217692+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 23826.38, "started_at": "2026-05-19T15:50:09.389926+00:00", "ended_at": "2026-05-19T15:50:33.216334+00:00", "prompt_metrics": {"chars": 9858, "bytes_utf8": 9858, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 954, "bytes_utf8": 954, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14784, "cached_input_tokens": 12032, "output_tokens": 1075, "reasoning_output_tokens": 805}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"company_type\\\",\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n WHERE TRIM(COALESCE(\\\"company_type\\\", '')) <> ''\\n AND TRIM(COALESCE(\\\"training_hours\\\", '')) <> ''\\n GROUP BY \\\"company_type\\\"\\n),\\n\\\"total\\\" AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM \\\"grouped\\\"\\n)\\nSELECT\\n \\\"g\\\".\\\"company_type\\\",\\n \\\"g\\\".\\\"group_value\\\"\\nFROM \\\"grouped\\\" AS \\\"g\\\"\\nCROSS JOIN \\\"total\\\" AS \\\"t\\\"\\nWHERE \\\"g\\\".\\\"group_value\\\" > \\\"t\\\".\\\"total_value\\\" * 0.05\\nORDER BY \\\"g\\\".\\\"group_value\\\" DESC;\",\"notes\":\"Applied the planned Relative-to-Total Extreme Threshold template with group_col=\\\"company_type\\\" and measure_col=\\\"training_hours\\\". Blank company_type/training_hours values are filtered out for a more stable view, and \\\"training_hours\\\" is cast from TEXT to REAL before summation.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..82689bc8baf94528ef2a1c2075d7a53f73899f40 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_a324887aa577ef52", + "api_calls": 0, + "input_tokens": 14784, + "cached_input_tokens": 12032, + "output_tokens": 1075, + "total_tokens": 15859, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 23826.38, + "sql_execution_elapsed_ms_total": 14.12, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a324887aa577ef52/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..afd151c852237f7c76fadda7f24374a21e627f06 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=education_level, measure_col=city_development_index. +Result preview: [{"education_level": "Graduate", "total_measure": 9553.635}, {"education_level": "Masters", "total_measure": 3645.564}, {"education_level": "High School", "total_measure": 1681.956}, {"education_level": "", "total_measure": 370.395}, {"education_level": "Phd", "total_measure": 365.591}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..d6a39e2850c3e3df3feb7adbc80c18e6c05703ad --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_m9_a5700007f628b14b +-- problem_id: v2p_m9_6f6bfceaa978dedf +-- realization_mode: agent +-- source_kind: agent +SELECT + "education_level", + SUM(CAST("city_development_index" AS REAL)) AS "total_measure" +FROM "m9" +GROUP BY "education_level" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..73365340a79eb68c91b1873e27b98c343b1b6f71 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum.\nSELECT\n \"education_level\",\n SUM(CAST(\"city_development_index\" AS REAL)) AS \"total_measure\"\nFROM \"m9\"\nGROUP BY \"education_level\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum.\\nSELECT\\n \\\"education_level\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"education_level\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"education_level\", \"total_measure\"], \"rows\": [{\"education_level\": \"Graduate\", \"total_measure\": 9553.635}, {\"education_level\": \"Masters\", \"total_measure\": 3645.564}, {\"education_level\": \"High School\", \"total_measure\": 1681.956}, {\"education_level\": \"\", \"total_measure\": 370.395}, {\"education_level\": \"Phd\", \"total_measure\": 365.591}, {\"education_level\": \"Primary School\", \"total_measure\": 261.92900000000003}], \"row_count_returned\": 6, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 13.61}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..2ea0b840d65c7345fd4aa2343d6e2627cf5359ee --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:29:46.284054+00:00", + "ended_at": "2026-05-19T15:30:03.986636+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_a5700007f628b14b", + "problem_id": "v2p_m9_6f6bfceaa978dedf", + "dataset_id": "m9", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_rank_order", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=education_level, measure_col=city_development_index.", + "bindings": { + "group_col": "education_level", + "measure_col": "city_development_index", + "top_k": 14, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=1/2", + "binding_index=4" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_a5700007f628b14b.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_a5700007f628b14b", + "api_calls": 0, + "input_tokens": 14650, + "cached_input_tokens": 12032, + "output_tokens": 758, + "total_tokens": 15408, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17684.51, + "sql_execution_elapsed_ms_total": 13.61, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..84f1d8663ca5fc40cb4611741a9f5e8f3a8b233d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:30:03.971228+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 17684.51, "started_at": "2026-05-19T15:29:46.285737+00:00", "ended_at": "2026-05-19T15:30:03.970275+00:00", "prompt_metrics": {"chars": 9323, "bytes_utf8": 9323, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 406, "bytes_utf8": 406, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14650, "cached_input_tokens": 12032, "output_tokens": 758, "reasoning_output_tokens": 651}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum.\\nSELECT\\n \\\"education_level\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"education_level\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Uses the grouped numeric sum template with \\\"education_level\\\" as the grouping column and casts \\\"city_development_index\\\" from TEXT to REAL so SQLite can sum it correctly.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..97953cc8b89527ec52841909c89a3041c72a8781 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_a5700007f628b14b", + "api_calls": 0, + "input_tokens": 14650, + "cached_input_tokens": 12032, + "output_tokens": 758, + "total_tokens": 15408, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17684.51, + "sql_execution_elapsed_ms_total": 13.61, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5700007f628b14b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..5e57503dd015af70157df2d0cac64e9f132c0943 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"target": "0.0", "total_rows": 14381, "missing_rows": 0, "missing_rate": 0.0}, {"target": "1.0", "total_rows": 4777, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..ea57b9752aa9196b325eac9bbe59798a8dfc5a55 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: co_missingness_pattern_consistency +-- intended_facet_id: missing_target_interaction +-- variant_semantic_role: missing_target_interaction +-- template_id: tpl_missing_target_interaction +-- query_record_id: v2q_m9_a5a15f9cee441912 +-- problem_id: v2p_m9_b618eeec34d03f6b +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "target", + COUNT(*) AS total_rows, + SUM(CASE WHEN "education_level" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "education_level" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9" +GROUP BY "target" +ORDER BY missing_rate DESC, total_rows DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1dc433830a447e93e71c5618c02d323b028afd00 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: co_missingness_pattern_consistency\n-- intended_facet_id: missing_target_interaction\n-- variant_semantic_role: missing_target_interaction\n-- template_id: tpl_missing_target_interaction\n-- query_record_id: v2q_m9_a5a15f9cee441912\n-- problem_id: v2p_m9_b618eeec34d03f6b\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"target\",\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"education_level\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"education_level\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\"\nGROUP BY \"target\"\nORDER BY missing_rate DESC, total_rows DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: co_missingness_pattern_consistency\\n-- intended_facet_id: missing_target_interaction\\n-- variant_semantic_role: missing_target_interaction\\n-- template_id: tpl_missing_target_interaction\\n-- query_record_id: v2q_m9_a5a15f9cee441912\\n-- problem_id: v2p_m9_b618eeec34d03f6b\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"target\\\",\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"education_level\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"education_level\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"target\\\"\\nORDER BY missing_rate DESC, total_rows DESC;\", \"columns\": [\"target\", \"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"target\": \"0.0\", \"total_rows\": 14381, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"target\": \"1.0\", \"total_rows\": 4777, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 8.25}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..817a911aed9083dc7b416f659616ffa20e1087d7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/run_manifest.json @@ -0,0 +1,59 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.088599+00:00", + "ended_at": "2026-05-19T16:08:56.097627+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_a5a15f9cee441912", + "problem_id": "v2p_m9_b618eeec34d03f6b", + "dataset_id": "m9", + "template_id": "tpl_missing_target_interaction", + "template_name": "Missingness-Target Interaction", + "family_id": "missingness_structure", + "canonical_subitem_id": "co_missingness_pattern_consistency", + "intended_facet_id": "missing_target_interaction", + "variant_semantic_role": "missing_target_interaction", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Missingness-Target Interaction to probe co_missingness_pattern_consistency with semantic role missing_target_interaction. Focus on target_col=target, missing_col=education_level.", + "bindings": { + "missing_col": "education_level", + "target_col": "target" + }, + "binding_roles": [ + "missing_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {target_col},\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {target_col}\nORDER BY missing_rate DESC, total_rows DESC;", + "notes": [ + "default_facets=missing_rate_by_subgroup,missing_target_interaction", + "template_selection_mode=deterministic", + "problem_index_within_template=4", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_a5a15f9cee441912.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5a15f9cee441912/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5cc86f444066e39/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5cc86f444066e39/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3826b60a88e24a0d91f37ea9591b046d1e0b9fda --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5cc86f444066e39/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=city_development_index, measure_col=enrollee_id. +Result preview: [{"city_development_index": "0.92", "total_measure": 88549363}, {"city_development_index": "0.624", "total_measure": 48522501}, {"city_development_index": "0.91", "total_measure": 26141445}, {"city_development_index": "0.9259999999999999", "total_measure": 22746055}, {"city_development_index": "0.698", "total_measure": 11041718}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5cc86f444066e39/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5cc86f444066e39/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..991c54f2a9c82389e0827f70816a0146d96e2f88 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a5cc86f444066e39/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_m9_a5cc86f444066e39 +-- problem_id: v2p_m9_cbdf9c3865cd4e42 +-- realization_mode: agent +-- source_kind: agent +SELECT "city_development_index", SUM("enrollee_id") AS total_measure +FROM "m9" +GROUP BY "city_development_index" +ORDER BY total_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..e786f0f9a0354259d2f9cb3d6fe78f28e509436f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=experience, measure_col=enrollee_id. +Result preview: [{"experience": "20", "city": "city_103", "total_measure": 927153.0, "share_within_group": 38.59204327589465}, {"experience": ">20", "city": "city_103", "total_measure": 20131306.0, "share_within_group": 36.967948572453984}, {"experience": "<1", "city": "city_21", "total_measure": 3398298.0, "share_within_group": 36.57944772676193}, {"experience": "18", "city": "city_103", "total_measure": 1557488.0, "share_within_group": 32.95179480235647}, {"experience": "", "city": "city_103", "total_measure": 312754.0, "share_within_group": 30.72689421143173}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..38c18ed73412a4802e94a7dfcf3ecffdd710b9ca --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/generated_sql.sql @@ -0,0 +1,19 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_m9_a6b27a42e81166a1 +-- problem_id: v2p_m9_e03c971eecbdb225 +-- realization_mode: agent +-- source_kind: agent +SELECT "experience", "city", + SUM(CAST("enrollee_id" AS REAL)) AS total_measure, + SUM(CAST("enrollee_id" AS REAL)) * 100.0 / SUM(SUM(CAST("enrollee_id" AS REAL))) OVER (PARTITION BY "experience") AS share_within_group +FROM "m9" +GROUP BY "experience", "city" +ORDER BY share_within_group DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5c48f1d6e8ac4dd2723e1a97136b84801ddb700b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT \"experience\", \"city\",\n SUM(CAST(\"enrollee_id\" AS REAL)) AS total_measure,\n SUM(CAST(\"enrollee_id\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"enrollee_id\" AS REAL))) OVER (PARTITION BY \"experience\") AS share_within_group\nFROM \"m9\"\nGROUP BY \"experience\", \"city\"\nORDER BY share_within_group DESC;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"experience\\\", \\\"city\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"enrollee_id\\\" AS REAL))) OVER (PARTITION BY \\\"experience\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\", \\\"city\\\"\\nORDER BY share_within_group DESC;\", \"columns\": [\"experience\", \"city\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"experience\": \"20\", \"city\": \"city_103\", \"total_measure\": 927153.0, \"share_within_group\": 38.59204327589465}, {\"experience\": \">20\", \"city\": \"city_103\", \"total_measure\": 20131306.0, \"share_within_group\": 36.967948572453984}, {\"experience\": \"<1\", \"city\": \"city_21\", \"total_measure\": 3398298.0, \"share_within_group\": 36.57944772676193}, {\"experience\": \"18\", \"city\": \"city_103\", \"total_measure\": 1557488.0, \"share_within_group\": 32.95179480235647}, {\"experience\": \"\", \"city\": \"city_103\", \"total_measure\": 312754.0, \"share_within_group\": 30.72689421143173}, {\"experience\": \"15\", \"city\": \"city_103\", \"total_measure\": 3131360.0, \"share_within_group\": 28.688154748342374}, {\"experience\": \"1\", \"city\": \"city_21\", \"total_measure\": 2831423.0, \"share_within_group\": 28.43445085822859}, {\"experience\": \"19\", \"city\": \"city_103\", \"total_measure\": 1427394.0, \"share_within_group\": 28.060414479659357}, {\"experience\": \"3\", \"city\": \"city_21\", \"total_measure\": 6493168.0, \"share_within_group\": 27.432934800660924}, {\"experience\": \"16\", \"city\": \"city_103\", \"total_measure\": 2431491.0, \"share_within_group\": 27.13575898044611}, {\"experience\": \"17\", \"city\": \"city_103\", \"total_measure\": 1518534.0, \"share_within_group\": 26.8049418839154}, {\"experience\": \"13\", \"city\": \"city_103\", \"total_measure\": 1749403.0, \"share_within_group\": 26.222159800511673}, {\"experience\": \"2\", \"city\": \"city_21\", \"total_measure\": 4898123.0, \"share_within_group\": 24.657904084470683}, {\"experience\": \"4\", \"city\": \"city_21\", \"total_measure\": 5316402.0, \"share_within_group\": 22.214176436585703}, {\"experience\": \"10\", \"city\": \"city_103\", \"total_measure\": 3614953.0, \"share_within_group\": 22.12121531069911}, {\"experience\": \"11\", \"city\": \"city_103\", \"total_measure\": 2392599.0, \"share_within_group\": 21.660747966961505}, {\"experience\": \"5\", \"city\": \"city_21\", \"total_measure\": 5261497.0, \"share_within_group\": 21.42145468921061}, {\"experience\": \"\", \"city\": \"city_21\", \"total_measure\": 211085.0, \"share_within_group\": 20.738300596059737}, {\"experience\": \"12\", \"city\": \"city_103\", \"total_measure\": 1626496.0, \"share_within_group\": 20.447189236844658}, {\"experience\": \"6\", \"city\": \"city_21\", \"total_measure\": 4223829.0, \"share_within_group\": 20.42311700328137}, {\"experience\": \"6\", \"city\": \"city_103\", \"total_measure\": 4145640.0, \"share_within_group\": 20.045056457892443}, {\"experience\": \"14\", \"city\": \"city_103\", \"total_measure\": 1862550.0, \"share_within_group\": 20.029028138066575}, {\"experience\": \"7\", \"city\": \"city_21\", \"total_measure\": 3454054.0, \"share_within_group\": 19.921798646134807}, {\"experience\": \"5\", \"city\": \"city_103\", \"total_measure\": 4860160.0, \"share_within_group\": 19.787466803138695}, {\"experience\": \"7\", \"city\": \"city_103\", \"total_measure\": 3299847.0, \"share_within_group\": 19.032385566945972}, {\"experience\": \"8\", \"city\": \"city_21\", \"total_measure\": 2404801.0, \"share_within_group\": 18.495549779373288}, {\"experience\": \"4\", \"city\": \"city_103\", \"total_measure\": 4391051.0, \"share_within_group\": 18.347668527708418}, {\"experience\": \"9\", \"city\": \"city_103\", \"total_measure\": 3009323.0, \"share_within_group\": 18.28556890574105}, {\"experience\": \"8\", \"city\": \"city_103\", \"total_measure\": 2185958.0, \"share_within_group\": 16.81240776455901}, {\"experience\": \"2\", \"city\": \"city_103\", \"total_measure\": 3284033.0, \"share_within_group\": 16.53232691874755}, {\"experience\": \"3\", \"city\": \"city_103\", \"total_measure\": 3865548.0, \"share_within_group\": 16.33152357259588}, {\"experience\": \"1\", \"city\": \"city_103\", \"total_measure\": 1446162.0, \"share_within_group\": 14.523023342692905}, {\"experience\": \"<1\", \"city\": \"city_103\", \"total_measure\": 1279451.0, \"share_within_group\": 13.7720738362125}, {\"experience\": \"9\", \"city\": \"city_21\", \"total_measure\": 2071680.0, \"share_within_group\": 12.58816265008629}, {\"experience\": \"10\", \"city\": \"city_21\", \"total_measure\": 2024406.0, \"share_within_group\": 12.388078351854405}, {\"experience\": \">20\", \"city\": \"city_16\", \"total_measure\": 6372890.0, \"share_within_group\": 11.702801088906318}, {\"experience\": \"11\", \"city\": \"city_114\", \"total_measure\": 1199414.0, \"share_within_group\": 10.858570266912746}, {\"experience\": \"12\", \"city\": \"city_21\", \"total_measure\": 847580.0, \"share_within_group\": 10.65519291370209}, {\"experience\": \"19\", \"city\": \"city_114\", \"total_measure\": 530347.0, \"share_within_group\": 10.425822609625584}, {\"experience\": \"20\", \"city\": \"city_16\", \"total_measure\": 249700.0, \"share_within_group\": 10.393573882617964}, {\"experience\": \"17\", \"city\": \"city_114\", \"total_measure\": 583871.0, \"share_within_group\": 10.306406193541646}, {\"experience\": \"15\", \"city\": \"city_114\", \"total_measure\": 1117791.0, \"share_within_group\": 10.240713678498919}, {\"experience\": \"14\", \"city\": \"city_114\", \"total_measure\": 947686.0, \"share_within_group\": 10.190990609675852}, {\"experience\": \"14\", \"city\": \"city_16\", \"total_measure\": 939765.0, \"share_within_group\": 10.105811724877256}, {\"experience\": \"15\", \"city\": \"city_16\", \"total_measure\": 1068760.0, \"share_within_group\": 9.79151303869194}, {\"experience\": \"16\", \"city\": \"city_16\", \"total_measure\": 871691.0, \"share_within_group\": 9.728186072423895}, {\"experience\": \"13\", \"city\": \"city_114\", \"total_measure\": 639668.0, \"share_within_group\": 9.58811463983639}, {\"experience\": \"19\", \"city\": \"city_16\", \"total_measure\": 478716.0, \"share_within_group\": 9.41083497481747}, {\"experience\": \"17\", \"city\": \"city_16\", \"total_measure\": 530208.0, \"share_within_group\": 9.359154702092292}, {\"experience\": \"11\", \"city\": \"city_21\", \"total_measure\": 1015518.0, \"share_within_group\": 9.193717565673484}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 27.91}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..eee0e168d8f81c233390e616ed0414c6b610e7fa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:37:43.491369+00:00", + "ended_at": "2026-05-19T15:37:54.881861+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_a6b27a42e81166a1", + "problem_id": "v2p_m9_e03c971eecbdb225", + "dataset_id": "m9", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=experience, measure_col=enrollee_id.", + "bindings": { + "group_col": "experience", + "measure_col": "enrollee_id", + "item_col": "city", + "top_k": 15, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=2/2", + "binding_index=30" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 7, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_a6b27a42e81166a1.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_a6b27a42e81166a1", + "api_calls": 0, + "input_tokens": 14765, + "cached_input_tokens": 13696, + "output_tokens": 535, + "total_tokens": 15300, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11356.95, + "sql_execution_elapsed_ms_total": 27.91, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..249d43f748eb5d0645d4b6e09f6adce56137f528 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:37:54.851651+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11356.95, "started_at": "2026-05-19T15:37:43.493910+00:00", "ended_at": "2026-05-19T15:37:54.850891+00:00", "prompt_metrics": {"chars": 9698, "bytes_utf8": 9698, "lines": 266, "estimated_tokens": null}, "response_metrics": {"chars": 588, "bytes_utf8": 588, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14765, "cached_input_tokens": 13696, "output_tokens": 535, "reasoning_output_tokens": 367}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"experience\\\", \\\"city\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"enrollee_id\\\" AS REAL))) OVER (PARTITION BY \\\"experience\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\", \\\"city\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Applied the Within-Group Share of Total template with group_col=\\\"experience\\\", item_col=\\\"city\\\", and measure_col=\\\"enrollee_id\\\". CAST is used because the schema stores \\\"enrollee_id\\\" as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..eeace25606548c07b523d3aa657bcff9d9f47fa0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_a6b27a42e81166a1", + "api_calls": 0, + "input_tokens": 14765, + "cached_input_tokens": 13696, + "output_tokens": 535, + "total_tokens": 15300, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11356.95, + "sql_execution_elapsed_ms_total": 27.91, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_a6b27a42e81166a1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..ca389dbb91d4e4863751f32f85444693fe160c64 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "Graduate", "support": 11598, "support_share": 0.6053867835891011, "cumulative_support": 11598}, {"value_label": "Masters", "support": 4361, "support_share": 0.22763336465184258, "cumulative_support": 15959}, {"value_label": "High School", "support": 2017, "support_share": 0.10528238855830463, "cumulative_support": 17976}, {"value_label": "", "support": 460, "support_share": 0.02401085708320284, "cumulative_support": 18436}, {"value_label": "Phd", "support": 414, "support_share": 0.021609771374882555, "cumulative_support": 18850}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..59ce427d82158d82b847a876e037d15bcf7230b2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/generated_sql.sql @@ -0,0 +1,28 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: support_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_cardinality_distinct_share_profile +-- query_record_id: v2q_m9_abb6bb384108ddce +-- problem_id: v2p_m9_fe1a73af9cfa172e +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "education_level" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "education_level" +), ranked AS ( + SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support + FROM grouped +) +SELECT * +FROM ranked +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d8ed9ee7d8a1162a5c4c8e11bfe523be708177c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: ranked_signal_view\n-- template_id: tpl_cardinality_distinct_share_profile\n-- query_record_id: v2q_m9_abb6bb384108ddce\n-- problem_id: v2p_m9_fe1a73af9cfa172e\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"education_level\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"education_level\"\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: ranked_signal_view\\n-- template_id: tpl_cardinality_distinct_share_profile\\n-- query_record_id: v2q_m9_abb6bb384108ddce\\n-- problem_id: v2p_m9_fe1a73af9cfa172e\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"education_level\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"education_level\\\"\\n), ranked AS (\\n SELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\\n FROM grouped\\n)\\nSELECT *\\nFROM ranked\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"cumulative_support\"], \"rows\": [{\"value_label\": \"Graduate\", \"support\": 11598, \"support_share\": 0.6053867835891011, \"cumulative_support\": 11598}, {\"value_label\": \"Masters\", \"support\": 4361, \"support_share\": 0.22763336465184258, \"cumulative_support\": 15959}, {\"value_label\": \"High School\", \"support\": 2017, \"support_share\": 0.10528238855830463, \"cumulative_support\": 17976}, {\"value_label\": \"\", \"support\": 460, \"support_share\": 0.02401085708320284, \"cumulative_support\": 18436}, {\"value_label\": \"Phd\", \"support\": 414, \"support_share\": 0.021609771374882555, \"cumulative_support\": 18850}, {\"value_label\": \"Primary School\", \"support\": 308, \"support_share\": 0.01607683474266625, \"cumulative_support\": 19158}], \"row_count_returned\": 6, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 6.47}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..96482a154ace03fb8afbb270fa2f8aa3432605eb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.204342+00:00", + "ended_at": "2026-05-19T16:08:56.211558+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_abb6bb384108ddce", + "problem_id": "v2p_m9_fe1a73af9cfa172e", + "dataset_id": "m9", + "template_id": "tpl_cardinality_distinct_share_profile", + "template_name": "Cardinality Distinct Share Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "support_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Distinct Share Profile to probe support_rank_profile_consistency with semantic role ranked_signal_view. Focus on group_col=education_level.", + "bindings": { + "group_col": "education_level" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=5", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_abb6bb384108ddce.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_abb6bb384108ddce/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..5cb96cefd458b50da4cb1d24b1923532139d1d20 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=enrollee_id. +Result preview: [{"enrollee_id": "33380"}, {"enrollee_id": "33379"}, {"enrollee_id": "33377"}, {"enrollee_id": "33376"}, {"enrollee_id": "33375"}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..89c9ff82edd8ac50cc119a71f7f514f38dd81c1a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/generated_sql.sql @@ -0,0 +1,23 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_m9_ad39db2dee95ced1 +-- problem_id: v2p_m9_a6d3205e059802fe +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT + "enrollee_id", + NTILE(10) OVER (ORDER BY CAST("enrollee_id" AS INTEGER) DESC) AS "tail_bucket" + FROM "m9" +) +SELECT "enrollee_id" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY CAST("enrollee_id" AS INTEGER) DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3953414776700ec4add2d2c22ffcc30e60ea2c7a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH \"buckets\" AS (\n SELECT\n \"enrollee_id\",\n NTILE(10) OVER (ORDER BY CAST(\"enrollee_id\" AS INTEGER) DESC) AS \"tail_bucket\"\n FROM \"m9\"\n)\nSELECT \"enrollee_id\"\nFROM \"buckets\"\nWHERE \"tail_bucket\" = 1\nORDER BY CAST(\"enrollee_id\" AS INTEGER) DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT\\n \\\"enrollee_id\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"enrollee_id\\\" AS INTEGER) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"m9\\\"\\n)\\nSELECT \\\"enrollee_id\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY CAST(\\\"enrollee_id\\\" AS INTEGER) DESC;\", \"columns\": [\"enrollee_id\"], \"rows\": [{\"enrollee_id\": \"33380\"}, {\"enrollee_id\": \"33379\"}, {\"enrollee_id\": \"33377\"}, {\"enrollee_id\": \"33376\"}, {\"enrollee_id\": \"33375\"}, {\"enrollee_id\": \"33374\"}, {\"enrollee_id\": \"33373\"}, {\"enrollee_id\": \"33370\"}, {\"enrollee_id\": \"33368\"}, {\"enrollee_id\": \"33367\"}, {\"enrollee_id\": \"33365\"}, {\"enrollee_id\": \"33362\"}, {\"enrollee_id\": \"33360\"}, {\"enrollee_id\": \"33358\"}, {\"enrollee_id\": \"33357\"}, {\"enrollee_id\": \"33356\"}, {\"enrollee_id\": \"33352\"}, {\"enrollee_id\": \"33350\"}, {\"enrollee_id\": \"33349\"}, {\"enrollee_id\": \"33348\"}, {\"enrollee_id\": \"33344\"}, {\"enrollee_id\": \"33342\"}, {\"enrollee_id\": \"33341\"}, {\"enrollee_id\": \"33340\"}, {\"enrollee_id\": \"33339\"}, {\"enrollee_id\": \"33338\"}, {\"enrollee_id\": \"33337\"}, {\"enrollee_id\": \"33336\"}, {\"enrollee_id\": \"33335\"}, {\"enrollee_id\": \"33333\"}, {\"enrollee_id\": \"33332\"}, {\"enrollee_id\": \"33331\"}, {\"enrollee_id\": \"33330\"}, {\"enrollee_id\": \"33328\"}, {\"enrollee_id\": \"33327\"}, {\"enrollee_id\": \"33326\"}, {\"enrollee_id\": \"33325\"}, {\"enrollee_id\": \"33321\"}, {\"enrollee_id\": \"33318\"}, {\"enrollee_id\": \"33317\"}, {\"enrollee_id\": \"33315\"}, {\"enrollee_id\": \"33314\"}, {\"enrollee_id\": \"33312\"}, {\"enrollee_id\": \"33311\"}, {\"enrollee_id\": \"33310\"}, {\"enrollee_id\": \"33307\"}, {\"enrollee_id\": \"33306\"}, {\"enrollee_id\": \"33305\"}, {\"enrollee_id\": \"33304\"}, {\"enrollee_id\": \"33302\"}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 24.6}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..096850388dc05937be2feb4113e62a7d42cf8fbd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:45:19.395829+00:00", + "ended_at": "2026-05-19T15:45:35.407315+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_ad39db2dee95ced1", + "problem_id": "v2p_m9_a6d3205e059802fe", + "dataset_id": "m9", + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=enrollee_id.", + "bindings": { + "measure_col": "enrollee_id", + "top_k": 11, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=1/1", + "binding_index=66" + ], + "template_selection_mode": "rule", + "selected_template_rank": 6, + "problem_index_within_template": 7, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_ad39db2dee95ced1.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_ad39db2dee95ced1", + "api_calls": 0, + "input_tokens": 14703, + "cached_input_tokens": 13696, + "output_tokens": 658, + "total_tokens": 15361, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15982.65, + "sql_execution_elapsed_ms_total": 24.6, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..381cdbbe4b455c2a3b621b44b2702aa49d6607de --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:45:35.381239+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15982.65, "started_at": "2026-05-19T15:45:19.397793+00:00", "ended_at": "2026-05-19T15:45:35.380474+00:00", "prompt_metrics": {"chars": 9462, "bytes_utf8": 9462, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 555, "bytes_utf8": 555, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14703, "cached_input_tokens": 13696, "output_tokens": 658, "reasoning_output_tokens": 495}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT\\n \\\"enrollee_id\\\",\\n NTILE(10) OVER (ORDER BY CAST(\\\"enrollee_id\\\" AS INTEGER) DESC) AS \\\"tail_bucket\\\"\\n FROM \\\"m9\\\"\\n)\\nSELECT \\\"enrollee_id\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY CAST(\\\"enrollee_id\\\" AS INTEGER) DESC;\",\"notes\":\"Applied the Quantile Tail Slice template with measure_col bound to \\\"enrollee_id\\\" and num_tiles=10. CAST is used because \\\"enrollee_id\\\" is stored as TEXT in SQLite but represents numeric identifiers.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..94ef78ce3342188aca532325f47a9f4d03f9d599 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_ad39db2dee95ced1", + "api_calls": 0, + "input_tokens": 14703, + "cached_input_tokens": 13696, + "output_tokens": 658, + "total_tokens": 15361, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15982.65, + "sql_execution_elapsed_ms_total": 24.6, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ad39db2dee95ced1/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..dc7292c6a65c3875d1007f07a37ba826538e4ba6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=training_hours. +Result preview: [{"empirical_cdf_at_threshold": 0.7504436788808853}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..2ad2c3ce36eda7c0c757d92725004becdfe2723a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/generated_sql.sql @@ -0,0 +1,15 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_threshold_rarity_cdf +-- query_record_id: v2q_m9_ae2b1f0db34ea4db +-- problem_id: v2p_m9_49935188335e0f2e +-- realization_mode: agent +-- source_kind: agent +SELECT AVG(CASE WHEN CAST(NULLIF("training_hours", '') AS REAL) <= 88.0 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold" +FROM "m9"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c051d580f292e84a24842f365e705fda8f9b4e17 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(NULLIF(\"training_hours\", '') AS REAL) <= 88.0 THEN 1 ELSE 0 END) AS \"empirical_cdf_at_threshold\"\nFROM \"m9\";", "result": "{\"query\": \"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(NULLIF(\\\"training_hours\\\", '') AS REAL) <= 88.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"m9\\\";\", \"columns\": [\"empirical_cdf_at_threshold\"], \"rows\": [{\"empirical_cdf_at_threshold\": 0.7504436788808853}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.17}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..d69c809705cdccd9a27698682f5893c507c9ba0a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:02:50.797528+00:00", + "ended_at": "2026-05-19T16:03:08.118244+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_ae2b1f0db34ea4db", + "problem_id": "v2p_m9_49935188335e0f2e", + "dataset_id": "m9", + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=training_hours.", + "bindings": { + "measure_col": "training_hours", + "top_k": 10, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=1/1", + "binding_index=110" + ], + "template_selection_mode": "rule", + "selected_template_rank": 10, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_ae2b1f0db34ea4db.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_ae2b1f0db34ea4db", + "api_calls": 0, + "input_tokens": 14635, + "cached_input_tokens": 12032, + "output_tokens": 622, + "total_tokens": 15257, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17304.86, + "sql_execution_elapsed_ms_total": 9.17, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..5776d7f0c537eeb1bdc7120148f27353a5cc9bc9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:03:08.105661+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 17304.86, "started_at": "2026-05-19T16:02:50.799226+00:00", "ended_at": "2026-05-19T16:03:08.104122+00:00", "prompt_metrics": {"chars": 9230, "bytes_utf8": 9230, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 383, "bytes_utf8": 383, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14635, "cached_input_tokens": 12032, "output_tokens": 622, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(NULLIF(\\\"training_hours\\\", '') AS REAL) <= 88.0 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"m9\\\";\",\"notes\":\"Uses the planned Threshold Rarity CDF template on \\\"training_hours\\\" with threshold 88.0, casting from TEXT to REAL and guarding empty strings with NULLIF for SQLite compatibility.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..38e8791e5ac11c42234f3123f86e48b9720dfe58 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_ae2b1f0db34ea4db", + "api_calls": 0, + "input_tokens": 14635, + "cached_input_tokens": 12032, + "output_tokens": 622, + "total_tokens": 15257, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17304.86, + "sql_execution_elapsed_ms_total": 9.17, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ae2b1f0db34ea4db/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..8e266c73810018c16686732d6d8489e54421e4f6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=city_development_index. +Result preview: [{"empirical_cdf_at_threshold": 0.8675749034345965}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..a4b4cbc1d9e247cd9b48fc8b815d661ebd0826d9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/generated_sql.sql @@ -0,0 +1,15 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_threshold_rarity_cdf +-- query_record_id: v2q_m9_af17ec05ff744d92 +-- problem_id: v2p_m9_43798335092d0231 +-- realization_mode: agent +-- source_kind: agent +SELECT AVG(CASE WHEN CAST("city_development_index" AS REAL) <= 0.92 THEN 1 ELSE 0 END) AS "empirical_cdf_at_threshold" +FROM "m9"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f077b03c853c42c70c4df63201267a1c0f79f577 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_threshold_rarity_cdf\nSELECT AVG(CASE WHEN CAST(\"city_development_index\" AS REAL) <= 0.92 THEN 1 ELSE 0 END) AS \"empirical_cdf_at_threshold\"\nFROM \"m9\";", "result": "{\"query\": \"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"city_development_index\\\" AS REAL) <= 0.92 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"m9\\\";\", \"columns\": [\"empirical_cdf_at_threshold\"], \"rows\": [{\"empirical_cdf_at_threshold\": 0.8675749034345965}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 11.84}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..a704e591c8f0cdf5e2ea5ee10f18817fb3b3dd0f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:03:42.943969+00:00", + "ended_at": "2026-05-19T16:04:01.852811+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_af17ec05ff744d92", + "problem_id": "v2p_m9_43798335092d0231", + "dataset_id": "m9", + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=city_development_index.", + "bindings": { + "measure_col": "city_development_index", + "top_k": 10, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/1", + "binding_index=115" + ], + "template_selection_mode": "rule", + "selected_template_rank": 10, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_af17ec05ff744d92.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_af17ec05ff744d92", + "api_calls": 0, + "input_tokens": 14639, + "cached_input_tokens": 12032, + "output_tokens": 484, + "total_tokens": 15123, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17886.28, + "sql_execution_elapsed_ms_total": 11.84, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..aac8a59255b0cadce42e1edbce78088147502614 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:03:48.876687+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 5928.14, "started_at": "2026-05-19T16:03:42.947595+00:00", "ended_at": "2026-05-19T16:03:48.875775+00:00", "prompt_metrics": {"chars": 9245, "bytes_utf8": 9245, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fa-8ff8-7c80-b75e-5096f11613c2\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:04:01.837957+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11958.14, "started_at": "2026-05-19T16:03:49.878171+00:00", "ended_at": "2026-05-19T16:04:01.836368+00:00", "prompt_metrics": {"chars": 9245, "bytes_utf8": 9245, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 412, "bytes_utf8": 412, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14639, "cached_input_tokens": 12032, "output_tokens": 484, "reasoning_output_tokens": 372}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_threshold_rarity_cdf\\nSELECT AVG(CASE WHEN CAST(\\\"city_development_index\\\" AS REAL) <= 0.92 THEN 1 ELSE 0 END) AS \\\"empirical_cdf_at_threshold\\\"\\nFROM \\\"m9\\\";\",\"notes\":\"Used the provided Threshold Rarity CDF template with measure_col bound to \\\"city_development_index\\\" and measure_threshold 0.92. The measure column is cast to REAL so the threshold comparison is numeric in SQLite.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..90f8e9e032351c5b53e7c2a0114d02dfc9269282 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_af17ec05ff744d92", + "api_calls": 0, + "input_tokens": 14639, + "cached_input_tokens": 12032, + "output_tokens": 484, + "total_tokens": 15123, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 17886.28, + "sql_execution_elapsed_ms_total": 11.84, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_af17ec05ff744d92/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b049d7fc80d2fb22/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b049d7fc80d2fb22/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..2c41774fee165208b3cd80b2c57565b2ddecc435 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b049d7fc80d2fb22/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:06:44.332569+00:00", + "ended_at": "2026-05-19T16:06:51.712491+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_b049d7fc80d2fb22", + "problem_id": "v2p_m9_6b0901d7c3fc20f2", + "dataset_id": "m9", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=city_development_index, measure_col=enrollee_id.", + "bindings": { + "group_col": "city_development_index", + "measure_col": "enrollee_id", + "top_k": 17, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=2/2", + "binding_index=132" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 1, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b049d7fc80d2fb22/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b049d7fc80d2fb22/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..97820ba295d887b58dcb6ab06d0c513559d83f00 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b049d7fc80d2fb22/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:06:47.457565+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3122.14, "started_at": "2026-05-19T16:06:44.334606+00:00", "ended_at": "2026-05-19T16:06:47.456781+00:00", "prompt_metrics": {"chars": 9404, "bytes_utf8": 9404, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fd-546b-7592-a74d-d8c87dca8c9a\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:06:51.712358+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3252.77, "started_at": "2026-05-19T16:06:48.458659+00:00", "ended_at": "2026-05-19T16:06:51.711470+00:00", "prompt_metrics": {"chars": 9404, "bytes_utf8": 9404, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fd-6484-7642-90a5-8d243dd26ab8\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b1f1468746372d9a/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b1f1468746372d9a/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..aa0de843fccdcbe9d318d0b94304b54b62f315ec --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b1f1468746372d9a/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:07:47.201105+00:00", + "ended_at": "2026-05-19T16:07:54.269257+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_b1f1468746372d9a", + "problem_id": "v2p_m9_86def8b0618cf055", + "dataset_id": "m9", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=education_level, measure_col=city_development_index.", + "bindings": { + "group_col": "education_level", + "measure_col": "city_development_index", + "top_k": 11, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=1/2", + "binding_index=136" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b1f1468746372d9a/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b1f1468746372d9a/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..dbdb07fbd662dec77946f4dd162dccc744f3a852 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b1f1468746372d9a/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:07:50.000376+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2796.45, "started_at": "2026-05-19T16:07:47.203163+00:00", "ended_at": "2026-05-19T16:07:49.999641+00:00", "prompt_metrics": {"chars": 9409, "bytes_utf8": 9409, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fe-4a02-7a73-a1e9-0c6f06e4616c\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:07:54.269168+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3267.13, "started_at": "2026-05-19T16:07:51.001269+00:00", "ended_at": "2026-05-19T16:07:54.268432+00:00", "prompt_metrics": {"chars": 9409, "bytes_utf8": 9409, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fe-58ee-7cb0-924e-0086f7f3fd2a\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2df9ea7682bcbce9891a4ad152d6202dde30e942 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/conversation.jsonl @@ -0,0 +1,4 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9302, "bytes_utf8": 9302, "lines": 262, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "status": "failed", "error": "AI CLI command failed with exit code 1: "} +{"attempt": 2, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_2.txt", "metrics": {"chars": 9302, "bytes_utf8": 9302, "lines": 262, "estimated_tokens": null}} +{"attempt": 2, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_2.txt", "raw_content_path": "cli/sql_response_attempt_2.raw.txt", "stderr_path": "cli/sql_stderr_attempt_2.txt", "metrics": {"chars": 359, "bytes_utf8": 359, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14662, "cached_input_tokens": 13696, "output_tokens": 325, "reasoning_output_tokens": 226}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..595a0358b329f3538bd8124982200248a3906b16 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 2, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_b2ff6a427ef6c731", + "api_calls": 0, + "input_tokens": 14662, + "cached_input_tokens": 13696, + "output_tokens": 325, + "total_tokens": 14987, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12446.25, + "sql_execution_elapsed_ms_total": 8.12, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..4aa2fb3c2a6c2b10f2b324fdd08f56b83cc44d95 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:04:01.857473+00:00", + "ended_at": "2026-05-19T16:04:05.250330+00:00", + "elapsed_ms": 3392.81, + "returncode": 1, + "prompt_metrics": { + "chars": 9302, + "bytes_utf8": 9302, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..93d4ca79a3e6efea610208fbf00e1166bad23d9a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_attempt_2.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:04:06.253071+00:00", + "ended_at": "2026-05-19T16:04:15.306538+00:00", + "elapsed_ms": 9053.44, + "prompt_metrics": { + "chars": 9302, + "bytes_utf8": 9302, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 712, + "bytes_utf8": 712, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 359, + "bytes_utf8": 359, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14662, + "cached_input_tokens": 13696, + "output_tokens": 325, + "reasoning_output_tokens": 226 + } + }, + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..c85af42c305fe2b77c0ec20972cdc2013b61ef90 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=city_development_index.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "city_development_index", + "top_k": 10, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..c85af42c305fe2b77c0ec20972cdc2013b61ef90 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=city_development_index.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "city_development_index", + "top_k": 10, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..e5e2339e006dfbe1cf859ce057e8630012b54071 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fa-d9d1-7f33-9686-10160cc650ed"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..85c96454123b54deb8b45dd2cbf46feed041509f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fa-d9d1-7f33-9686-10160cc650ed"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..d04e0fa0a5716a5540bd42fa65141cc83b55a311 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fa-eb0c-78f0-a630-29691ca96142"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"city_development_index\\\",\\n COUNT(*) AS support\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city_development_index\\\"\\nORDER BY support ASC, \\\"city_development_index\\\"\\nLIMIT 10;\",\"notes\":\"Uses the planned Low-Support Group Count template with group_col bound to \\\"city_development_index\\\" and top_k=10.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14662,"cached_input_tokens":13696,"output_tokens":325,"reasoning_output_tokens":226}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..5cb1cccfef51b2b93dccd0ee2a56bd5cee280f12 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_response_attempt_2.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n \"city_development_index\",\n COUNT(*) AS support\nFROM \"m9\"\nGROUP BY \"city_development_index\"\nORDER BY support ASC, \"city_development_index\"\nLIMIT 10;","notes":"Uses the planned Low-Support Group Count template with group_col bound to \"city_development_index\" and top_k=10."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b2ff6a427ef6c731/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..b12615d0962af9b8dbda7e6e771c8c669d6c2d53 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=company_size, condition_col=target. +Result preview: [{"company_size": "1000-4999", "condition_rate": 0.8493975903614458}, {"company_size": "100-500", "condition_rate": 0.838584208479191}, {"company_size": "<10", "condition_rate": 0.8287461773700305}, {"company_size": "500-999", "condition_rate": 0.8266818700114025}, {"company_size": "50-99", "condition_rate": 0.8232241323386312}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..ef3d2394258dbe3e9a621673caacb458638f843f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: focused_target_view +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_m9_b3deab2abab90e4e +-- problem_id: v2p_m9_fc25cf5b12ba0df0 +-- realization_mode: agent +-- source_kind: agent +SELECT "company_size", + AVG(CASE WHEN "target" = '0.0' THEN 1 ELSE 0 END) AS "condition_rate" +FROM "m9" +GROUP BY "company_size" +ORDER BY "condition_rate" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..72c1eb77dd5051507314db7bb306d221ae871734 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"company_size\",\n AVG(CASE WHEN \"target\" = '0.0' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"m9\"\nGROUP BY \"company_size\"\nORDER BY \"condition_rate\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"company_size\\\",\\n AVG(CASE WHEN \\\"target\\\" = '0.0' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"company_size\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\", \"columns\": [\"company_size\", \"condition_rate\"], \"rows\": [{\"company_size\": \"1000-4999\", \"condition_rate\": 0.8493975903614458}, {\"company_size\": \"100-500\", \"condition_rate\": 0.838584208479191}, {\"company_size\": \"<10\", \"condition_rate\": 0.8287461773700305}, {\"company_size\": \"500-999\", \"condition_rate\": 0.8266818700114025}, {\"company_size\": \"50-99\", \"condition_rate\": 0.8232241323386312}, {\"company_size\": \"5000-9999\", \"condition_rate\": 0.8188277087033747}, {\"company_size\": \"10000+\", \"condition_rate\": 0.8093115403665181}, {\"company_size\": \"10/49\", \"condition_rate\": 0.7661454792658056}, {\"company_size\": \"\", \"condition_rate\": 0.5941394408891882}], \"row_count_returned\": 9, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.93}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..3fc78a4fa983945e9ba4b7fb00313b1cbb048aee --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:01:45.579491+00:00", + "ended_at": "2026-05-19T16:01:55.079418+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_b3deab2abab90e4e", + "problem_id": "v2p_m9_fc25cf5b12ba0df0", + "dataset_id": "m9", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=company_size, condition_col=target.", + "bindings": { + "group_col": "company_size", + "condition_col": "target", + "condition_value": "0.0", + "positive_value": "0.0", + "negative_value": "1.0", + "top_k": 13, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/2", + "binding_index=103" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_b3deab2abab90e4e.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_b3deab2abab90e4e", + "api_calls": 0, + "input_tokens": 14711, + "cached_input_tokens": 12032, + "output_tokens": 344, + "total_tokens": 15055, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9485.67, + "sql_execution_elapsed_ms_total": 9.93, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3521f6cb238008b9de3e784ae68596665de88cfc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:01:55.067721+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9485.67, "started_at": "2026-05-19T16:01:45.581271+00:00", "ended_at": "2026-05-19T16:01:55.066968+00:00", "prompt_metrics": {"chars": 9527, "bytes_utf8": 9527, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 416, "bytes_utf8": 416, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14711, "cached_input_tokens": 12032, "output_tokens": 344, "reasoning_output_tokens": 229}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"company_size\\\",\\n AVG(CASE WHEN \\\"target\\\" = '0.0' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"company_size\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Uses the Grouped Condition Rate template with group_col=\\\"company_size\\\" and condition_col=\\\"target\\\", measuring the rate of target='0.0' within each company_size group.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..2917c13a88493e4307a2a0fe33573f04b28c4961 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_b3deab2abab90e4e", + "api_calls": 0, + "input_tokens": 14711, + "cached_input_tokens": 12032, + "output_tokens": 344, + "total_tokens": 15055, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9485.67, + "sql_execution_elapsed_ms_total": 9.93, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b3deab2abab90e4e/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b69e70d76274d9b5/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b69e70d76274d9b5/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..9b48fb873538c36cf1ef9c627155a3553af3aa58 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b69e70d76274d9b5/run_manifest.json @@ -0,0 +1,67 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:05:12.148047+00:00", + "ended_at": "2026-05-19T16:05:19.858679+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_b69e70d76274d9b5", + "problem_id": "v2p_m9_3ec0d3944c8ecd90", + "dataset_id": "m9", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role rare_extreme_view. Focus on group_col=enrolled_university.", + "bindings": { + "group_col": "enrolled_university", + "top_k": 18, + "top_n": 7, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=2/2", + "binding_index=123" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 4, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b69e70d76274d9b5/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b69e70d76274d9b5/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1aa22c4b8e571fcfb2abec32b0579e8624f545ba --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b69e70d76274d9b5/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:05:15.651708+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3500.92, "started_at": "2026-05-19T16:05:12.149839+00:00", "ended_at": "2026-05-19T16:05:15.650787+00:00", "prompt_metrics": {"chars": 9298, "bytes_utf8": 9298, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fb-ec40-7361-91e5-b046f88a4c8b\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:05:19.858590+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3205.09, "started_at": "2026-05-19T16:05:16.652702+00:00", "ended_at": "2026-05-19T16:05:19.857828+00:00", "prompt_metrics": {"chars": 9298, "bytes_utf8": 9298, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fb-fde8-77f3-9597-be7d4d37e2d8\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..5c403642551431831b46344c0ceed0352a2cafed --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "1", "support": 8040, "support_share": 0.419668023802067, "cumulative_support": 8040}, {"value_label": ">4", "support": 3290, "support_share": 0.17172982566029857, "cumulative_support": 11330}, {"value_label": "2", "support": 2900, "support_share": 0.1513727946549744, "cumulative_support": 14230}, {"value_label": "never", "support": 2452, "support_share": 0.1279883077565508, "cumulative_support": 16682}, {"value_label": "4", "support": 1029, "support_share": 0.053711243344816785, "cumulative_support": 17711}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..1a75d55676eeb3c1caf4df56f1dacf9910d43154 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/generated_sql.sql @@ -0,0 +1,28 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: value_imbalance_profile +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_cardinality_distinct_share_profile +-- query_record_id: v2q_m9_b6eb7b4b29101b35 +-- problem_id: v2p_m9_7715b0e8a406c01d +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "last_new_job" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "last_new_job" +), ranked AS ( + SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support + FROM grouped +) +SELECT * +FROM ranked +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..882734d6e5318a6a96d96f9d0a9ddc341a6e53e5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: value_imbalance_profile\n-- variant_semantic_role: ranked_signal_view\n-- template_id: tpl_cardinality_distinct_share_profile\n-- query_record_id: v2q_m9_b6eb7b4b29101b35\n-- problem_id: v2p_m9_7715b0e8a406c01d\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"last_new_job\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"last_new_job\"\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: value_imbalance_profile\\n-- variant_semantic_role: ranked_signal_view\\n-- template_id: tpl_cardinality_distinct_share_profile\\n-- query_record_id: v2q_m9_b6eb7b4b29101b35\\n-- problem_id: v2p_m9_7715b0e8a406c01d\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"last_new_job\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"last_new_job\\\"\\n), ranked AS (\\n SELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\\n FROM grouped\\n)\\nSELECT *\\nFROM ranked\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"cumulative_support\"], \"rows\": [{\"value_label\": \"1\", \"support\": 8040, \"support_share\": 0.419668023802067, \"cumulative_support\": 8040}, {\"value_label\": \">4\", \"support\": 3290, \"support_share\": 0.17172982566029857, \"cumulative_support\": 11330}, {\"value_label\": \"2\", \"support\": 2900, \"support_share\": 0.1513727946549744, \"cumulative_support\": 14230}, {\"value_label\": \"never\", \"support\": 2452, \"support_share\": 0.1279883077565508, \"cumulative_support\": 16682}, {\"value_label\": \"4\", \"support\": 1029, \"support_share\": 0.053711243344816785, \"cumulative_support\": 17711}, {\"value_label\": \"3\", \"support\": 1024, \"support_share\": 0.05345025576782545, \"cumulative_support\": 18735}, {\"value_label\": \"\", \"support\": 423, \"support_share\": 0.02207954901346696, \"cumulative_support\": 19158}], \"row_count_returned\": 7, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 6.69}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..14cc5124b151bdf554ecea1f2178296c3eeaea34 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.245739+00:00", + "ended_at": "2026-05-19T16:08:56.253189+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_b6eb7b4b29101b35", + "problem_id": "v2p_m9_7715b0e8a406c01d", + "dataset_id": "m9", + "template_id": "tpl_cardinality_distinct_share_profile", + "template_name": "Cardinality Distinct Share Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "value_imbalance_profile", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Distinct Share Profile to probe support_rank_profile_consistency with semantic role ranked_signal_view. Focus on group_col=last_new_job.", + "bindings": { + "group_col": "last_new_job" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=10", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 10, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_b6eb7b4b29101b35.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b6eb7b4b29101b35/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..33c03308d499be27880aeeddd58e6560d8312365 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=enrolled_university, measure_col=enrollee_id. +Result preview: [{"enrolled_university": "no_enrollment", "group_value": 229978469.0}, {"enrolled_university": "Full time course", "group_value": 65323820.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..fee605fc26842c1daa5e5380b5ff2a2108f516db --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/generated_sql.sql @@ -0,0 +1,30 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_m9_b79b3e19f722a052 +-- problem_id: v2p_m9_5baf34898230ead5 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "enrolled_university", SUM(CAST("enrollee_id" AS REAL)) AS "group_value" + FROM "m9" + WHERE "enrolled_university" IS NOT NULL + AND "enrolled_university" <> '' + AND "enrollee_id" IS NOT NULL + AND "enrollee_id" <> '' + GROUP BY "enrolled_university" +), total AS ( + SELECT SUM("group_value") AS "total_value" + FROM grouped +) +SELECT g."enrolled_university", g."group_value" +FROM grouped AS g +CROSS JOIN total AS t +WHERE g."group_value" > t."total_value" * 0.1 +ORDER BY g."group_value" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..4bfcc82961c3b7ac40888eaa579542adf1385b52 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold.\nWITH grouped AS (\n SELECT \"enrolled_university\", SUM(CAST(\"enrollee_id\" AS REAL)) AS \"group_value\"\n FROM \"m9\"\n WHERE \"enrolled_university\" IS NOT NULL\n AND \"enrolled_university\" <> ''\n AND \"enrollee_id\" IS NOT NULL\n AND \"enrollee_id\" <> ''\n GROUP BY \"enrolled_university\"\n), total AS (\n SELECT SUM(\"group_value\") AS \"total_value\"\n FROM grouped\n)\nSELECT g.\"enrolled_university\", g.\"group_value\"\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.\"group_value\" > t.\"total_value\" * 0.1\nORDER BY g.\"group_value\" DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold.\\nWITH grouped AS (\\n SELECT \\\"enrolled_university\\\", SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"enrolled_university\\\" IS NOT NULL\\n AND \\\"enrolled_university\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\n GROUP BY \\\"enrolled_university\\\"\\n), total AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM grouped\\n)\\nSELECT g.\\\"enrolled_university\\\", g.\\\"group_value\\\"\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\", \"columns\": [\"enrolled_university\", \"group_value\"], \"rows\": [{\"enrolled_university\": \"no_enrollment\", \"group_value\": 229978469.0}, {\"enrolled_university\": \"Full time course\", \"group_value\": 65323820.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 10.46}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..0693a68f97353b731de24b09399db59cd49c7022 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:47:12.750977+00:00", + "ended_at": "2026-05-19T15:47:35.307267+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_b79b3e19f722a052", + "problem_id": "v2p_m9_5baf34898230ead5", + "dataset_id": "m9", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=enrolled_university, measure_col=enrollee_id.", + "bindings": { + "group_col": "enrolled_university", + "measure_col": "enrollee_id", + "top_k": 10, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/2", + "binding_index=75" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_b79b3e19f722a052.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_b79b3e19f722a052", + "api_calls": 0, + "input_tokens": 14791, + "cached_input_tokens": 13696, + "output_tokens": 1208, + "total_tokens": 15999, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 22538.33, + "sql_execution_elapsed_ms_total": 10.46, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ea0c9bc9d09e55eaac5cd1d2a494ef0d7e48b058 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:47:35.294714+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 22538.33, "started_at": "2026-05-19T15:47:12.755039+00:00", "ended_at": "2026-05-19T15:47:35.293421+00:00", "prompt_metrics": {"chars": 9868, "bytes_utf8": 9868, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 959, "bytes_utf8": 959, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14791, "cached_input_tokens": 13696, "output_tokens": 1208, "reasoning_output_tokens": 945}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold.\\nWITH grouped AS (\\n SELECT \\\"enrolled_university\\\", SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS \\\"group_value\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"enrolled_university\\\" IS NOT NULL\\n AND \\\"enrolled_university\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\n GROUP BY \\\"enrolled_university\\\"\\n), total AS (\\n SELECT SUM(\\\"group_value\\\") AS \\\"total_value\\\"\\n FROM grouped\\n)\\nSELECT g.\\\"enrolled_university\\\", g.\\\"group_value\\\"\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.\\\"group_value\\\" > t.\\\"total_value\\\" * 0.1\\nORDER BY g.\\\"group_value\\\" DESC;\",\"notes\":\"Used the provided relative-to-total threshold template with group_col=\\\"enrolled_university\\\", measure_col=\\\"enrollee_id\\\", and fraction_threshold=0.1. Blank grouped values were filtered out for a stable grouped view, and \\\"enrollee_id\\\" was cast from TEXT to REAL so SQLite can sum it reliably.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..88249ba33148eb97034d7dea2a9aea271b43325e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_b79b3e19f722a052", + "api_calls": 0, + "input_tokens": 14791, + "cached_input_tokens": 13696, + "output_tokens": 1208, + "total_tokens": 15999, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 22538.33, + "sql_execution_elapsed_ms_total": 10.46, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_b79b3e19f722a052/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..1c0574814fc51cdc2246c7172271d65f177e3074 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=education_level, measure_col=city_development_index. +Result preview: [{"education_level": "Phd", "avg_measure": 0.8830700483091788}, {"education_level": "Primary School", "avg_measure": 0.8504188311688312}, {"education_level": "Masters", "avg_measure": 0.8359468011923871}, {"education_level": "High School", "avg_measure": 0.8338899355478433}, {"education_level": "Graduate", "avg_measure": 0.823731246766684}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..2a590d6889c52de893de7aec6d37b191a9852ebc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_m9_bc5870e8544dc5e3 +-- problem_id: v2p_m9_682d2c4f87acc3d6 +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "education_level", + AVG(CAST("city_development_index" AS REAL)) OVER (PARTITION BY "education_level") AS avg_measure +FROM "m9" +WHERE "education_level" IS NOT NULL + AND "education_level" <> '' + AND "city_development_index" IS NOT NULL + AND "city_development_index" <> '' +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b5919ae3d2d55b2defb0889a52e34703a3dbed61 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT \"education_level\",\n AVG(CAST(\"city_development_index\" AS REAL)) OVER (PARTITION BY \"education_level\") AS avg_measure\nFROM \"m9\"\nWHERE \"education_level\" IS NOT NULL\n AND \"education_level\" <> ''\n AND \"city_development_index\" IS NOT NULL\n AND \"city_development_index\" <> ''\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"education_level\\\",\\n AVG(CAST(\\\"city_development_index\\\" AS REAL)) OVER (PARTITION BY \\\"education_level\\\") AS avg_measure\\nFROM \\\"m9\\\"\\nWHERE \\\"education_level\\\" IS NOT NULL\\n AND \\\"education_level\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\nORDER BY avg_measure DESC;\", \"columns\": [\"education_level\", \"avg_measure\"], \"rows\": [{\"education_level\": \"Phd\", \"avg_measure\": 0.8830700483091788}, {\"education_level\": \"Primary School\", \"avg_measure\": 0.8504188311688312}, {\"education_level\": \"Masters\", \"avg_measure\": 0.8359468011923871}, {\"education_level\": \"High School\", \"avg_measure\": 0.8338899355478433}, {\"education_level\": \"Graduate\", \"avg_measure\": 0.823731246766684}], \"row_count_returned\": 5, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 46.15}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..b80fefe5c7308f6a356126c522bee404e5f0e3c8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:07:54.269641+00:00", + "ended_at": "2026-05-19T16:08:11.601682+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_bc5870e8544dc5e3", + "problem_id": "v2p_m9_682d2c4f87acc3d6", + "dataset_id": "m9", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role ranked_signal_view. Focus on group_col=education_level, measure_col=city_development_index.", + "bindings": { + "group_col": "education_level", + "measure_col": "city_development_index", + "top_k": 16, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=2/2", + "binding_index=136" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 5, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_bc5870e8544dc5e3.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_bc5870e8544dc5e3", + "api_calls": 0, + "input_tokens": 14661, + "cached_input_tokens": 13696, + "output_tokens": 538, + "total_tokens": 15199, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16278.58, + "sql_execution_elapsed_ms_total": 46.15, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b9ae741f5595e6cba8fb5409ae85a1dd01cb3dc6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:07:57.465928+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3193.33, "started_at": "2026-05-19T16:07:54.271867+00:00", "ended_at": "2026-05-19T16:07:57.465220+00:00", "prompt_metrics": {"chars": 9408, "bytes_utf8": 9408, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fe-6592-7e80-948c-81c69a53f0dc\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:08:11.553930+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13085.25, "started_at": "2026-05-19T16:07:58.467890+00:00", "ended_at": "2026-05-19T16:08:11.553182+00:00", "prompt_metrics": {"chars": 9408, "bytes_utf8": 9408, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 648, "bytes_utf8": 648, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14661, "cached_input_tokens": 13696, "output_tokens": 538, "reasoning_output_tokens": 382}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"education_level\\\",\\n AVG(CAST(\\\"city_development_index\\\" AS REAL)) OVER (PARTITION BY \\\"education_level\\\") AS avg_measure\\nFROM \\\"m9\\\"\\nWHERE \\\"education_level\\\" IS NOT NULL\\n AND \\\"education_level\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\nORDER BY avg_measure DESC;\",\"notes\":\"Applied the Window Partition Average template with group_col=education_level and measure_col=city_development_index; cast the measure to REAL because the schema stores it as TEXT, and excluded blank/null values for cleaner slice averages.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..c41015d61436c5586ce20f8072dc98c230d960c9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_bc5870e8544dc5e3", + "api_calls": 0, + "input_tokens": 14661, + "cached_input_tokens": 13696, + "output_tokens": 538, + "total_tokens": 15199, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16278.58, + "sql_execution_elapsed_ms_total": 46.15, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bc5870e8544dc5e3/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcbe9cbe9287f27a/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcbe9cbe9287f27a/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..0ad285b1867f4b005d6592f94f0ac27dc2fe9821 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcbe9cbe9287f27a/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:18.987707+00:00", + "ended_at": "2026-05-19T16:08:26.235453+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_bcbe9cbe9287f27a", + "problem_id": "v2p_m9_7af692ef338ed8aa", + "dataset_id": "m9", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe direction_consistency with semantic role filtered_stable_view. Focus on group_col=major_discipline, measure_col=training_hours.", + "bindings": { + "group_col": "major_discipline", + "measure_col": "training_hours", + "top_k": 17, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 70.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=2/2", + "binding_index=137" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 6, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcbe9cbe9287f27a/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcbe9cbe9287f27a/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..33f4724334a5fc6c20bcceb082fb2a86e132aedd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcbe9cbe9287f27a/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:08:22.043077+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3052.34, "started_at": "2026-05-19T16:08:18.989879+00:00", "ended_at": "2026-05-19T16:08:22.042243+00:00", "prompt_metrics": {"chars": 9395, "bytes_utf8": 9395, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fe-c639-7a10-9172-0c04810fc83b\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:08:26.235361+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3189.48, "started_at": "2026-05-19T16:08:23.045032+00:00", "ended_at": "2026-05-19T16:08:26.234565+00:00", "prompt_metrics": {"chars": 9395, "bytes_utf8": 9395, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fe-d60a-7f00-a642-cead5329ff03\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..8d71cc681827039a4924a22094052cc32a05f0f8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=company_type, condition_col=major_discipline. +Result preview: [{"company_type": "Funded Startup", "condition_ratio": 12.5}, {"company_type": "NGO", "condition_ratio": 11.911764705882353}, {"company_type": "Public Sector", "condition_ratio": 9.058823529411764}, {"company_type": "Pvt Ltd", "condition_ratio": 9.028058361391695}, {"company_type": "Early Stage Startup", "condition_ratio": 6.575342465753424}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..fa01d913e9c9f121898595e157f7968ea623c731 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/generated_sql.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_m9_bcf7ab78929086c6 +-- problem_id: v2p_m9_7866485700d585d0 +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "company_type", + SUM(CASE WHEN "major_discipline" = 'STEM' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "major_discipline" = '' THEN 1 ELSE 0 END) AS denominator_count + FROM "m9" + GROUP BY "company_type" +) +SELECT "company_type", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..25d3279e05c680dac596692574e47e7420e99249 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n SELECT \"company_type\",\n SUM(CASE WHEN \"major_discipline\" = 'STEM' THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN \"major_discipline\" = '' THEN 1 ELSE 0 END) AS denominator_count\n FROM \"m9\"\n GROUP BY \"company_type\"\n)\nSELECT \"company_type\",\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"company_type\\\",\\n SUM(CASE WHEN \\\"major_discipline\\\" = 'STEM' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"major_discipline\\\" = '' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"m9\\\"\\n GROUP BY \\\"company_type\\\"\\n)\\nSELECT \\\"company_type\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\", \"columns\": [\"company_type\", \"condition_ratio\"], \"rows\": [{\"company_type\": \"Funded Startup\", \"condition_ratio\": 12.5}, {\"company_type\": \"NGO\", \"condition_ratio\": 11.911764705882353}, {\"company_type\": \"Public Sector\", \"condition_ratio\": 9.058823529411764}, {\"company_type\": \"Pvt Ltd\", \"condition_ratio\": 9.028058361391695}, {\"company_type\": \"Early Stage Startup\", \"condition_ratio\": 6.575342465753424}, {\"company_type\": \"Other\", \"condition_ratio\": 5.866666666666666}, {\"company_type\": \"\", \"condition_ratio\": 2.3529411764705883}], \"row_count_returned\": 7, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 10.74}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..7d323d23754140625f696bc2a1fe384e5d58bbb2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:41:55.400849+00:00", + "ended_at": "2026-05-19T15:42:05.847286+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_bcf7ab78929086c6", + "problem_id": "v2p_m9_7866485700d585d0", + "dataset_id": "m9", + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "contrastive_conditional_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=company_type, condition_col=major_discipline.", + "bindings": { + "group_col": "company_type", + "condition_col": "major_discipline", + "condition_value": "STEM", + "positive_value": "STEM", + "negative_value": "", + "top_k": 14, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=9", + "sql_variant_index=1/1", + "binding_index=44" + ], + "template_selection_mode": "rule", + "selected_template_rank": 4, + "problem_index_within_template": 9, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_bcf7ab78929086c6.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_bcf7ab78929086c6", + "api_calls": 0, + "input_tokens": 14857, + "cached_input_tokens": 13696, + "output_tokens": 502, + "total_tokens": 15359, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10428.59, + "sql_execution_elapsed_ms_total": 10.74, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..bb71f4b8af9607b272f11c6d1d6df3e08cfab992 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:42:05.834781+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10428.59, "started_at": "2026-05-19T15:41:55.405158+00:00", "ended_at": "2026-05-19T15:42:05.833792+00:00", "prompt_metrics": {"chars": 10116, "bytes_utf8": 10116, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 718, "bytes_utf8": 718, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14857, "cached_input_tokens": 13696, "output_tokens": 502, "reasoning_output_tokens": 320}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"company_type\\\",\\n SUM(CASE WHEN \\\"major_discipline\\\" = 'STEM' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"major_discipline\\\" = '' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"m9\\\"\\n GROUP BY \\\"company_type\\\"\\n)\\nSELECT \\\"company_type\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Uses the planned grouped ratio template with group_col=\\\"company_type\\\" and condition_col=\\\"major_discipline\\\", computing the ratio of STEM rows to empty-string major_discipline rows per company_type.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..919987464a01943703ba052cb49f65d7f7ad04fb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_bcf7ab78929086c6", + "api_calls": 0, + "input_tokens": 14857, + "cached_input_tokens": 13696, + "output_tokens": 502, + "total_tokens": 15359, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10428.59, + "sql_execution_elapsed_ms_total": 10.74, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bcf7ab78929086c6/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..705376ed3b0379bf6e04fef693b1a5bcf0327553 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=relevent_experience, measure_col=training_hours. +Result preview: [{"relevent_experience": "No relevent experience", "percentile_measure": 190.0}, {"relevent_experience": "Has relevent experience", "percentile_measure": 188.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..d8321040801a69c013971a15b1a8076213f5bb31 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/generated_sql.sql @@ -0,0 +1,73 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: focused_target_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_m9_bd3f35e44639dce9 +-- problem_id: v2p_m9_dfc16293b2639c9e +-- realization_mode: agent +-- source_kind: agent +WITH "base" AS ( + SELECT + "relevent_experience" AS "group_col", + CAST("training_hours" AS REAL) AS "measure" + FROM "m9" + WHERE "training_hours" IS NOT NULL + AND TRIM("training_hours") <> '' + AND "relevent_experience" IS NOT NULL + AND TRIM("relevent_experience") <> '' +), +"ordered" AS ( + SELECT + "group_col", + "measure", + ROW_NUMBER() OVER ( + PARTITION BY "group_col" + ORDER BY "measure" + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "group_col" + ) AS "cnt" + FROM "base" +), +"pos" AS ( + SELECT DISTINCT + "group_col", + 1.0 + ("cnt" - 1) * 0.95 AS "pos", + CAST(1.0 + ("cnt" - 1) * 0.95 AS INTEGER) AS "lower_rn", + CASE + WHEN 1.0 + ("cnt" - 1) * 0.95 = CAST(1.0 + ("cnt" - 1) * 0.95 AS INTEGER) + THEN CAST(1.0 + ("cnt" - 1) * 0.95 AS INTEGER) + ELSE CAST(1.0 + ("cnt" - 1) * 0.95 AS INTEGER) + 1 + END AS "upper_rn" + FROM "ordered" +), +"bounds" AS ( + SELECT + "pos"."group_col", + "pos"."pos", + "pos"."lower_rn", + "pos"."upper_rn", + MAX(CASE WHEN "ordered"."rn" = "pos"."lower_rn" THEN "ordered"."measure" END) AS "lower_val", + MAX(CASE WHEN "ordered"."rn" = "pos"."upper_rn" THEN "ordered"."measure" END) AS "upper_val" + FROM "pos" + JOIN "ordered" + ON "ordered"."group_col" = "pos"."group_col" + GROUP BY + "pos"."group_col", + "pos"."pos", + "pos"."lower_rn", + "pos"."upper_rn" +) +SELECT + "group_col" AS "relevent_experience", + CASE + WHEN "lower_rn" = "upper_rn" THEN "lower_val" + ELSE "lower_val" + ("pos" - "lower_rn") * ("upper_val" - "lower_val") + END AS "percentile_measure" +FROM "bounds" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d11ba919934723b9096656173bb73918bb253441 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"base\" AS (\n SELECT\n \"relevent_experience\" AS \"group_col\",\n CAST(\"training_hours\" AS REAL) AS \"measure\"\n FROM \"m9\"\n WHERE \"training_hours\" IS NOT NULL\n AND TRIM(\"training_hours\") <> ''\n AND \"relevent_experience\" IS NOT NULL\n AND TRIM(\"relevent_experience\") <> ''\n),\n\"ordered\" AS (\n SELECT\n \"group_col\",\n \"measure\",\n ROW_NUMBER() OVER (\n PARTITION BY \"group_col\"\n ORDER BY \"measure\"\n ) AS \"rn\",\n COUNT(*) OVER (\n PARTITION BY \"group_col\"\n ) AS \"cnt\"\n FROM \"base\"\n),\n\"pos\" AS (\n SELECT DISTINCT\n \"group_col\",\n 1.0 + (\"cnt\" - 1) * 0.95 AS \"pos\",\n CAST(1.0 + (\"cnt\" - 1) * 0.95 AS INTEGER) AS \"lower_rn\",\n CASE\n WHEN 1.0 + (\"cnt\" - 1) * 0.95 = CAST(1.0 + (\"cnt\" - 1) * 0.95 AS INTEGER)\n THEN CAST(1.0 + (\"cnt\" - 1) * 0.95 AS INTEGER)\n ELSE CAST(1.0 + (\"cnt\" - 1) * 0.95 AS INTEGER) + 1\n END AS \"upper_rn\"\n FROM \"ordered\"\n),\n\"bounds\" AS (\n SELECT\n \"pos\".\"group_col\",\n \"pos\".\"pos\",\n \"pos\".\"lower_rn\",\n \"pos\".\"upper_rn\",\n MAX(CASE WHEN \"ordered\".\"rn\" = \"pos\".\"lower_rn\" THEN \"ordered\".\"measure\" END) AS \"lower_val\",\n MAX(CASE WHEN \"ordered\".\"rn\" = \"pos\".\"upper_rn\" THEN \"ordered\".\"measure\" END) AS \"upper_val\"\n FROM \"pos\"\n JOIN \"ordered\"\n ON \"ordered\".\"group_col\" = \"pos\".\"group_col\"\n GROUP BY\n \"pos\".\"group_col\",\n \"pos\".\"pos\",\n \"pos\".\"lower_rn\",\n \"pos\".\"upper_rn\"\n)\nSELECT\n \"group_col\" AS \"relevent_experience\",\n CASE\n WHEN \"lower_rn\" = \"upper_rn\" THEN \"lower_val\"\n ELSE \"lower_val\" + (\"pos\" - \"lower_rn\") * (\"upper_val\" - \"lower_val\")\n END AS \"percentile_measure\"\nFROM \"bounds\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"base\\\" AS (\\n SELECT\\n \\\"relevent_experience\\\" AS \\\"group_col\\\",\\n CAST(\\\"training_hours\\\" AS REAL) AS \\\"measure\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"training_hours\\\" IS NOT NULL\\n AND TRIM(\\\"training_hours\\\") <> ''\\n AND \\\"relevent_experience\\\" IS NOT NULL\\n AND TRIM(\\\"relevent_experience\\\") <> ''\\n),\\n\\\"ordered\\\" AS (\\n SELECT\\n \\\"group_col\\\",\\n \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"group_col\\\"\\n ORDER BY \\\"measure\\\"\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"group_col\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"base\\\"\\n),\\n\\\"pos\\\" AS (\\n SELECT DISTINCT\\n \\\"group_col\\\",\\n 1.0 + (\\\"cnt\\\" - 1) * 0.95 AS \\\"pos\\\",\\n CAST(1.0 + (\\\"cnt\\\" - 1) * 0.95 AS INTEGER) AS \\\"lower_rn\\\",\\n CASE\\n WHEN 1.0 + (\\\"cnt\\\" - 1) * 0.95 = CAST(1.0 + (\\\"cnt\\\" - 1) * 0.95 AS INTEGER)\\n THEN CAST(1.0 + (\\\"cnt\\\" - 1) * 0.95 AS INTEGER)\\n ELSE CAST(1.0 + (\\\"cnt\\\" - 1) * 0.95 AS INTEGER) + 1\\n END AS \\\"upper_rn\\\"\\n FROM \\\"ordered\\\"\\n),\\n\\\"bounds\\\" AS (\\n SELECT\\n \\\"pos\\\".\\\"group_col\\\",\\n \\\"pos\\\".\\\"pos\\\",\\n \\\"pos\\\".\\\"lower_rn\\\",\\n \\\"pos\\\".\\\"upper_rn\\\",\\n MAX(CASE WHEN \\\"ordered\\\".\\\"rn\\\" = \\\"pos\\\".\\\"lower_rn\\\" THEN \\\"ordered\\\".\\\"measure\\\" END) AS \\\"lower_val\\\",\\n MAX(CASE WHEN \\\"ordered\\\".\\\"rn\\\" = \\\"pos\\\".\\\"upper_rn\\\" THEN \\\"ordered\\\".\\\"measure\\\" END) AS \\\"upper_val\\\"\\n FROM \\\"pos\\\"\\n JOIN \\\"ordered\\\"\\n ON \\\"ordered\\\".\\\"group_col\\\" = \\\"pos\\\".\\\"group_col\\\"\\n GROUP BY\\n \\\"pos\\\".\\\"group_col\\\",\\n \\\"pos\\\".\\\"pos\\\",\\n \\\"pos\\\".\\\"lower_rn\\\",\\n \\\"pos\\\".\\\"upper_rn\\\"\\n)\\nSELECT\\n \\\"group_col\\\" AS \\\"relevent_experience\\\",\\n CASE\\n WHEN \\\"lower_rn\\\" = \\\"upper_rn\\\" THEN \\\"lower_val\\\"\\n ELSE \\\"lower_val\\\" + (\\\"pos\\\" - \\\"lower_rn\\\") * (\\\"upper_val\\\" - \\\"lower_val\\\")\\n END AS \\\"percentile_measure\\\"\\nFROM \\\"bounds\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"relevent_experience\", \"percentile_measure\"], \"rows\": [{\"relevent_experience\": \"No relevent experience\", \"percentile_measure\": 190.0}, {\"relevent_experience\": \"Has relevent experience\", \"percentile_measure\": 188.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 94.04}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..b7d1d0fcf1a9e67e270fdeae43c7f04337fcc39a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:53:00.332865+00:00", + "ended_at": "2026-05-19T15:53:52.439884+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_bd3f35e44639dce9", + "problem_id": "v2p_m9_dfc16293b2639c9e", + "dataset_id": "m9", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=relevent_experience, measure_col=training_hours.", + "bindings": { + "group_col": "relevent_experience", + "measure_col": "training_hours", + "top_k": 11, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=1/2", + "binding_index=86" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_bd3f35e44639dce9.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_bd3f35e44639dce9", + "api_calls": 0, + "input_tokens": 14689, + "cached_input_tokens": 13696, + "output_tokens": 3624, + "total_tokens": 18313, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 51005.25, + "sql_execution_elapsed_ms_total": 94.04, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..173786a04400c2cb0327db0ae465dde26a9c3844 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:53:03.902817+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3566.64, "started_at": "2026-05-19T15:53:00.334602+00:00", "ended_at": "2026-05-19T15:53:03.901274+00:00", "prompt_metrics": {"chars": 9494, "bytes_utf8": 9494, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f0-c1b2-7ac2-ac05-62503dbe6483\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:53:52.344125+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 47438.61, "started_at": "2026-05-19T15:53:04.904564+00:00", "ended_at": "2026-05-19T15:53:52.343221+00:00", "prompt_metrics": {"chars": 9494, "bytes_utf8": 9494, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 2224, "bytes_utf8": 2224, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14689, "cached_input_tokens": 13696, "output_tokens": 3624, "reasoning_output_tokens": 2895}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"base\\\" AS (\\n SELECT\\n \\\"relevent_experience\\\" AS \\\"group_col\\\",\\n CAST(\\\"training_hours\\\" AS REAL) AS \\\"measure\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"training_hours\\\" IS NOT NULL\\n AND TRIM(\\\"training_hours\\\") <> ''\\n AND \\\"relevent_experience\\\" IS NOT NULL\\n AND TRIM(\\\"relevent_experience\\\") <> ''\\n),\\n\\\"ordered\\\" AS (\\n SELECT\\n \\\"group_col\\\",\\n \\\"measure\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"group_col\\\"\\n ORDER BY \\\"measure\\\"\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"group_col\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"base\\\"\\n),\\n\\\"pos\\\" AS (\\n SELECT DISTINCT\\n \\\"group_col\\\",\\n 1.0 + (\\\"cnt\\\" - 1) * 0.95 AS \\\"pos\\\",\\n CAST(1.0 + (\\\"cnt\\\" - 1) * 0.95 AS INTEGER) AS \\\"lower_rn\\\",\\n CASE\\n WHEN 1.0 + (\\\"cnt\\\" - 1) * 0.95 = CAST(1.0 + (\\\"cnt\\\" - 1) * 0.95 AS INTEGER)\\n THEN CAST(1.0 + (\\\"cnt\\\" - 1) * 0.95 AS INTEGER)\\n ELSE CAST(1.0 + (\\\"cnt\\\" - 1) * 0.95 AS "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..ad12ae4b409136ae93cd0adfc68a9c9ba0bf34d7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_bd3f35e44639dce9", + "api_calls": 0, + "input_tokens": 14689, + "cached_input_tokens": 13696, + "output_tokens": 3624, + "total_tokens": 18313, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 51005.25, + "sql_execution_elapsed_ms_total": 94.04, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd3f35e44639dce9/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..8ee78ebb93e829a9729ab0ffdd77b7c706e410b7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=company_size. +Result preview: [{"company_size": "", "row_count": 5938}, {"company_size": "50-99", "row_count": 3083}, {"company_size": "100-500", "row_count": 2571}, {"company_size": "10000+", "row_count": 2019}, {"company_size": "10/49", "row_count": 1471}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..51969246069ab669f65f15ac69c0a9ea8ff6c00a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: subgroup_size_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: count_distribution +-- template_id: tpl_clickbench_group_count +-- query_record_id: v2q_m9_bd949a989eb0fbf6 +-- problem_id: v2p_m9_906eaba230eb1ed8 +-- realization_mode: agent +-- source_kind: agent +SELECT "company_size", COUNT(*) AS "row_count" +FROM "m9" +GROUP BY "company_size" +ORDER BY "row_count" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0dd06272cf41e05e647133deaee71d772e4b5a5b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_clickbench_group_count\nSELECT \"company_size\", COUNT(*) AS \"row_count\"\nFROM \"m9\"\nGROUP BY \"company_size\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"company_size\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"company_size\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"company_size\", \"row_count\"], \"rows\": [{\"company_size\": \"\", \"row_count\": 5938}, {\"company_size\": \"50-99\", \"row_count\": 3083}, {\"company_size\": \"100-500\", \"row_count\": 2571}, {\"company_size\": \"10000+\", \"row_count\": 2019}, {\"company_size\": \"10/49\", \"row_count\": 1471}, {\"company_size\": \"1000-4999\", \"row_count\": 1328}, {\"company_size\": \"<10\", \"row_count\": 1308}, {\"company_size\": \"500-999\", \"row_count\": 877}, {\"company_size\": \"5000-9999\", \"row_count\": 563}], \"row_count_returned\": 9, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 8.06}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..c215d72b9042099049e243a9c217986137ac3cd5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:33:34.675067+00:00", + "ended_at": "2026-05-19T15:33:49.227633+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_bd949a989eb0fbf6", + "problem_id": "v2p_m9_906eaba230eb1ed8", + "dataset_id": "m9", + "template_id": "tpl_clickbench_group_count", + "template_name": "Grouped Count by Category", + "family_id": "subgroup_structure", + "canonical_subitem_id": "subgroup_size_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=company_size.", + "bindings": { + "group_col": "company_size", + "top_k": 14, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=1/1", + "binding_index=19" + ], + "template_selection_mode": "rule", + "selected_template_rank": 2, + "problem_index_within_template": 8, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_bd949a989eb0fbf6.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_bd949a989eb0fbf6", + "api_calls": 0, + "input_tokens": 14619, + "cached_input_tokens": 12032, + "output_tokens": 409, + "total_tokens": 15028, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14538.72, + "sql_execution_elapsed_ms_total": 8.06, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6e20bf97f6bdcfa420a66c88502c37676b575f81 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:33:49.217938+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 14538.72, "started_at": "2026-05-19T15:33:34.678416+00:00", "ended_at": "2026-05-19T15:33:49.217172+00:00", "prompt_metrics": {"chars": 9198, "bytes_utf8": 9198, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 277, "bytes_utf8": 277, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14619, "cached_input_tokens": 12032, "output_tokens": 409, "reasoning_output_tokens": 333}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"company_size\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"company_size\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Uses the grouped count template with group_col bound to company_size on the single table m9.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..9d881b2a892ebdb524f47e8e285de06a6b7698bc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_bd949a989eb0fbf6", + "api_calls": 0, + "input_tokens": 14619, + "cached_input_tokens": 12032, + "output_tokens": 409, + "total_tokens": 15028, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14538.72, + "sql_execution_elapsed_ms_total": 8.06, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bd949a989eb0fbf6/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3ef51d7af37267e3ad6e6eb1a03ef981169789cf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=relevent_experience, measure_col=training_hours. +Result preview: [{"relevent_experience": "Has relevent experience", "group_value": 907516.0}, {"relevent_experience": "No relevent experience", "group_value": 344783.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..db58a19996743edd2ac96701f5154911a8f57e65 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: count_distribution +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_m9_bf64a03d304de7f8 +-- problem_id: v2p_m9_f5c2d17c0a2d3d8b +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "relevent_experience", SUM(CAST(NULLIF("training_hours", '') AS REAL)) AS group_value + FROM "m9" + GROUP BY "relevent_experience" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT g."relevent_experience", g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.1 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..e5a9b6dccfe0ce9a3f54494aad267b3d2140fe65 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT \"relevent_experience\", SUM(CAST(NULLIF(\"training_hours\", '') AS REAL)) AS group_value\n FROM \"m9\"\n GROUP BY \"relevent_experience\"\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.\"relevent_experience\", g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.1\nORDER BY g.group_value DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"relevent_experience\\\", SUM(CAST(NULLIF(\\\"training_hours\\\", '') AS REAL)) AS group_value\\n FROM \\\"m9\\\"\\n GROUP BY \\\"relevent_experience\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"relevent_experience\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\", \"columns\": [\"relevent_experience\", \"group_value\"], \"rows\": [{\"relevent_experience\": \"Has relevent experience\", \"group_value\": 907516.0}, {\"relevent_experience\": \"No relevent experience\", \"group_value\": 344783.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.71}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..ace9c65dc8de32fa7ef45109dacd79f525e0da21 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:46:42.802505+00:00", + "ended_at": "2026-05-19T15:46:53.510581+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_bf64a03d304de7f8", + "problem_id": "v2p_m9_f5c2d17c0a2d3d8b", + "dataset_id": "m9", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=relevent_experience, measure_col=training_hours.", + "bindings": { + "group_col": "relevent_experience", + "measure_col": "training_hours", + "top_k": 14, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=1/2", + "binding_index=74" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_bf64a03d304de7f8.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_bf64a03d304de7f8", + "api_calls": 0, + "input_tokens": 14787, + "cached_input_tokens": 13696, + "output_tokens": 526, + "total_tokens": 15313, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10692.73, + "sql_execution_elapsed_ms_total": 9.71, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2a6c2ec61f3fd120a275a7f59adea40f460c5bd2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:46:53.499016+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 10692.73, "started_at": "2026-05-19T15:46:42.805319+00:00", "ended_at": "2026-05-19T15:46:53.498082+00:00", "prompt_metrics": {"chars": 9869, "bytes_utf8": 9869, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 718, "bytes_utf8": 718, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14787, "cached_input_tokens": 13696, "output_tokens": 526, "reasoning_output_tokens": 338}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT \\\"relevent_experience\\\", SUM(CAST(NULLIF(\\\"training_hours\\\", '') AS REAL)) AS group_value\\n FROM \\\"m9\\\"\\n GROUP BY \\\"relevent_experience\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT g.\\\"relevent_experience\\\", g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.1\\nORDER BY g.group_value DESC;\",\"notes\":\"Uses the planned Relative-to-Total Extreme Threshold template with group_col=\\\"relevent_experience\\\" and measure_col=\\\"training_hours\\\". \\\"training_hours\\\" is cast from TEXT to REAL with NULLIF to ignore blank values during SUM.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..9d4f8fc8fec52901af81be593017f6221376f41d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_bf64a03d304de7f8", + "api_calls": 0, + "input_tokens": 14787, + "cached_input_tokens": 13696, + "output_tokens": 526, + "total_tokens": 15313, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10692.73, + "sql_execution_elapsed_ms_total": 9.71, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_bf64a03d304de7f8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..0ad043b1c5d9f1216694aeb0c085deab33e3d8dc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9213, "bytes_utf8": 9213, "lines": 262, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 293, "bytes_utf8": 293, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14624, "cached_input_tokens": 12032, "output_tokens": 406, "reasoning_output_tokens": 320}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..36ac4f759769a40dca668f5800c9ce5987888d37 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_c32f5fd069b9d3b5", + "api_calls": 0, + "input_tokens": 14624, + "cached_input_tokens": 12032, + "output_tokens": 406, + "total_tokens": 15030, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 18904.54, + "sql_execution_elapsed_ms_total": 7.67, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..c10f08be81ce46c4b66e600a52d9427fb95a7f10 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:32:31.154705+00:00", + "ended_at": "2026-05-19T15:32:50.059274+00:00", + "elapsed_ms": 18904.54, + "prompt_metrics": { + "chars": 9213, + "bytes_utf8": 9213, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1650, + "bytes_utf8": 1650, + "lines": 7, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 293, + "bytes_utf8": 293, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14624, + "cached_input_tokens": 12032, + "output_tokens": 406, + "reasoning_output_tokens": 320 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..707f92675b27814eb907aca77ed488bf5f14f51d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_clickbench_group_count", + "template_name": "Grouped Count by Category", + "primary_family": "subgroup_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Count by Category to probe subgroup_size_stability with semantic role count_distribution. Focus on group_col=relevent_experience.", + "planned_template_id": "tpl_clickbench_group_count", + "bindings": { + "group_col": "relevent_experience", + "top_k": 14, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, COUNT(*) AS row_count\nFROM {table}\nGROUP BY {group_col}\nORDER BY row_count DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..ac97f26e491ce35058c0afdc3bfd8469baa48e37 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,7 @@ +{"type":"thread.started","thread_id":"019e40de-003a-7031-b047-a1281693a703"} +{"type":"turn.started"} +{"type":"error","message":"Reconnecting... 2/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1992913, Requested 15259. Please try again in 245ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"error","message":"Reconnecting... 3/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1994491, Requested 15259. Please try again in 292ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"error","message":"Reconnecting... 4/5 (stream disconnected before completion: Rate limit reached for gpt-5.4 in organization org-yXK0mBGOR7eXhtGEx8v7e3bf on tokens per min (TPM): Limit 2000000, Used 1988642, Requested 15259. Please try again in 117ms. Visit https://platform.openai.com/account/rate-limits to learn more.)"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_clickbench_group_count\\nSELECT \\\"relevent_experience\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"relevent_experience\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Uses the grouped count template with \\\"relevent_experience\\\" as the grouping column on \\\"m9\\\".\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14624,"cached_input_tokens":12032,"output_tokens":406,"reasoning_output_tokens":320}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..0ecfe21906ee5fa71b6800011b975b101094af29 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_clickbench_group_count\nSELECT \"relevent_experience\", COUNT(*) AS \"row_count\"\nFROM \"m9\"\nGROUP BY \"relevent_experience\"\nORDER BY \"row_count\" DESC;","notes":"Uses the grouped count template with \"relevent_experience\" as the grouping column on \"m9\"."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c32f5fd069b9d3b5/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..a57b5e2b8cbc82e9f5b2c64a3c6d950cce774f50 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=major_discipline, measure_col=training_hours. +Result preview: [{"major_discipline": "STEM", "total_measure": 944971.0}, {"major_discipline": "", "total_measure": 187324.0}, {"major_discipline": "Humanities", "total_measure": 43910.0}, {"major_discipline": "Other", "total_measure": 25165.0}, {"major_discipline": "Business Degree", "total_measure": 21644.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..e29ab1abc642a5a58fbaf897de8e4568d8042806 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_m9_c3a90fe24a3ab805 +-- problem_id: v2p_m9_1572e0bb99d6ab88 +-- realization_mode: agent +-- source_kind: agent +SELECT "major_discipline", SUM(CAST(NULLIF("training_hours", '') AS REAL)) AS "total_measure" +FROM "m9" +GROUP BY "major_discipline" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..97877316f2d138c6b0b029da6f8b21fbe499b20d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"major_discipline\", SUM(CAST(NULLIF(\"training_hours\", '') AS REAL)) AS \"total_measure\"\nFROM \"m9\"\nGROUP BY \"major_discipline\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"major_discipline\\\", SUM(CAST(NULLIF(\\\"training_hours\\\", '') AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"major_discipline\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"major_discipline\", \"total_measure\"], \"rows\": [{\"major_discipline\": \"STEM\", \"total_measure\": 944971.0}, {\"major_discipline\": \"\", \"total_measure\": 187324.0}, {\"major_discipline\": \"Humanities\", \"total_measure\": 43910.0}, {\"major_discipline\": \"Other\", \"total_measure\": 25165.0}, {\"major_discipline\": \"Business Degree\", \"total_measure\": 21644.0}, {\"major_discipline\": \"Arts\", \"total_measure\": 15249.0}, {\"major_discipline\": \"No Major\", \"total_measure\": 14036.0}], \"row_count_returned\": 7, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 21.43}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..008019f2da3a0e4e1ecefa20e7235fe43daa48f7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:30:47.059822+00:00", + "ended_at": "2026-05-19T15:31:03.459950+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_c3a90fe24a3ab805", + "problem_id": "v2p_m9_1572e0bb99d6ab88", + "dataset_id": "m9", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=major_discipline, measure_col=training_hours.", + "bindings": { + "group_col": "major_discipline", + "measure_col": "training_hours", + "top_k": 15, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 70.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=6", + "sql_variant_index=2/2", + "binding_index=5" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 6, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_c3a90fe24a3ab805.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_c3a90fe24a3ab805", + "api_calls": 0, + "input_tokens": 14648, + "cached_input_tokens": 13696, + "output_tokens": 444, + "total_tokens": 15092, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16371.89, + "sql_execution_elapsed_ms_total": 21.43, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..cc495f66ed2e3bc1bc9d006160fd8af5610c98c5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:31:03.435402+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 16371.89, "started_at": "2026-05-19T15:30:47.061787+00:00", "ended_at": "2026-05-19T15:31:03.433717+00:00", "prompt_metrics": {"chars": 9311, "bytes_utf8": 9311, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 459, "bytes_utf8": 459, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14648, "cached_input_tokens": 13696, "output_tokens": 444, "reasoning_output_tokens": 324}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"major_discipline\\\", SUM(CAST(NULLIF(\\\"training_hours\\\", '') AS REAL)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"major_discipline\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Used the requested Grouped Numeric Sum template with group_col=\\\"major_discipline\\\" and measure_col=\\\"training_hours\\\". Casted \\\"training_hours\\\" to REAL and applied NULLIF(..., '') so empty text values are ignored in the sum.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..157f148c10f8d85f801bbaff599a682fea9d6142 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_c3a90fe24a3ab805", + "api_calls": 0, + "input_tokens": 14648, + "cached_input_tokens": 13696, + "output_tokens": 444, + "total_tokens": 15092, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16371.89, + "sql_execution_elapsed_ms_total": 21.43, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3a90fe24a3ab805/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..ffe9a0dc7697a789c23297169cdd65e5066285a5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:03:34.208479+00:00", + "ended_at": "2026-05-19T16:03:37.282698+00:00", + "elapsed_ms": 3074.2, + "returncode": 1, + "prompt_metrics": { + "chars": 9228, + "bytes_utf8": 9228, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..1eb305873345fd56f0929b43145ee76a8536b5a9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:03:38.284223+00:00", + "ended_at": "2026-05-19T16:03:42.941602+00:00", + "elapsed_ms": 4657.34, + "returncode": 1, + "prompt_metrics": { + "chars": 9228, + "bytes_utf8": 9228, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..2a2a985b1d9368d55722911ec9c99b3f5d50ede6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "required_roles": [ + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=enrollee_id.", + "planned_template_id": "tpl_threshold_rarity_cdf", + "bindings": { + "measure_col": "enrollee_id", + "top_k": 14, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..2a2a985b1d9368d55722911ec9c99b3f5d50ede6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_threshold_rarity_cdf", + "template_name": "Threshold Rarity CDF", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};", + "required_roles": [ + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Threshold Rarity CDF to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=enrollee_id.", + "planned_template_id": "tpl_threshold_rarity_cdf", + "bindings": { + "measure_col": "enrollee_id", + "top_k": 14, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT AVG(CASE WHEN {measure_col} <= {measure_threshold} THEN 1 ELSE 0 END) AS empirical_cdf_at_threshold\nFROM {table};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..d6a639024ce091a8837a29ae5d9ab05eb9c416bc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fa-6dea-7470-b016-340d421ed37c"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..31ec5b2cc1ef6f6c3828b63ccda040de168aaa7c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fa-6dea-7470-b016-340d421ed37c"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..dc4e67fe387d9b9cc491836b0b135252f986ba52 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fa-7d95-74d3-be5b-e83d50a49bc8"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..6b84039f5f9c3db40062da37b0c4bea88b372b9d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fa-7d95-74d3-be5b-e83d50a49bc8"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c3fb18c7d4efbfdd/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..29b673a2ed233d0beabfc93392243a25b320404c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"relevent_experience": "Has relevent experience", "total_rows": 13792, "missing_rows": 0, "missing_rate": 0.0}, {"relevent_experience": "No relevent experience", "total_rows": 5366, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..339c8a68b612668b89627df068ed6b5f14c1914a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: co_missingness_pattern_consistency +-- intended_facet_id: missing_target_interaction +-- variant_semantic_role: missing_target_interaction +-- template_id: tpl_missing_target_interaction +-- query_record_id: v2q_m9_c5034e2016642ca3 +-- problem_id: v2p_m9_eaa6cd9e9f04273d +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "relevent_experience", + COUNT(*) AS total_rows, + SUM(CASE WHEN "enrolled_university" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "enrolled_university" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9" +GROUP BY "relevent_experience" +ORDER BY missing_rate DESC, total_rows DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d12a1b8cea20325ce3cdc37b8eb03b912fa24ed0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: co_missingness_pattern_consistency\n-- intended_facet_id: missing_target_interaction\n-- variant_semantic_role: missing_target_interaction\n-- template_id: tpl_missing_target_interaction\n-- query_record_id: v2q_m9_c5034e2016642ca3\n-- problem_id: v2p_m9_eaa6cd9e9f04273d\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"relevent_experience\",\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"enrolled_university\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"enrolled_university\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\"\nGROUP BY \"relevent_experience\"\nORDER BY missing_rate DESC, total_rows DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: co_missingness_pattern_consistency\\n-- intended_facet_id: missing_target_interaction\\n-- variant_semantic_role: missing_target_interaction\\n-- template_id: tpl_missing_target_interaction\\n-- query_record_id: v2q_m9_c5034e2016642ca3\\n-- problem_id: v2p_m9_eaa6cd9e9f04273d\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"relevent_experience\\\",\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"enrolled_university\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"enrolled_university\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"relevent_experience\\\"\\nORDER BY missing_rate DESC, total_rows DESC;\", \"columns\": [\"relevent_experience\", \"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"relevent_experience\": \"Has relevent experience\", \"total_rows\": 13792, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"relevent_experience\": \"No relevent experience\", \"total_rows\": 5366, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.39}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..1c25cc9bb7b86602806a40bedde58cc6a4f0e606 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/run_manifest.json @@ -0,0 +1,59 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.077819+00:00", + "ended_at": "2026-05-19T16:08:56.088116+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_c5034e2016642ca3", + "problem_id": "v2p_m9_eaa6cd9e9f04273d", + "dataset_id": "m9", + "template_id": "tpl_missing_target_interaction", + "template_name": "Missingness-Target Interaction", + "family_id": "missingness_structure", + "canonical_subitem_id": "co_missingness_pattern_consistency", + "intended_facet_id": "missing_target_interaction", + "variant_semantic_role": "missing_target_interaction", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Missingness-Target Interaction to probe co_missingness_pattern_consistency with semantic role missing_target_interaction. Focus on target_col=relevent_experience, missing_col=enrolled_university.", + "bindings": { + "missing_col": "enrolled_university", + "target_col": "relevent_experience" + }, + "binding_roles": [ + "missing_col", + "target_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {target_col},\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {target_col}\nORDER BY missing_rate DESC, total_rows DESC;", + "notes": [ + "default_facets=missing_rate_by_subgroup,missing_target_interaction", + "template_selection_mode=deterministic", + "problem_index_within_template=3", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_c5034e2016642ca3.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5034e2016642ca3/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..f476d446050df2a5108bc37fb36702ddb4f516de --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=training_hours. +Result preview: [{"training_hours": 336.0}, {"training_hours": 336.0}, {"training_hours": 336.0}, {"training_hours": 336.0}, {"training_hours": 336.0}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..8c09db4524ad36d9651f178c2d7cb4488f9ed570 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/generated_sql.sql @@ -0,0 +1,26 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_m4_quantile_tail_slice +-- query_record_id: v2q_m9_c51df929d8943233 +-- problem_id: v2p_m9_2fabf2b06ac3ecb7 +-- realization_mode: agent +-- source_kind: agent +WITH "buckets" AS ( + SELECT + CAST(NULLIF("training_hours", '') AS REAL) AS "training_hours", + NTILE(10) OVER ( + ORDER BY CAST(NULLIF("training_hours", '') AS REAL) DESC + ) AS "tail_bucket" + FROM "m9" + WHERE NULLIF("training_hours", '') IS NOT NULL +) +SELECT "training_hours" +FROM "buckets" +WHERE "tail_bucket" = 1 +ORDER BY "training_hours" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..fa8bbb6a670e3ab49192e280fcd110a4eda9efa5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_quantile_tail_slice\nWITH \"buckets\" AS (\n SELECT\n CAST(NULLIF(\"training_hours\", '') AS REAL) AS \"training_hours\",\n NTILE(10) OVER (\n ORDER BY CAST(NULLIF(\"training_hours\", '') AS REAL) DESC\n ) AS \"tail_bucket\"\n FROM \"m9\"\n WHERE NULLIF(\"training_hours\", '') IS NOT NULL\n)\nSELECT \"training_hours\"\nFROM \"buckets\"\nWHERE \"tail_bucket\" = 1\nORDER BY \"training_hours\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT\\n CAST(NULLIF(\\\"training_hours\\\", '') AS REAL) AS \\\"training_hours\\\",\\n NTILE(10) OVER (\\n ORDER BY CAST(NULLIF(\\\"training_hours\\\", '') AS REAL) DESC\\n ) AS \\\"tail_bucket\\\"\\n FROM \\\"m9\\\"\\n WHERE NULLIF(\\\"training_hours\\\", '') IS NOT NULL\\n)\\nSELECT \\\"training_hours\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"training_hours\\\" DESC;\", \"columns\": [\"training_hours\"], \"rows\": [{\"training_hours\": 336.0}, {\"training_hours\": 336.0}, {\"training_hours\": 336.0}, {\"training_hours\": 336.0}, {\"training_hours\": 336.0}, {\"training_hours\": 336.0}, {\"training_hours\": 336.0}, {\"training_hours\": 336.0}, {\"training_hours\": 336.0}, {\"training_hours\": 336.0}, {\"training_hours\": 336.0}, {\"training_hours\": 334.0}, {\"training_hours\": 334.0}, {\"training_hours\": 334.0}, {\"training_hours\": 334.0}, {\"training_hours\": 334.0}, {\"training_hours\": 334.0}, {\"training_hours\": 334.0}, {\"training_hours\": 334.0}, {\"training_hours\": 334.0}, {\"training_hours\": 334.0}, {\"training_hours\": 334.0}, {\"training_hours\": 332.0}, {\"training_hours\": 332.0}, {\"training_hours\": 332.0}, {\"training_hours\": 332.0}, {\"training_hours\": 332.0}, {\"training_hours\": 332.0}, {\"training_hours\": 332.0}, {\"training_hours\": 332.0}, {\"training_hours\": 332.0}, {\"training_hours\": 332.0}, {\"training_hours\": 332.0}, {\"training_hours\": 332.0}, {\"training_hours\": 330.0}, {\"training_hours\": 330.0}, {\"training_hours\": 330.0}, {\"training_hours\": 330.0}, {\"training_hours\": 330.0}, {\"training_hours\": 330.0}, {\"training_hours\": 330.0}, {\"training_hours\": 330.0}, {\"training_hours\": 330.0}, {\"training_hours\": 330.0}, {\"training_hours\": 330.0}, {\"training_hours\": 328.0}, {\"training_hours\": 328.0}, {\"training_hours\": 328.0}, {\"training_hours\": 328.0}, {\"training_hours\": 328.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 30.43}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..985d84d9425a991ef9074ba80016d9646fefe726 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:44:32.680246+00:00", + "ended_at": "2026-05-19T15:44:43.801862+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_c51df929d8943233", + "problem_id": "v2p_m9_2fabf2b06ac3ecb7", + "dataset_id": "m9", + "template_id": "tpl_m4_quantile_tail_slice", + "template_name": "Quantile Tail Slice", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Quantile Tail Slice to probe tail_set_consistency with semantic role rare_extreme_view. Focus on measure_col=training_hours.", + "bindings": { + "measure_col": "training_hours", + "top_k": 12, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH buckets AS (\n SELECT {measure_col},\n NTILE({num_tiles}) OVER (ORDER BY {measure_col} DESC) AS tail_bucket\n FROM {table}\n)\nSELECT {measure_col}\nFROM buckets\nWHERE tail_bucket = 1\nORDER BY {measure_col} DESC;", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=1/1", + "binding_index=62" + ], + "template_selection_mode": "rule", + "selected_template_rank": 6, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_c51df929d8943233.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_c51df929d8943233", + "api_calls": 0, + "input_tokens": 14699, + "cached_input_tokens": 13696, + "output_tokens": 493, + "total_tokens": 15192, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11086.76, + "sql_execution_elapsed_ms_total": 30.43, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..33b46994ef039103c25578d32ff73cdbee02b376 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:44:43.769861+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11086.76, "started_at": "2026-05-19T15:44:32.682331+00:00", "ended_at": "2026-05-19T15:44:43.769116+00:00", "prompt_metrics": {"chars": 9464, "bytes_utf8": 9464, "lines": 262, "estimated_tokens": null}, "response_metrics": {"chars": 643, "bytes_utf8": 643, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14699, "cached_input_tokens": 13696, "output_tokens": 493, "reasoning_output_tokens": 322}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_quantile_tail_slice\\nWITH \\\"buckets\\\" AS (\\n SELECT\\n CAST(NULLIF(\\\"training_hours\\\", '') AS REAL) AS \\\"training_hours\\\",\\n NTILE(10) OVER (\\n ORDER BY CAST(NULLIF(\\\"training_hours\\\", '') AS REAL) DESC\\n ) AS \\\"tail_bucket\\\"\\n FROM \\\"m9\\\"\\n WHERE NULLIF(\\\"training_hours\\\", '') IS NOT NULL\\n)\\nSELECT \\\"training_hours\\\"\\nFROM \\\"buckets\\\"\\nWHERE \\\"tail_bucket\\\" = 1\\nORDER BY \\\"training_hours\\\" DESC;\",\"notes\":\"Uses the Quantile Tail Slice template on \\\"training_hours\\\"; casts the TEXT field to REAL and excludes empty strings so the top decile is computed numerically.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..518cdbc2ec89c617518adaaf1748d5c191bbc0e0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_c51df929d8943233", + "api_calls": 0, + "input_tokens": 14699, + "cached_input_tokens": 13696, + "output_tokens": 493, + "total_tokens": 15192, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11086.76, + "sql_execution_elapsed_ms_total": 30.43, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c51df929d8943233/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..eb9ab2c6991074bc8952441ab63932312964d9fa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=enrolled_university, measure_col=enrollee_id. +Result preview: [{"enrolled_university": "no_enrollment", "total_measure": 229978469}, {"enrolled_university": "Full time course", "total_measure": 65323820}, {"enrolled_university": "Part time course", "total_measure": 21118449}, {"enrolled_university": "", "total_measure": 6877374}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..54df8ec6737eded44d160ad0b414c451b1eac854 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_rank_order +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_m9_c52c6918cfe60eff +-- problem_id: v2p_m9_1b890c7aacbfc9c4 +-- realization_mode: agent +-- source_kind: agent +SELECT "enrolled_university", SUM(CAST("enrollee_id" AS NUMERIC)) AS "total_measure" +FROM "m9" +GROUP BY "enrolled_university" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..543bfe2c8f6925037b4a5db10603ae7887f6940c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"enrolled_university\", SUM(CAST(\"enrollee_id\" AS NUMERIC)) AS \"total_measure\"\nFROM \"m9\"\nGROUP BY \"enrolled_university\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"enrolled_university\\\", SUM(CAST(\\\"enrollee_id\\\" AS NUMERIC)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"enrolled_university\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"enrolled_university\", \"total_measure\"], \"rows\": [{\"enrolled_university\": \"no_enrollment\", \"total_measure\": 229978469}, {\"enrolled_university\": \"Full time course\", \"total_measure\": 65323820}, {\"enrolled_university\": \"Part time course\", \"total_measure\": 21118449}, {\"enrolled_university\": \"\", \"total_measure\": 6877374}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 8.44}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..b2f37225cc76b7508c8521b54b665eb9ac0d41dd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:29:34.557164+00:00", + "ended_at": "2026-05-19T15:29:46.283538+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_c52c6918cfe60eff", + "problem_id": "v2p_m9_1b890c7aacbfc9c4", + "dataset_id": "m9", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_rank_order", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=enrolled_university, measure_col=enrollee_id.", + "bindings": { + "group_col": "enrolled_university", + "measure_col": "enrollee_id", + "top_k": 18, + "top_n": 7, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=2/2", + "binding_index=3" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 4, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_c52c6918cfe60eff.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_c52c6918cfe60eff", + "api_calls": 0, + "input_tokens": 14653, + "cached_input_tokens": 13696, + "output_tokens": 425, + "total_tokens": 15078, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11713.62, + "sql_execution_elapsed_ms_total": 8.44, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b46ea1701b4ba45d535f95ee6af9d99a4f232d85 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:29:46.273663+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11713.62, "started_at": "2026-05-19T15:29:34.559237+00:00", "ended_at": "2026-05-19T15:29:46.272881+00:00", "prompt_metrics": {"chars": 9315, "bytes_utf8": 9315, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 403, "bytes_utf8": 403, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14653, "cached_input_tokens": 13696, "output_tokens": 425, "reasoning_output_tokens": 309}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"enrolled_university\\\", SUM(CAST(\\\"enrollee_id\\\" AS NUMERIC)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"enrolled_university\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Uses the planned grouped-sum template with group_col=\\\"enrolled_university\\\" and measure_col=\\\"enrollee_id\\\". CAST is added because \\\"enrollee_id\\\" is stored as TEXT in SQLite.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..19d6031af04a3f31a617cf03bb60f978a8b4929a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_c52c6918cfe60eff", + "api_calls": 0, + "input_tokens": 14653, + "cached_input_tokens": 13696, + "output_tokens": 425, + "total_tokens": 15078, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11713.62, + "sql_execution_elapsed_ms_total": 8.44, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c52c6918cfe60eff/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c572571d1f11fd9b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c572571d1f11fd9b/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..92c0f0428c461bd9720973dc34ec0fb027ef1a3a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c572571d1f11fd9b/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:57:27.919628+00:00", + "ended_at": "2026-05-19T15:57:35.519815+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_c572571d1f11fd9b", + "problem_id": "v2p_m9_31b74cbbbdfbbb15", + "dataset_id": "m9", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=company_size, measure_col=city_development_index.", + "bindings": { + "group_col": "company_size", + "measure_col": "city_development_index", + "top_k": 16, + "top_n": 7, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=8", + "sql_variant_index=2/2", + "binding_index=91" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 8, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c572571d1f11fd9b/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c572571d1f11fd9b/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..ff119ce903cf1bde6188acf2978215535879ac69 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c572571d1f11fd9b/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:57:31.264135+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3340.63, "started_at": "2026-05-19T15:57:27.922662+00:00", "ended_at": "2026-05-19T15:57:31.263325+00:00", "prompt_metrics": {"chars": 9498, "bytes_utf8": 9498, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f4-d6ff-7262-8da7-5b853144ea5f\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:57:35.519729+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3253.31, "started_at": "2026-05-19T15:57:32.265610+00:00", "ended_at": "2026-05-19T15:57:35.518968+00:00", "prompt_metrics": {"chars": 9498, "bytes_utf8": 9498, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f4-e805-7511-9f3e-9801d2ff0b14\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..65567f1010c3f9ef95c4307c7ac8d76d9adacf9a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=gender, condition_col=company_type. +Result preview: [{"gender": "Male", "condition_ratio": 1.7711779448621554}, {"gender": "Female", "condition_ratio": 1.6166666666666667}, {"gender": "", "condition_ratio": 1.223784417106034}, {"gender": "Other", "condition_ratio": 0.9518072289156626}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..f9ac84eb27fd35b91e168f31e3f48cab4b8b58e5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/generated_sql.sql @@ -0,0 +1,24 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: contrastive_conditional_view +-- template_id: tpl_m4_group_ratio_two_conditions +-- query_record_id: v2q_m9_c5aa48b9b5e80dff +-- problem_id: v2p_m9_b84517ef473a997d +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT "gender", + SUM(CASE WHEN "company_type" = 'Pvt Ltd' THEN 1 ELSE 0 END) AS numerator_count, + SUM(CASE WHEN "company_type" = '' THEN 1 ELSE 0 END) AS denominator_count + FROM "m9" + GROUP BY "gender" +) +SELECT "gender", + CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio +FROM grouped +ORDER BY condition_ratio DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..7ea42de7dcb55218ff4800c479a7f6de5f99380b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_ratio_two_conditions\nWITH grouped AS (\n SELECT \"gender\",\n SUM(CASE WHEN \"company_type\" = 'Pvt Ltd' THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN \"company_type\" = '' THEN 1 ELSE 0 END) AS denominator_count\n FROM \"m9\"\n GROUP BY \"gender\"\n)\nSELECT \"gender\",\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"gender\\\",\\n SUM(CASE WHEN \\\"company_type\\\" = 'Pvt Ltd' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"company_type\\\" = '' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"m9\\\"\\n GROUP BY \\\"gender\\\"\\n)\\nSELECT \\\"gender\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\", \"columns\": [\"gender\", \"condition_ratio\"], \"rows\": [{\"gender\": \"Male\", \"condition_ratio\": 1.7711779448621554}, {\"gender\": \"Female\", \"condition_ratio\": 1.6166666666666667}, {\"gender\": \"\", \"condition_ratio\": 1.223784417106034}, {\"gender\": \"Other\", \"condition_ratio\": 0.9518072289156626}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.34}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..726cce3e451ba39316a16d2c5fe9310c6ec1b95b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:40:11.630607+00:00", + "ended_at": "2026-05-19T15:40:24.042730+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_c5aa48b9b5e80dff", + "problem_id": "v2p_m9_b84517ef473a997d", + "dataset_id": "m9", + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "contrastive_conditional_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=gender, condition_col=company_type.", + "bindings": { + "group_col": "gender", + "condition_col": "company_type", + "condition_value": "Pvt Ltd", + "positive_value": "Pvt Ltd", + "negative_value": "", + "top_k": 12, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=1/1", + "binding_index=37" + ], + "template_selection_mode": "rule", + "selected_template_rank": 4, + "problem_index_within_template": 2, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_c5aa48b9b5e80dff.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_c5aa48b9b5e80dff", + "api_calls": 0, + "input_tokens": 14855, + "cached_input_tokens": 13696, + "output_tokens": 594, + "total_tokens": 15449, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12396.95, + "sql_execution_elapsed_ms_total": 9.34, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3387c86a8262be076d7f0253cfbc895977526679 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:40:24.031850+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 12396.95, "started_at": "2026-05-19T15:40:11.634119+00:00", "ended_at": "2026-05-19T15:40:24.031110+00:00", "prompt_metrics": {"chars": 10101, "bytes_utf8": 10101, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 692, "bytes_utf8": 692, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14855, "cached_input_tokens": 13696, "output_tokens": 594, "reasoning_output_tokens": 416}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions\\nWITH grouped AS (\\n SELECT \\\"gender\\\",\\n SUM(CASE WHEN \\\"company_type\\\" = 'Pvt Ltd' THEN 1 ELSE 0 END) AS numerator_count,\\n SUM(CASE WHEN \\\"company_type\\\" = '' THEN 1 ELSE 0 END) AS denominator_count\\n FROM \\\"m9\\\"\\n GROUP BY \\\"gender\\\"\\n)\\nSELECT \\\"gender\\\",\\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\\nFROM grouped\\nORDER BY condition_ratio DESC;\",\"notes\":\"Instantiated the provided grouped ratio template with group_col=\\\"gender\\\", condition_col=\\\"company_type\\\", positive_value='Pvt Ltd', and negative_value='' exactly as bound in the problem instance.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..b88adf9a773a5680f10df51543c1118758f18b25 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_c5aa48b9b5e80dff", + "api_calls": 0, + "input_tokens": 14855, + "cached_input_tokens": 13696, + "output_tokens": 594, + "total_tokens": 15449, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12396.95, + "sql_execution_elapsed_ms_total": 9.34, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_c5aa48b9b5e80dff/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..07f760cfeea0925e2007579cc9d3fa90fac9fbc7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9727, "bytes_utf8": 9727, "lines": 266, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 666, "bytes_utf8": 666, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14771, "cached_input_tokens": 12032, "output_tokens": 707, "reasoning_output_tokens": 516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..aacbb0da61555785cd777d64f691c884764819e3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_cac5916e1e379119", + "api_calls": 0, + "input_tokens": 14771, + "cached_input_tokens": 12032, + "output_tokens": 707, + "total_tokens": 15478, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14105.38, + "sql_execution_elapsed_ms_total": 21.58, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..c015dd4d7359c0c8bbdfb853c1ee12e62f429afd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:35:57.406111+00:00", + "ended_at": "2026-05-19T15:36:11.511522+00:00", + "elapsed_ms": 14105.38, + "prompt_metrics": { + "chars": 9727, + "bytes_utf8": 9727, + "lines": 266, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1053, + "bytes_utf8": 1053, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 666, + "bytes_utf8": 666, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14771, + "cached_input_tokens": 12032, + "output_tokens": 707, + "reasoning_output_tokens": 516 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..2f56c0c6227e92435fe6fae73fa858238ba7ea3b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,266 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "required_roles": [ + "group_col", + "item_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=enrolled_university, measure_col=enrollee_id.", + "planned_template_id": "tpl_tpcds_within_group_share", + "bindings": { + "group_col": "enrolled_university", + "measure_col": "enrollee_id", + "item_col": "experience", + "top_k": 17, + "top_n": 7, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..c64c8a0dbd5d0d03786277e52eb3b6d025846b16 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40e1-25d8-7e82-8fbf-408ddecd6f5b"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"enrolled_university\\\",\\n \\\"experience\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) * 100.0 /\\n SUM(SUM(CAST(\\\"enrollee_id\\\" AS REAL))) OVER (PARTITION BY \\\"enrolled_university\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nGROUP BY \\\"enrolled_university\\\", \\\"experience\\\"\\nORDER BY share_within_group DESC;\",\"notes\":\"Used the provided template with group_col=\\\"enrolled_university\\\", item_col=\\\"experience\\\", and measure_col=\\\"enrollee_id\\\". Since \\\"enrollee_id\\\" is stored as TEXT in SQLite, it is cast to REAL so SUM(...) remains SQLite-compatible.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14771,"cached_input_tokens":12032,"output_tokens":707,"reasoning_output_tokens":516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e0a7087932ee02ba2de21c5bbdeaa9e020f67cf3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"enrolled_university\",\n \"experience\",\n SUM(CAST(\"enrollee_id\" AS REAL)) AS total_measure,\n SUM(CAST(\"enrollee_id\" AS REAL)) * 100.0 /\n SUM(SUM(CAST(\"enrollee_id\" AS REAL))) OVER (PARTITION BY \"enrolled_university\") AS share_within_group\nFROM \"m9\"\nGROUP BY \"enrolled_university\", \"experience\"\nORDER BY share_within_group DESC;","notes":"Used the provided template with group_col=\"enrolled_university\", item_col=\"experience\", and measure_col=\"enrollee_id\". Since \"enrollee_id\" is stored as TEXT in SQLite, it is cast to REAL so SUM(...) remains SQLite-compatible."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cac5916e1e379119/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..03cdefe64193f02627cc74f9432514f1a5bbca9c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "no_enrollment", "support": 13817, "support_share": 0.7212130702578557, "support_rank": 1}, {"value_label": "Full time course", "support": 3757, "support_share": 0.19610606535128927, "support_rank": 2}, {"value_label": "Part time course", "support": 1198, "support_share": 0.06253262344712392, "support_rank": 3}, {"value_label": "", "support": 386, "support_share": 0.020148240943731077, "support_rank": 4}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..ad64be987b02e1cb9ce681b30cd405945e5efedc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/generated_sql.sql @@ -0,0 +1,25 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: value_imbalance_profile +-- variant_semantic_role: count_distribution +-- template_id: tpl_cardinality_support_rank_profile +-- query_record_id: v2q_m9_cc00937eeb3aecfd +-- problem_id: v2p_m9_c8d95c8646006585 +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "enrolled_university" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "enrolled_university" +) +SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank +FROM grouped +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..32272fffd9f7ceb7d8d55b53b45d865b57ebe0aa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: value_imbalance_profile\n-- variant_semantic_role: count_distribution\n-- template_id: tpl_cardinality_support_rank_profile\n-- query_record_id: v2q_m9_cc00937eeb3aecfd\n-- problem_id: v2p_m9_c8d95c8646006585\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"enrolled_university\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"enrolled_university\"\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: value_imbalance_profile\\n-- variant_semantic_role: count_distribution\\n-- template_id: tpl_cardinality_support_rank_profile\\n-- query_record_id: v2q_m9_cc00937eeb3aecfd\\n-- problem_id: v2p_m9_c8d95c8646006585\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"enrolled_university\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"enrolled_university\\\"\\n)\\nSELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\\nFROM grouped\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"support_rank\"], \"rows\": [{\"value_label\": \"no_enrollment\", \"support\": 13817, \"support_share\": 0.7212130702578557, \"support_rank\": 1}, {\"value_label\": \"Full time course\", \"support\": 3757, \"support_share\": 0.19610606535128927, \"support_rank\": 2}, {\"value_label\": \"Part time course\", \"support\": 1198, \"support_share\": 0.06253262344712392, \"support_rank\": 3}, {\"value_label\": \"\", \"support\": 386, \"support_share\": 0.020148240943731077, \"support_rank\": 4}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.98}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..c5cc2b819ff2a88a6d6ae7a45b6906df098d3eaf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.298597+00:00", + "ended_at": "2026-05-19T16:08:56.305348+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_cc00937eeb3aecfd", + "problem_id": "v2p_m9_c8d95c8646006585", + "dataset_id": "m9", + "template_id": "tpl_cardinality_support_rank_profile", + "template_name": "Cardinality Support Rank Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "value_imbalance_profile", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Support Rank Profile to probe support_rank_profile_consistency with semantic role count_distribution. Focus on group_col=enrolled_university.", + "bindings": { + "group_col": "enrolled_university" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=4", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_cc00937eeb3aecfd.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cc00937eeb3aecfd/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..1df692144313a778d42cac41f9bf97b6baa0dc67 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 10156, "bytes_utf8": 10156, "lines": 267, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 881, "bytes_utf8": 881, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14863, "cached_input_tokens": 13696, "output_tokens": 759, "reasoning_output_tokens": 516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..9d52e6db8fa7623fccfb14309b9a761028f9b718 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_cf8beba493454b99", + "api_calls": 0, + "input_tokens": 14863, + "cached_input_tokens": 13696, + "output_tokens": 759, + "total_tokens": 15622, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14937.15, + "sql_execution_elapsed_ms_total": 10.81, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..571ded34156eb5b1af4c1303dd4a1af371483c32 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:41:26.720924+00:00", + "ended_at": "2026-05-19T15:41:41.658097+00:00", + "elapsed_ms": 14937.15, + "prompt_metrics": { + "chars": 10156, + "bytes_utf8": 10156, + "lines": 267, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1286, + "bytes_utf8": 1286, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 881, + "bytes_utf8": 881, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14863, + "cached_input_tokens": 13696, + "output_tokens": 759, + "reasoning_output_tokens": 516 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..806fbecabc695f956f4072a0b82c95eb58ca1c95 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,267 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_ratio_two_conditions", + "template_name": "Grouped Ratio of Two Conditions", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Ratio of Two Conditions to probe direction_consistency with semantic role contrastive_conditional_view. Focus on group_col=experience, condition_col=enrolled_university.", + "planned_template_id": "tpl_m4_group_ratio_two_conditions", + "bindings": { + "group_col": "experience", + "condition_col": "enrolled_university", + "condition_value": "no_enrollment", + "positive_value": "no_enrollment", + "negative_value": "Full time course", + "top_k": 12, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col},\n SUM(CASE WHEN {condition_col} = {positive_value} THEN 1 ELSE 0 END) AS numerator_count,\n SUM(CASE WHEN {condition_col} = {negative_value} THEN 1 ELSE 0 END) AS denominator_count\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT {group_col},\n CAST(numerator_count AS FLOAT) / NULLIF(denominator_count, 0) AS condition_ratio\nFROM grouped\nORDER BY condition_ratio DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..2893b0eeea4ba231352a64002c799a8d8efea85c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40e6-2c50-7eb1-9dbd-d306320469df"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_ratio_two_conditions.\\nWITH \\\"grouped\\\" AS (\\n SELECT\\n \\\"experience\\\",\\n SUM(CASE WHEN \\\"enrolled_university\\\" = 'no_enrollment' THEN 1 ELSE 0 END) AS \\\"numerator_count\\\",\\n SUM(CASE WHEN \\\"enrolled_university\\\" = 'Full time course' THEN 1 ELSE 0 END) AS \\\"denominator_count\\\"\\n FROM \\\"m9\\\"\\n GROUP BY \\\"experience\\\"\\n)\\nSELECT\\n \\\"experience\\\",\\n CAST(\\\"numerator_count\\\" AS FLOAT) / NULLIF(\\\"denominator_count\\\", 0) AS \\\"condition_ratio\\\"\\nFROM \\\"grouped\\\"\\nWHERE (\\\"numerator_count\\\" + \\\"denominator_count\\\") >= 5\\nORDER BY \\\"condition_ratio\\\" DESC\\nLIMIT 12;\",\"notes\":\"Computes, for each experience group, the ratio of rows with enrolled_university = 'no_enrollment' to rows with enrolled_university = 'Full time course'. Applies a minimum combined support of 5 and returns the top 12 groups by ratio.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14863,"cached_input_tokens":13696,"output_tokens":759,"reasoning_output_tokens":516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..fb24d97c02e23b893013c37b78f14b3ed3367be8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_group_ratio_two_conditions.\nWITH \"grouped\" AS (\n SELECT\n \"experience\",\n SUM(CASE WHEN \"enrolled_university\" = 'no_enrollment' THEN 1 ELSE 0 END) AS \"numerator_count\",\n SUM(CASE WHEN \"enrolled_university\" = 'Full time course' THEN 1 ELSE 0 END) AS \"denominator_count\"\n FROM \"m9\"\n GROUP BY \"experience\"\n)\nSELECT\n \"experience\",\n CAST(\"numerator_count\" AS FLOAT) / NULLIF(\"denominator_count\", 0) AS \"condition_ratio\"\nFROM \"grouped\"\nWHERE (\"numerator_count\" + \"denominator_count\") >= 5\nORDER BY \"condition_ratio\" DESC\nLIMIT 12;","notes":"Computes, for each experience group, the ratio of rows with enrolled_university = 'no_enrollment' to rows with enrolled_university = 'Full time course'. Applies a minimum combined support of 5 and returns the top 12 groups by ratio."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_cf8beba493454b99/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..907342f0d326699eddb1296e782e63ab8ca752aa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:06:09.241107+00:00", + "ended_at": "2026-05-19T16:06:12.698116+00:00", + "elapsed_ms": 3456.98, + "returncode": 1, + "prompt_metrics": { + "chars": 9280, + "bytes_utf8": 9280, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..f6b781a25dd63796513e906a901beb10cf748bd0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:06:13.699636+00:00", + "ended_at": "2026-05-19T16:06:16.835895+00:00", + "elapsed_ms": 3136.23, + "returncode": 1, + "prompt_metrics": { + "chars": 9280, + "bytes_utf8": 9280, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..a69d334d0ea81bbddf06d8a5a5460c6541cac98e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role count_distribution. Focus on group_col=experience.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "experience", + "top_k": 16, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..a69d334d0ea81bbddf06d8a5a5460c6541cac98e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role count_distribution. Focus on group_col=experience.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "experience", + "top_k": 16, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..7a38b1490f968cd06261062d251e8abd5c5b4595 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-cb4f-7f11-a901-463568de7594"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..bbdc2fca6af026b29578e195f2057b5b581353a8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-cb4f-7f11-a901-463568de7594"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..f477328a6b7bc7378ff5a806fbd55dbfc492d047 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-dcc7-7d41-b6b2-3747e1063193"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..22aa027ad76ecf2110d5ce444c65d7db49b1a098 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fc-dcc7-7d41-b6b2-3747e1063193"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d0e648e47097b9a5/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..1f18c74bfff188381ddb2893c2c9f793758a3d51 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=company_type, measure_col=training_hours. +Result preview: [{"company_type": "NGO", "percentile_measure": 156.0}, {"company_type": "Early Stage Startup", "percentile_measure": 152.0}, {"company_type": "Other", "percentile_measure": 152.0}, {"company_type": "Funded Startup", "percentile_measure": 146.0}, {"company_type": "Pvt Ltd", "percentile_measure": 146.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..b03f8bf71c34ed7f77158f197383a83b92db3681 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/generated_sql.sql @@ -0,0 +1,41 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_m9_d42363a79139d199 +-- problem_id: v2p_m9_c8a02f22ec4ab88c +-- realization_mode: agent +-- source_kind: agent +WITH "base" AS ( + SELECT + "company_type", + CAST("training_hours" AS REAL) AS "training_hours_num" + FROM "m9" + WHERE NULLIF("company_type", '') IS NOT NULL + AND NULLIF("training_hours", '') IS NOT NULL +), +"ranked" AS ( + SELECT + "company_type", + "training_hours_num", + ROW_NUMBER() OVER ( + PARTITION BY "company_type" + ORDER BY "training_hours_num" + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "company_type" + ) AS "cnt" + FROM "base" +) +SELECT + "company_type", + "training_hours_num" AS "percentile_measure" +FROM "ranked" +WHERE "cnt" >= 5 + AND "rn" = CAST((9 * "cnt" + 9) / 10 AS INTEGER) +ORDER BY "percentile_measure" DESC, "company_type"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2c63fe2dc20f913b92e70d9cc354731a72f1323e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 2, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"base\" AS (\n SELECT\n \"company_type\",\n CAST(\"training_hours\" AS REAL) AS \"training_hours_num\"\n FROM \"m9\"\n WHERE NULLIF(\"company_type\", '') IS NOT NULL\n AND NULLIF(\"training_hours\", '') IS NOT NULL\n),\n\"ranked\" AS (\n SELECT\n \"company_type\",\n \"training_hours_num\",\n ROW_NUMBER() OVER (\n PARTITION BY \"company_type\"\n ORDER BY \"training_hours_num\"\n ) AS \"rn\",\n COUNT(*) OVER (\n PARTITION BY \"company_type\"\n ) AS \"cnt\"\n FROM \"base\"\n)\nSELECT\n \"company_type\",\n \"training_hours_num\" AS \"percentile_measure\"\nFROM \"ranked\"\nWHERE \"cnt\" >= 5\n AND \"rn\" = CAST((9 * \"cnt\" + 9) / 10 AS INTEGER)\nORDER BY \"percentile_measure\" DESC, \"company_type\";", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"base\\\" AS (\\n SELECT\\n \\\"company_type\\\",\\n CAST(\\\"training_hours\\\" AS REAL) AS \\\"training_hours_num\\\"\\n FROM \\\"m9\\\"\\n WHERE NULLIF(\\\"company_type\\\", '') IS NOT NULL\\n AND NULLIF(\\\"training_hours\\\", '') IS NOT NULL\\n),\\n\\\"ranked\\\" AS (\\n SELECT\\n \\\"company_type\\\",\\n \\\"training_hours_num\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"company_type\\\"\\n ORDER BY \\\"training_hours_num\\\"\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"company_type\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"base\\\"\\n)\\nSELECT\\n \\\"company_type\\\",\\n \\\"training_hours_num\\\" AS \\\"percentile_measure\\\"\\nFROM \\\"ranked\\\"\\nWHERE \\\"cnt\\\" >= 5\\n AND \\\"rn\\\" = CAST((9 * \\\"cnt\\\" + 9) / 10 AS INTEGER)\\nORDER BY \\\"percentile_measure\\\" DESC, \\\"company_type\\\";\", \"columns\": [\"company_type\", \"percentile_measure\"], \"rows\": [{\"company_type\": \"NGO\", \"percentile_measure\": 156.0}, {\"company_type\": \"Early Stage Startup\", \"percentile_measure\": 152.0}, {\"company_type\": \"Other\", \"percentile_measure\": 152.0}, {\"company_type\": \"Funded Startup\", \"percentile_measure\": 146.0}, {\"company_type\": \"Pvt Ltd\", \"percentile_measure\": 146.0}, {\"company_type\": \"Public Sector\", \"percentile_measure\": 141.0}], \"row_count_returned\": 6, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 53.02}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..6714e874ee55a0ec5f1dda7d744dc7e2badc28ed --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:58:34.341813+00:00", + "ended_at": "2026-05-19T15:59:08.723718+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_d42363a79139d199", + "problem_id": "v2p_m9_c8a02f22ec4ab88c", + "dataset_id": "m9", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=company_type, measure_col=training_hours.", + "bindings": { + "group_col": "company_type", + "measure_col": "training_hours", + "top_k": 17, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 70.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=9", + "sql_variant_index=2/2", + "binding_index=92" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 9, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_d42363a79139d199.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_d42363a79139d199", + "api_calls": 0, + "input_tokens": 14684, + "cached_input_tokens": 12032, + "output_tokens": 1697, + "total_tokens": 16381, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 33320.67, + "sql_execution_elapsed_ms_total": 53.02, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..39643881452f40135fbb54b4d6fa258eba40f66f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:58:37.694666+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3350.28, "started_at": "2026-05-19T15:58:34.343630+00:00", "ended_at": "2026-05-19T15:58:37.693929+00:00", "prompt_metrics": {"chars": 9480, "bytes_utf8": 9480, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f5-da7d-7b51-9cdd-83e240146658\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:59:08.667927+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 29970.39, "started_at": "2026-05-19T15:58:38.696249+00:00", "ended_at": "2026-05-19T15:59:08.666693+00:00", "prompt_metrics": {"chars": 9480, "bytes_utf8": 9480, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 1101, "bytes_utf8": 1101, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14684, "cached_input_tokens": 12032, "output_tokens": 1697, "reasoning_output_tokens": 1391}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"base\\\" AS (\\n SELECT\\n \\\"company_type\\\",\\n CAST(\\\"training_hours\\\" AS REAL) AS \\\"training_hours_num\\\"\\n FROM \\\"m9\\\"\\n WHERE NULLIF(\\\"company_type\\\", '') IS NOT NULL\\n AND NULLIF(\\\"training_hours\\\", '') IS NOT NULL\\n),\\n\\\"ranked\\\" AS (\\n SELECT\\n \\\"company_type\\\",\\n \\\"training_hours_num\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"company_type\\\"\\n ORDER BY \\\"training_hours_num\\\"\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"company_type\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"base\\\"\\n)\\nSELECT\\n \\\"company_type\\\",\\n \\\"training_hours_num\\\" AS \\\"percentile_measure\\\"\\nFROM \\\"ranked\\\"\\nWHERE \\\"cnt\\\" >= 5\\n AND \\\"rn\\\" = CAST((9 * \\\"cnt\\\" + 9) / 10 AS INTEGER)\\nORDER BY \\\"percentile_measure\\\" DESC, \\\"company_type\\\";\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this uses the nearest-rank 90th percentile per company_type via window functions. It casts training_hours from TEXT to REAL, exclu"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..9c5e2e4935bf9e6997577c53be0d87466ee4da88 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_d42363a79139d199", + "api_calls": 0, + "input_tokens": 14684, + "cached_input_tokens": 12032, + "output_tokens": 1697, + "total_tokens": 16381, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 33320.67, + "sql_execution_elapsed_ms_total": 53.02, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d42363a79139d199/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..4b67360856702c3ade1850355172b469ffc64575 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9294, "bytes_utf8": 9294, "lines": 262, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 358, "bytes_utf8": 358, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14660, "cached_input_tokens": 13696, "output_tokens": 278, "reasoning_output_tokens": 170}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..4e376cb873452f54ee2d007092ca504e1044e52b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_d4358642b47fe90b", + "api_calls": 0, + "input_tokens": 14660, + "cached_input_tokens": 13696, + "output_tokens": 278, + "total_tokens": 14938, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8087.15, + "sql_execution_elapsed_ms_total": 9.49, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..4bd74f4509cf68360be92b8210530cabc345bf4a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:04:47.835317+00:00", + "ended_at": "2026-05-19T16:04:55.922499+00:00", + "elapsed_ms": 8087.15, + "prompt_metrics": { + "chars": 9294, + "bytes_utf8": 9294, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 719, + "bytes_utf8": 719, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 358, + "bytes_utf8": 358, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14660, + "cached_input_tokens": 13696, + "output_tokens": 278, + "reasoning_output_tokens": 170 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..ac925fb06dd6edd5eb3fc7f2c348defb8af0907f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role count_distribution. Focus on group_col=relevent_experience.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "relevent_experience", + "top_k": 17, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..f9f97d6ceb9a140415ffee3274ec6c9cac7030f6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fb-8d62-7890-9f3e-c482fce3c8a3"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"relevent_experience\\\",\\n COUNT(*) AS \\\"support\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"relevent_experience\\\"\\nORDER BY \\\"support\\\" ASC, \\\"relevent_experience\\\"\\nLIMIT 17;\",\"notes\":\"Uses the Low-Support Group Count template with group_col bound to \\\"relevent_experience\\\" and top_k set to 17.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14660,"cached_input_tokens":13696,"output_tokens":278,"reasoning_output_tokens":170}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..54910244f41d6413742e3af35dcda8d277ea96bd --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n \"relevent_experience\",\n COUNT(*) AS \"support\"\nFROM \"m9\"\nGROUP BY \"relevent_experience\"\nORDER BY \"support\" ASC, \"relevent_experience\"\nLIMIT 17;","notes":"Uses the Low-Support Group Count template with group_col bound to \"relevent_experience\" and top_k set to 17."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4358642b47fe90b/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4a0d62d3e212d89/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4a0d62d3e212d89/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..334dbafffb458a89ef82ad84ae367c091e63d29c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4a0d62d3e212d89/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:07:05.980895+00:00", + "ended_at": "2026-05-19T16:07:12.663228+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_d4a0d62d3e212d89", + "problem_id": "v2p_m9_09c65e48ed7150e9", + "dataset_id": "m9", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe slice_level_consistency with semantic role filtered_stable_view. Focus on group_col=relevent_experience, measure_col=training_hours.", + "bindings": { + "group_col": "relevent_experience", + "measure_col": "training_hours", + "top_k": 14, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=1/2", + "binding_index=134" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4a0d62d3e212d89/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4a0d62d3e212d89/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a3479805a6aa3ae2c51ada57fa2e7d782913b484 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d4a0d62d3e212d89/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T16:07:08.898738+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2914.43, "started_at": "2026-05-19T16:07:05.983514+00:00", "ended_at": "2026-05-19T16:07:08.897976+00:00", "prompt_metrics": {"chars": 9401, "bytes_utf8": 9401, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fd-a91a-7910-9c2f-4957e5236012\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T16:07:12.663068+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 2761.65, "started_at": "2026-05-19T16:07:09.900124+00:00", "ended_at": "2026-05-19T16:07:12.661826+00:00", "prompt_metrics": {"chars": 9401, "bytes_utf8": 9401, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40fd-b84d-71b1-85c3-deb8a9f6e564\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..76e41d87eef837e4f8f69837e84a70d2ea13c966 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=enrolled_university, measure_col=enrollee_id. +Result preview: [{"enrolled_university": "", "avg_measure": 17817.031088082902}, {"enrolled_university": "Part time course", "avg_measure": 17628.087646076794}, {"enrolled_university": "Full time course", "avg_measure": 17387.22917221187}, {"enrolled_university": "no_enrollment", "avg_measure": 16644.602229138018}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..3398fa4ffe3fa4ae19f8375e27d4af95655ab6c3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_m9_d91e1b55d49f5e6b +-- problem_id: v2p_m9_eaf36c86aa88822b +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "enrolled_university", + AVG(CAST("enrollee_id" AS REAL)) OVER (PARTITION BY "enrolled_university") AS avg_measure +FROM "m9" +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6636530a5d45aaf95d6138339989fc46dfc97a6c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT \"enrolled_university\",\n AVG(CAST(\"enrollee_id\" AS REAL)) OVER (PARTITION BY \"enrolled_university\") AS avg_measure\nFROM \"m9\"\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"enrolled_university\\\",\\n AVG(CAST(\\\"enrollee_id\\\" AS REAL)) OVER (PARTITION BY \\\"enrolled_university\\\") AS avg_measure\\nFROM \\\"m9\\\"\\nORDER BY avg_measure DESC;\", \"columns\": [\"enrolled_university\", \"avg_measure\"], \"rows\": [{\"enrolled_university\": \"\", \"avg_measure\": 17817.031088082902}, {\"enrolled_university\": \"Part time course\", \"avg_measure\": 17628.087646076794}, {\"enrolled_university\": \"Full time course\", \"avg_measure\": 17387.22917221187}, {\"enrolled_university\": \"no_enrollment\", \"avg_measure\": 16644.602229138018}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 35.24}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..eda008a4d81c544b6a9d995d7f3a87bcd4ca3810 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:07:26.364649+00:00", + "ended_at": "2026-05-19T16:07:35.626639+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_d91e1b55d49f5e6b", + "problem_id": "v2p_m9_eaf36c86aa88822b", + "dataset_id": "m9", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe direction_consistency with semantic role ranked_signal_view. Focus on group_col=enrolled_university, measure_col=enrollee_id.", + "bindings": { + "group_col": "enrolled_university", + "measure_col": "enrollee_id", + "top_k": 10, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/2", + "binding_index=135" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_d91e1b55d49f5e6b.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_d91e1b55d49f5e6b", + "api_calls": 0, + "input_tokens": 14663, + "cached_input_tokens": 12032, + "output_tokens": 344, + "total_tokens": 15007, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9222.19, + "sql_execution_elapsed_ms_total": 35.24, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b0eb4c70b98655ebd52a4e78ff371074c83179ba --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:07:35.589584+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 9222.19, "started_at": "2026-05-19T16:07:26.366575+00:00", "ended_at": "2026-05-19T16:07:35.588797+00:00", "prompt_metrics": {"chars": 9394, "bytes_utf8": 9394, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 488, "bytes_utf8": 488, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14663, "cached_input_tokens": 12032, "output_tokens": 344, "reasoning_output_tokens": 220}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"enrolled_university\\\",\\n AVG(CAST(\\\"enrollee_id\\\" AS REAL)) OVER (PARTITION BY \\\"enrolled_university\\\") AS avg_measure\\nFROM \\\"m9\\\"\\nORDER BY avg_measure DESC;\",\"notes\":\"Used the requested Window Partition Average template with group_col=\\\"enrolled_university\\\" and measure_col=\\\"enrollee_id\\\". CAST was added because \\\"enrollee_id\\\" is stored as TEXT in the SQLite schema while AVG requires numeric coercion.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..ba6d657bb97582b0e95942ed9d68a46b901bff62 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_d91e1b55d49f5e6b", + "api_calls": 0, + "input_tokens": 14663, + "cached_input_tokens": 12032, + "output_tokens": 344, + "total_tokens": 15007, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 9222.19, + "sql_execution_elapsed_ms_total": 35.24, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_d91e1b55d49f5e6b/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..80511e9a012772921727192c7ec52040206f823c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/conversation.jsonl @@ -0,0 +1,4 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9614, "bytes_utf8": 9614, "lines": 267, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "status": "failed", "error": "AI CLI command failed with exit code 1: "} +{"attempt": 2, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_2.txt", "metrics": {"chars": 9614, "bytes_utf8": 9614, "lines": 267, "estimated_tokens": null}} +{"attempt": 2, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_2.txt", "raw_content_path": "cli/sql_response_attempt_2.raw.txt", "stderr_path": "cli/sql_stderr_attempt_2.txt", "metrics": {"chars": 470, "bytes_utf8": 470, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14722, "cached_input_tokens": 12032, "output_tokens": 288, "reasoning_output_tokens": 164}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..6b41c9a21fa72ab7510a273fa5f81f056b7848c2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 2, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_dd2c943b4f284c51", + "api_calls": 0, + "input_tokens": 14722, + "cached_input_tokens": 12032, + "output_tokens": 288, + "total_tokens": 15010, + "cost_usd": 0.0, + "ai_cli_calls": 2, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 12044.06, + "sql_execution_elapsed_ms_total": 9.0, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..33d8a0e524721303838c8b2734e18bb1854c6bd5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:59:56.091106+00:00", + "ended_at": "2026-05-19T15:59:59.022125+00:00", + "elapsed_ms": 2930.98, + "returncode": 1, + "prompt_metrics": { + "chars": 9614, + "bytes_utf8": 9614, + "lines": 267, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..602fbf9b6edf057c16e08ede1ecad5d2e445047a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_attempt_2.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:00:00.024720+00:00", + "ended_at": "2026-05-19T16:00:09.137842+00:00", + "elapsed_ms": 9113.08, + "prompt_metrics": { + "chars": 9614, + "bytes_utf8": 9614, + "lines": 267, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 825, + "bytes_utf8": 825, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 470, + "bytes_utf8": 470, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14722, + "cached_input_tokens": 12032, + "output_tokens": 288, + "reasoning_output_tokens": 164 + } + }, + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..cd5f25177dfba89c116213295961e93ba62e8d79 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,267 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=relevent_experience, condition_col=enrolled_university.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "relevent_experience", + "condition_col": "enrolled_university", + "condition_value": "no_enrollment", + "positive_value": "no_enrollment", + "negative_value": "Full time course", + "top_k": 13, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..cd5f25177dfba89c116213295961e93ba62e8d79 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,267 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=relevent_experience, condition_col=enrolled_university.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "relevent_experience", + "condition_col": "enrolled_university", + "condition_value": "no_enrollment", + "positive_value": "no_enrollment", + "negative_value": "Full time course", + "top_k": 13, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..1f0ee2636973a492442a72b43d63c15f4c7d22ef --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f7-19df-7900-a575-f1d326cd866e"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..ff49f6cd55566c2e2c50a151db4d9d745c6a4436 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f7-19df-7900-a575-f1d326cd866e"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..e282bf011147536a0481822bd65ab9c8deba9d7d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f7-292e-71a2-9c01-79ef3a101a42"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"relevent_experience\\\",\\n AVG(CASE WHEN \\\"enrolled_university\\\" = 'no_enrollment' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"relevent_experience\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Applies the Grouped Condition Rate template as specified: groups by relevent_experience and computes the within-group proportion of rows where enrolled_university equals 'no_enrollment'.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14722,"cached_input_tokens":12032,"output_tokens":288,"reasoning_output_tokens":164}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..9c2bf32248ccb2659a9bbc3ccb49d082a2685b94 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_response_attempt_2.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT \"relevent_experience\",\n AVG(CASE WHEN \"enrolled_university\" = 'no_enrollment' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"m9\"\nGROUP BY \"relevent_experience\"\nORDER BY \"condition_rate\" DESC;","notes":"Applies the Grouped Condition Rate template as specified: groups by relevent_experience and computes the within-group proportion of rows where enrolled_university equals 'no_enrollment'."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dd2c943b4f284c51/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..4c3a13e52e4779d158eeb5f638e9af7a7d8582b2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "Pvt Ltd", "support": 9817, "support_share": 0.5124230086647875, "support_rank": 1}, {"value_label": "", "support": 6140, "support_share": 0.32049274454535964, "support_rank": 2}, {"value_label": "Funded Startup", "support": 1001, "support_share": 0.05224971291366531, "support_rank": 3}, {"value_label": "Public Sector", "support": 955, "support_share": 0.049848627205345025, "support_rank": 4}, {"value_label": "Early Stage Startup", "support": 603, "support_share": 0.03147510178515503, "support_rank": 5}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..10ec4e2d6dd83dbffc095d4679cd4480f24e0825 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/generated_sql.sql @@ -0,0 +1,25 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: support_concentration +-- variant_semantic_role: count_distribution +-- template_id: tpl_cardinality_support_rank_profile +-- query_record_id: v2q_m9_de0d50470026f862 +-- problem_id: v2p_m9_7b16f6a2d125b502 +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "company_type" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "company_type" +) +SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank +FROM grouped +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..27d62bdbd94dfa5599e68731069319c709e40c8e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: count_distribution\n-- template_id: tpl_cardinality_support_rank_profile\n-- query_record_id: v2q_m9_de0d50470026f862\n-- problem_id: v2p_m9_7b16f6a2d125b502\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"company_type\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"company_type\"\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: count_distribution\\n-- template_id: tpl_cardinality_support_rank_profile\\n-- query_record_id: v2q_m9_de0d50470026f862\\n-- problem_id: v2p_m9_7b16f6a2d125b502\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"company_type\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"company_type\\\"\\n)\\nSELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\\nFROM grouped\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"support_rank\"], \"rows\": [{\"value_label\": \"Pvt Ltd\", \"support\": 9817, \"support_share\": 0.5124230086647875, \"support_rank\": 1}, {\"value_label\": \"\", \"support\": 6140, \"support_share\": 0.32049274454535964, \"support_rank\": 2}, {\"value_label\": \"Funded Startup\", \"support\": 1001, \"support_share\": 0.05224971291366531, \"support_rank\": 3}, {\"value_label\": \"Public Sector\", \"support\": 955, \"support_share\": 0.049848627205345025, \"support_rank\": 4}, {\"value_label\": \"Early Stage Startup\", \"support\": 603, \"support_share\": 0.03147510178515503, \"support_rank\": 5}, {\"value_label\": \"NGO\", \"support\": 521, \"support_share\": 0.02719490552249713, \"support_rank\": 6}, {\"value_label\": \"Other\", \"support\": 121, \"support_share\": 0.006315899363190312, \"support_rank\": 7}], \"row_count_returned\": 7, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 6.13}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..9e1837a06da296b986edbd9f05b16f23ff953e43 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.338905+00:00", + "ended_at": "2026-05-19T16:08:56.345808+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_de0d50470026f862", + "problem_id": "v2p_m9_7b16f6a2d125b502", + "dataset_id": "m9", + "template_id": "tpl_cardinality_support_rank_profile", + "template_name": "Cardinality Support Rank Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "support_concentration", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Support Rank Profile to probe support_rank_profile_consistency with semantic role count_distribution. Focus on group_col=company_type.", + "bindings": { + "group_col": "company_type" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n)\nSELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n ROW_NUMBER() OVER (ORDER BY support DESC, value_label) AS support_rank\nFROM grouped\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=9", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 9, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_de0d50470026f862.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de0d50470026f862/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6dd629cbe1116b59016101175376d62fd874ff25 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9296, "bytes_utf8": 9296, "lines": 264, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 378, "bytes_utf8": 378, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14648, "cached_input_tokens": 12032, "output_tokens": 508, "reasoning_output_tokens": 404}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..aced16ee383ed357dfc42ad0fc047e51551711d3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_de1a3d0bc776d971", + "api_calls": 0, + "input_tokens": 14648, + "cached_input_tokens": 12032, + "output_tokens": 508, + "total_tokens": 15156, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11309.93, + "sql_execution_elapsed_ms_total": 10.24, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..f8116c9920ea01331d664f03d258aaae29458696 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:31:30.906877+00:00", + "ended_at": "2026-05-19T15:31:42.216843+00:00", + "elapsed_ms": 11309.93, + "prompt_metrics": { + "chars": 9296, + "bytes_utf8": 9296, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 736, + "bytes_utf8": 736, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 378, + "bytes_utf8": 378, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14648, + "cached_input_tokens": 12032, + "output_tokens": 508, + "reasoning_output_tokens": 404 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..a2638149722a69e67ec31a958c7474ea992f8e9f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "primary_family": "subgroup_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=experience, measure_col=enrollee_id.", + "planned_template_id": "tpl_h2o_group_sum", + "bindings": { + "group_col": "experience", + "measure_col": "enrollee_id", + "top_k": 16, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..d7dd9efb399ff5bfd0fe45df22e6e796e4fb8cb3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40dd-14ed-78c1-af21-97895a377784"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"experience\\\", SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS total_measure\\nFROM \\\"m9\\\"\\nGROUP BY \\\"experience\\\"\\nORDER BY total_measure DESC;\",\"notes\":\"Used the planned grouped-sum template with group_col=\\\"experience\\\" and measure_col=\\\"enrollee_id\\\"; CAST is applied because \\\"enrollee_id\\\" is stored as TEXT in the SQLite schema.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14648,"cached_input_tokens":12032,"output_tokens":508,"reasoning_output_tokens":404}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..dfcec14287b0e030280da2f6a66e5e016552bc7b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_h2o_group_sum\nSELECT \"experience\", SUM(CAST(\"enrollee_id\" AS REAL)) AS total_measure\nFROM \"m9\"\nGROUP BY \"experience\"\nORDER BY total_measure DESC;","notes":"Used the planned grouped-sum template with group_col=\"experience\" and measure_col=\"enrollee_id\"; CAST is applied because \"enrollee_id\" is stored as TEXT in the SQLite schema."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_de1a3d0bc776d971/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..e813b1fef76bf21cb0b1a9cc0e7f5a4538f5fc0f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=city_development_index, measure_col=enrollee_id. +Result preview: [{"city_development_index": "0.664", "enrollee_id": "32091", "total_measure": 32091.0, "share_within_group": 100.0}, {"city_development_index": "0.7809999999999999", "enrollee_id": "18672", "total_measure": 18672.0, "share_within_group": 40.31001057835539}, {"city_development_index": "0.625", "enrollee_id": "17630", "total_measure": 17630.0, "share_within_group": 40.159453302961275}, {"city_development_index": "0.645", "enrollee_id": "30030", "total_measure": 30030.0, "share_within_group": 40.06778032769387}, {"city_development_index": "0.625", "enrollee_id": "16655", "total_measure": 16655.0, "share_within_group": 37.93849658314351}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..1721e95f998bf1ea692b3fa24b02fe1f6ce9acd2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/generated_sql.sql @@ -0,0 +1,22 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_m9_dfc60077c1267844 +-- problem_id: v2p_m9_2ccf330920828aad +-- realization_mode: agent +-- source_kind: agent +SELECT + "city_development_index", + "enrollee_id", + SUM(CAST("enrollee_id" AS REAL)) AS total_measure, + SUM(CAST("enrollee_id" AS REAL)) * 100.0 / SUM(SUM(CAST("enrollee_id" AS REAL))) OVER (PARTITION BY "city_development_index") AS share_within_group +FROM "m9" +GROUP BY "city_development_index", "enrollee_id" +ORDER BY share_within_group DESC +LIMIT 14; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..20303fdbd554acc1ef89661c0347b5b85f6e7a9d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"city_development_index\",\n \"enrollee_id\",\n SUM(CAST(\"enrollee_id\" AS REAL)) AS total_measure,\n SUM(CAST(\"enrollee_id\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"enrollee_id\" AS REAL))) OVER (PARTITION BY \"city_development_index\") AS share_within_group\nFROM \"m9\"\nGROUP BY \"city_development_index\", \"enrollee_id\"\nORDER BY share_within_group DESC\nLIMIT 14;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"city_development_index\\\",\\n \\\"enrollee_id\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"enrollee_id\\\" AS REAL))) OVER (PARTITION BY \\\"city_development_index\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city_development_index\\\", \\\"enrollee_id\\\"\\nORDER BY share_within_group DESC\\nLIMIT 14;\", \"columns\": [\"city_development_index\", \"enrollee_id\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"city_development_index\": \"0.664\", \"enrollee_id\": \"32091\", \"total_measure\": 32091.0, \"share_within_group\": 100.0}, {\"city_development_index\": \"0.7809999999999999\", \"enrollee_id\": \"18672\", \"total_measure\": 18672.0, \"share_within_group\": 40.31001057835539}, {\"city_development_index\": \"0.625\", \"enrollee_id\": \"17630\", \"total_measure\": 17630.0, \"share_within_group\": 40.159453302961275}, {\"city_development_index\": \"0.645\", \"enrollee_id\": \"30030\", \"total_measure\": 30030.0, \"share_within_group\": 40.06778032769387}, {\"city_development_index\": \"0.625\", \"enrollee_id\": \"16655\", \"total_measure\": 16655.0, \"share_within_group\": 37.93849658314351}, {\"city_development_index\": \"0.693\", \"enrollee_id\": \"15060\", \"total_measure\": 15060.0, \"share_within_group\": 37.386425698823295}, {\"city_development_index\": \"0.78\", \"enrollee_id\": \"28600\", \"total_measure\": 28600.0, \"share_within_group\": 36.8532955350815}, {\"city_development_index\": \"0.649\", \"enrollee_id\": \"29251\", \"total_measure\": 29251.0, \"share_within_group\": 34.99886332364167}, {\"city_development_index\": \"0.807\", \"enrollee_id\": \"22169\", \"total_measure\": 22169.0, \"share_within_group\": 34.850890569241166}, {\"city_development_index\": \"0.693\", \"enrollee_id\": \"13253\", \"total_measure\": 13253.0, \"share_within_group\": 32.90055111464178}, {\"city_development_index\": \"0.8240000000000001\", \"enrollee_id\": \"17761\", \"total_measure\": 17761.0, \"share_within_group\": 32.49359678009513}, {\"city_development_index\": \"0.807\", \"enrollee_id\": \"20619\", \"total_measure\": 20619.0, \"share_within_group\": 32.41420509031457}, {\"city_development_index\": \"0.78\", \"enrollee_id\": \"24646\", \"total_measure\": 24646.0, \"share_within_group\": 31.758262998518138}, {\"city_development_index\": \"0.649\", \"enrollee_id\": \"26401\", \"total_measure\": 26401.0, \"share_within_group\": 31.588834248656926}], \"row_count_returned\": 14, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 88.22}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..148018b0d2f1a86cdcf2b2b5d64fbed6cb6ed58f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:33:49.228233+00:00", + "ended_at": "2026-05-19T15:34:09.696052+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_dfc60077c1267844", + "problem_id": "v2p_m9_2ccf330920828aad", + "dataset_id": "m9", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=city_development_index, measure_col=enrollee_id.", + "bindings": { + "group_col": "city_development_index", + "measure_col": "enrollee_id", + "item_col": "enrollee_id", + "top_k": 14, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=1/2", + "binding_index=24" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 1, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_dfc60077c1267844.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_dfc60077c1267844", + "api_calls": 0, + "input_tokens": 14775, + "cached_input_tokens": 13696, + "output_tokens": 927, + "total_tokens": 15702, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 20374.3, + "sql_execution_elapsed_ms_total": 88.22, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..d03816329a49e14c3a43c869c0ebb90208dcb3ab --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:34:09.606136+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 20374.3, "started_at": "2026-05-19T15:33:49.230217+00:00", "ended_at": "2026-05-19T15:34:09.604552+00:00", "prompt_metrics": {"chars": 9732, "bytes_utf8": 9732, "lines": 266, "estimated_tokens": null}, "response_metrics": {"chars": 687, "bytes_utf8": 687, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14775, "cached_input_tokens": 13696, "output_tokens": 927, "reasoning_output_tokens": 730}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"city_development_index\\\",\\n \\\"enrollee_id\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"enrollee_id\\\" AS REAL))) OVER (PARTITION BY \\\"city_development_index\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city_development_index\\\", \\\"enrollee_id\\\"\\nORDER BY share_within_group DESC\\nLIMIT 14;\",\"notes\":\"Used the planned template and bindings with \\\"city_development_index\\\" as group_col and \\\"enrollee_id\\\" as both item_col and measure_col. CAST is applied because the schema stores \\\"enrollee_id\\\" as TEXT while the template requires SUM().\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..0518796f265b16c9a83033bcf9a6a5edf56177e7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_dfc60077c1267844", + "api_calls": 0, + "input_tokens": 14775, + "cached_input_tokens": 13696, + "output_tokens": 927, + "total_tokens": 15702, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 20374.3, + "sql_execution_elapsed_ms_total": 88.22, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_dfc60077c1267844/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..7501155d27431a4259a405f3cd3f055826c4be1a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=relevent_experience, measure_col=training_hours. +Result preview: [{"relevent_experience": "Has relevent experience", "city_development_index": "0.92", "total_measure": 261008.0, "share_within_group": 28.760705045420686}, {"relevent_experience": "No relevent experience", "city_development_index": "0.92", "total_measure": 82511.0, "share_within_group": 23.931284315061937}, {"relevent_experience": "No relevent experience", "city_development_index": "0.624", "total_measure": 54166.0, "share_within_group": 15.710171325152341}, {"relevent_experience": "Has relevent experience", "city_development_index": "0.624", "total_measure": 123456.0, "share_within_group": 13.603727096822535}, {"relevent_experience": "Has relevent experience", "city_development_index": "0.91", "total_measure": 78947.0, "share_within_group": 8.699240564353687}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..e202a6cfd504998cc3fe279797d63e0f8a23a58f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/generated_sql.sql @@ -0,0 +1,29 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_m9_e05a029cf72ca8ce +-- problem_id: v2p_m9_695f10b97b3e86a5 +-- realization_mode: agent +-- source_kind: agent +SELECT + "relevent_experience", + "city_development_index", + SUM(CAST("training_hours" AS REAL)) AS total_measure, + SUM(CAST("training_hours" AS REAL)) * 100.0 + / SUM(SUM(CAST("training_hours" AS REAL))) OVER (PARTITION BY "relevent_experience") AS share_within_group +FROM "m9" +WHERE "relevent_experience" IS NOT NULL + AND "relevent_experience" <> '' + AND "city_development_index" IS NOT NULL + AND "city_development_index" <> '' + AND "training_hours" IS NOT NULL + AND "training_hours" <> '' +GROUP BY "relevent_experience", "city_development_index" +ORDER BY share_within_group DESC +LIMIT 11; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f0697b7fd938fac8a3e4f2d9db09e073cfd2c058 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"relevent_experience\",\n \"city_development_index\",\n SUM(CAST(\"training_hours\" AS REAL)) AS total_measure,\n SUM(CAST(\"training_hours\" AS REAL)) * 100.0\n / SUM(SUM(CAST(\"training_hours\" AS REAL))) OVER (PARTITION BY \"relevent_experience\") AS share_within_group\nFROM \"m9\"\nWHERE \"relevent_experience\" IS NOT NULL\n AND \"relevent_experience\" <> ''\n AND \"city_development_index\" IS NOT NULL\n AND \"city_development_index\" <> ''\n AND \"training_hours\" IS NOT NULL\n AND \"training_hours\" <> ''\nGROUP BY \"relevent_experience\", \"city_development_index\"\nORDER BY share_within_group DESC\nLIMIT 11;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"relevent_experience\\\",\\n \\\"city_development_index\\\",\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) * 100.0\\n / SUM(SUM(CAST(\\\"training_hours\\\" AS REAL))) OVER (PARTITION BY \\\"relevent_experience\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nWHERE \\\"relevent_experience\\\" IS NOT NULL\\n AND \\\"relevent_experience\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n AND \\\"training_hours\\\" IS NOT NULL\\n AND \\\"training_hours\\\" <> ''\\nGROUP BY \\\"relevent_experience\\\", \\\"city_development_index\\\"\\nORDER BY share_within_group DESC\\nLIMIT 11;\", \"columns\": [\"relevent_experience\", \"city_development_index\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"relevent_experience\": \"Has relevent experience\", \"city_development_index\": \"0.92\", \"total_measure\": 261008.0, \"share_within_group\": 28.760705045420686}, {\"relevent_experience\": \"No relevent experience\", \"city_development_index\": \"0.92\", \"total_measure\": 82511.0, \"share_within_group\": 23.931284315061937}, {\"relevent_experience\": \"No relevent experience\", \"city_development_index\": \"0.624\", \"total_measure\": 54166.0, \"share_within_group\": 15.710171325152341}, {\"relevent_experience\": \"Has relevent experience\", \"city_development_index\": \"0.624\", \"total_measure\": 123456.0, \"share_within_group\": 13.603727096822535}, {\"relevent_experience\": \"Has relevent experience\", \"city_development_index\": \"0.91\", \"total_measure\": 78947.0, \"share_within_group\": 8.699240564353687}, {\"relevent_experience\": \"No relevent experience\", \"city_development_index\": \"0.9259999999999999\", \"total_measure\": 25249.0, \"share_within_group\": 7.323156884185125}, {\"relevent_experience\": \"No relevent experience\", \"city_development_index\": \"0.91\", \"total_measure\": 23096.0, \"share_within_group\": 6.698706142704252}, {\"relevent_experience\": \"Has relevent experience\", \"city_development_index\": \"0.9259999999999999\", \"total_measure\": 56512.0, \"share_within_group\": 6.22710784162483}, {\"relevent_experience\": \"No relevent experience\", \"city_development_index\": \"0.698\", \"total_measure\": 17580.0, \"share_within_group\": 5.098859282505228}, {\"relevent_experience\": \"Has relevent experience\", \"city_development_index\": \"0.897\", \"total_measure\": 27205.0, \"share_within_group\": 2.9977432904764214}, {\"relevent_experience\": \"No relevent experience\", \"city_development_index\": \"0.897\", \"total_measure\": 10091.0, \"share_within_group\": 2.9267684311581488}], \"row_count_returned\": 11, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 35.86}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..51ad4875490dbd747c9cec8b881c6344ce973b91 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:35:12.158089+00:00", + "ended_at": "2026-05-19T15:35:27.452467+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_e05a029cf72ca8ce", + "problem_id": "v2p_m9_695f10b97b3e86a5", + "dataset_id": "m9", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=relevent_experience, measure_col=training_hours.", + "bindings": { + "group_col": "relevent_experience", + "measure_col": "training_hours", + "item_col": "city_development_index", + "top_k": 11, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=1/2", + "binding_index=26" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_e05a029cf72ca8ce.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_e05a029cf72ca8ce", + "api_calls": 0, + "input_tokens": 14772, + "cached_input_tokens": 12032, + "output_tokens": 790, + "total_tokens": 15562, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15252.92, + "sql_execution_elapsed_ms_total": 35.86, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..817e2a55d5464b68913dba9597aa0ce4f3790513 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:35:27.414023+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15252.92, "started_at": "2026-05-19T15:35:12.159835+00:00", "ended_at": "2026-05-19T15:35:27.412793+00:00", "prompt_metrics": {"chars": 9739, "bytes_utf8": 9739, "lines": 266, "estimated_tokens": null}, "response_metrics": {"chars": 1015, "bytes_utf8": 1015, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14772, "cached_input_tokens": 12032, "output_tokens": 790, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"relevent_experience\\\",\\n \\\"city_development_index\\\",\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) * 100.0\\n / SUM(SUM(CAST(\\\"training_hours\\\" AS REAL))) OVER (PARTITION BY \\\"relevent_experience\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nWHERE \\\"relevent_experience\\\" IS NOT NULL\\n AND \\\"relevent_experience\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n AND \\\"training_hours\\\" IS NOT NULL\\n AND \\\"training_hours\\\" <> ''\\nGROUP BY \\\"relevent_experience\\\", \\\"city_development_index\\\"\\nORDER BY share_within_group DESC\\nLIMIT 11;\",\"notes\":\"Uses the requested Within-Group Share of Total template with group_col=\\\"relevent_experience\\\", item_col=\\\"city_development_index\\\", and measure_col=\\\"training_hours\\\". CAST is applied because \\\"training_hours\\\" is stored as TEXT in the schema snapshot, and blank values are excluded before"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..f58bb658b0206acd66452e54908f4ea44b157d2c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_e05a029cf72ca8ce", + "api_calls": 0, + "input_tokens": 14772, + "cached_input_tokens": 12032, + "output_tokens": 790, + "total_tokens": 15562, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15252.92, + "sql_execution_elapsed_ms_total": 35.86, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e05a029cf72ca8ce/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..44dd7b0b6d9f8c45a4a95f96dc465a3351dd25f4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9600, "bytes_utf8": 9600, "lines": 267, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 554, "bytes_utf8": 554, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14719, "cached_input_tokens": 13696, "output_tokens": 376, "reasoning_output_tokens": 238}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..f2d58b91cd635a078bbb57b51db261fef1a7241d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_e184c88223563dd8", + "api_calls": 0, + "input_tokens": 14719, + "cached_input_tokens": 13696, + "output_tokens": 376, + "total_tokens": 15095, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 10570.82, + "sql_execution_elapsed_ms_total": 21.19, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..feca724767ac8a0e04076a05949d24e1fc0b79b9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:59:35.152841+00:00", + "ended_at": "2026-05-19T15:59:45.723696+00:00", + "elapsed_ms": 10570.82, + "prompt_metrics": { + "chars": 9600, + "bytes_utf8": 9600, + "lines": 267, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 909, + "bytes_utf8": 909, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 554, + "bytes_utf8": 554, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14719, + "cached_input_tokens": 13696, + "output_tokens": 376, + "reasoning_output_tokens": 238 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..b13999410983bf18772eb56fbf89434bd863d627 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,267 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Condition Rate to probe direction_consistency with semantic role focused_target_view. Focus on group_col=gender, condition_col=relevent_experience.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "gender", + "condition_col": "relevent_experience", + "condition_value": "Has relevent experience", + "positive_value": "Has relevent experience", + "negative_value": "No relevent experience", + "top_k": 12, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..24bbe004445264176e0144926797c13702abd294 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f6-c7f5-7531-8e10-fc47f2de9a65"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"gender\\\",\\n AVG(CASE WHEN \\\"relevent_experience\\\" = 'Has relevent experience' THEN 1 ELSE 0 END) AS condition_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"gender\\\"\\nORDER BY condition_rate DESC;\",\"notes\":\"Instantiated the Grouped Condition Rate template with group_col=\\\"gender\\\" and condition_col=\\\"relevent_experience\\\", measuring the share of rows in each gender group where relevent_experience is 'Has relevent experience'. Empty-string gender values, if present, will appear as their own group.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14719,"cached_input_tokens":13696,"output_tokens":376,"reasoning_output_tokens":238}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..cb3a178e373fb4e2e6483079a85d94c3142db8e0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_m4_group_condition_rate\nSELECT \"gender\",\n AVG(CASE WHEN \"relevent_experience\" = 'Has relevent experience' THEN 1 ELSE 0 END) AS condition_rate\nFROM \"m9\"\nGROUP BY \"gender\"\nORDER BY condition_rate DESC;","notes":"Instantiated the Grouped Condition Rate template with group_col=\"gender\" and condition_col=\"relevent_experience\", measuring the share of rows in each gender group where relevent_experience is 'Has relevent experience'. Empty-string gender values, if present, will appear as their own group."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e184c88223563dd8/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..4ac6b3afd9ebff6fbcc7810282e69c7ae89e79e2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/generated_sql.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_set_consistency +-- intended_facet_id: low_support_extremes +-- variant_semantic_role: rare_extreme_view +-- template_id: tpl_tail_low_support_group_count_v2 +-- query_record_id: v2q_m9_e1a797e538210d87 +-- problem_id: v2p_m9_7f643487079c2470 +-- realization_mode: agent +-- source_kind: agent +SELECT + "relevent_experience", + COUNT(*) AS "support" +FROM "m9" +GROUP BY "relevent_experience" +ORDER BY "support" ASC, "relevent_experience" +LIMIT 12; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..cc609693ca3b3d3bba61a8f0c215d984c0e27ec6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n \"relevent_experience\",\n COUNT(*) AS \"support\"\nFROM \"m9\"\nGROUP BY \"relevent_experience\"\nORDER BY \"support\" ASC, \"relevent_experience\"\nLIMIT 12;", "result": "{\"query\": \"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"relevent_experience\\\",\\n COUNT(*) AS \\\"support\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"relevent_experience\\\"\\nORDER BY \\\"support\\\" ASC, \\\"relevent_experience\\\"\\nLIMIT 12;\", \"columns\": [\"relevent_experience\", \"support\"], \"rows\": [{\"relevent_experience\": \"No relevent experience\", \"support\": 5366}, {\"relevent_experience\": \"Has relevent experience\", \"support\": 13792}], \"row_count_returned\": 2, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 14.72}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..cf351c334d5ed670b3e8cfeedb3841796d41d539 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/run_manifest.json @@ -0,0 +1,87 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:04:39.287569+00:00", + "ended_at": "2026-05-19T16:04:47.830642+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_e1a797e538210d87", + "problem_id": "v2p_m9_7f643487079c2470", + "dataset_id": "m9", + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_set_consistency", + "intended_facet_id": "low_support_extremes", + "variant_semantic_role": "rare_extreme_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role rare_extreme_view. Focus on group_col=relevent_experience.", + "bindings": { + "group_col": "relevent_experience", + "top_k": 12, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "notes": [ + "default_facets=low_support_extremes", + "template_selection_mode=rule", + "problem_index_within_template=3", + "sql_variant_index=1/2", + "binding_index=122" + ], + "template_selection_mode": "rule", + "selected_template_rank": 11, + "problem_index_within_template": 3, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_e1a797e538210d87.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_e1a797e538210d87", + "api_calls": 0, + "input_tokens": 14662, + "cached_input_tokens": 13696, + "output_tokens": 354, + "total_tokens": 15016, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8521.06, + "sql_execution_elapsed_ms_total": 14.72, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..e98e2db6599496b64f4b9b9d37bf54c9db773eeb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_e1a797e538210d87", + "api_calls": 0, + "input_tokens": 14662, + "cached_input_tokens": 13696, + "output_tokens": 354, + "total_tokens": 15016, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8521.06, + "sql_execution_elapsed_ms_total": 14.72, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e1a797e538210d87/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e23caf085b15d3d5/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e23caf085b15d3d5/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..63ef1211b12c201ae3d4fe421258a5b11ca6ec3d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e23caf085b15d3d5/run_manifest.json @@ -0,0 +1,69 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:54:07.089740+00:00", + "ended_at": "2026-05-19T15:54:14.445552+00:00", + "status": "failed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_e23caf085b15d3d5", + "problem_id": "v2p_m9_d4585f4786f0e61d", + "dataset_id": "m9", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role focused_target_view. Focus on group_col=enrolled_university, measure_col=enrollee_id.", + "bindings": { + "group_col": "enrolled_university", + "measure_col": "enrollee_id", + "top_k": 17, + "top_n": 7, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=2/2", + "binding_index=87" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 4, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "error": "AI CLI command failed with exit code 1: " +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e23caf085b15d3d5/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e23caf085b15d3d5/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c97bb2681ab6d263eaea29c197f78c03bfc5f40e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e23caf085b15d3d5/trace.jsonl @@ -0,0 +1,2 @@ +{"timestamp": "2026-05-19T15:54:10.199131+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3105.93, "started_at": "2026-05-19T15:54:07.091928+00:00", "ended_at": "2026-05-19T15:54:10.197881+00:00", "prompt_metrics": {"chars": 9494, "bytes_utf8": 9494, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f1-c681-7022-8abb-6910eea16bb0\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} +{"timestamp": "2026-05-19T15:54:14.445445+00:00", "event_type": "ai_cli_sql_generation_error", "engine": "v2-cli:codex", "attempt": 2, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 1, "elapsed_ms": 3243.61, "started_at": "2026-05-19T15:54:11.201050+00:00", "ended_at": "2026-05-19T15:54:14.444708+00:00", "prompt_metrics": {"chars": 9494, "bytes_utf8": 9494, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 280, "bytes_utf8": 280, "lines": 4, "estimated_tokens": null}, "usage": {}, "stderr_preview": "", "stdout_preview": "{\"type\":\"thread.started\",\"thread_id\":\"019e40f1-d683-7412-ae8b-55251249d589\"}\n{\"type\":\"turn.started\"}\n{\"type\":\"error\",\"message\":\"Quota exceeded. Check your plan and billing details.\"}\n{\"type\":\"turn.failed\",\"error\":{\"message\":\"Quota exceeded. Check your plan and billing details.\"}}", "error": "AI CLI command failed with exit code 1: "} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..6a73cb4243845501e2646d57861a4b686afc19e2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:53:59.877514+00:00", + "ended_at": "2026-05-19T15:54:02.785330+00:00", + "elapsed_ms": 2907.79, + "returncode": 1, + "prompt_metrics": { + "chars": 9490, + "bytes_utf8": 9490, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..b0f8a6ce4dbf407bac635c2f315eb1e3de54ac4d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:54:03.787575+00:00", + "ended_at": "2026-05-19T15:54:07.088549+00:00", + "elapsed_ms": 3300.93, + "returncode": 1, + "prompt_metrics": { + "chars": 9490, + "bytes_utf8": 9490, + "lines": 264, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..1b8e47e3972d0830c61c2a7b93db4e7bc8c123eb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=enrolled_university, measure_col=enrollee_id.", + "planned_template_id": "tpl_grouped_percentile_point", + "bindings": { + "group_col": "enrolled_university", + "measure_col": "enrollee_id", + "top_k": 12, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..1b8e47e3972d0830c61c2a7b93db4e7bc8c123eb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,264 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "required_roles": [ + "group_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=enrolled_university, measure_col=enrollee_id.", + "planned_template_id": "tpl_grouped_percentile_point", + "bindings": { + "group_col": "enrolled_university", + "measure_col": "enrollee_id", + "top_k": 12, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..062cf88fd0bca3f5e101a01d78b9b851ba8a6b69 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f1-aa32-7200-97bb-cf2c04cca01c"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..3f56a2d919c1b99836594bd2e82f7968868e03bb --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f1-aa32-7200-97bb-cf2c04cca01c"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..f06300f9491bbebf6bfc1b91c1e9357efb011276 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f1-b9ce-7273-9cf3-3ac46477b2db"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..a37b25357ca66b3a970b70ededbdf51fa1fe7f10 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f1-b9ce-7273-9cf3-3ac46477b2db"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e39abd54e4efa193/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..3c1fbbfc502ce3527f253e3a3e071a2157c198f3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"total_rows": 19158, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..0fbbd9d204fa28dfdbbea612b816af3a37e005e6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: marginal_missing_rate_consistency +-- intended_facet_id: missing_indicator_distribution +-- variant_semantic_role: missing_indicator_view +-- template_id: tpl_missing_marginal_rate_profile +-- query_record_id: v2q_m9_e598956285297f9b +-- problem_id: v2p_m9_a82b7afbc7d3cbc3 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + COUNT(*) AS total_rows, + SUM(CASE WHEN "experience" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "experience" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9"; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..04a5ba7fd3dc161da5db63ac1682205eae06fe16 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: marginal_missing_rate_consistency\n-- intended_facet_id: missing_indicator_distribution\n-- variant_semantic_role: missing_indicator_view\n-- template_id: tpl_missing_marginal_rate_profile\n-- query_record_id: v2q_m9_e598956285297f9b\n-- problem_id: v2p_m9_a82b7afbc7d3cbc3\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"experience\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"experience\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\";", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: marginal_missing_rate_consistency\\n-- intended_facet_id: missing_indicator_distribution\\n-- variant_semantic_role: missing_indicator_view\\n-- template_id: tpl_missing_marginal_rate_profile\\n-- query_record_id: v2q_m9_e598956285297f9b\\n-- problem_id: v2p_m9_a82b7afbc7d3cbc3\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"experience\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"experience\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\";\", \"columns\": [\"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"total_rows\": 19158, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 1, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 2.9}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..73d182a77833afc3ccd701ba4d3eea5dcd39fdda --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:55.918830+00:00", + "ended_at": "2026-05-19T16:08:55.922467+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_e598956285297f9b", + "problem_id": "v2p_m9_a82b7afbc7d3cbc3", + "dataset_id": "m9", + "template_id": "tpl_missing_marginal_rate_profile", + "template_name": "Marginal Missing Rate Profile", + "family_id": "missingness_structure", + "canonical_subitem_id": "marginal_missing_rate_consistency", + "intended_facet_id": "missing_indicator_distribution", + "variant_semantic_role": "missing_indicator_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Marginal Missing Rate Profile to probe marginal_missing_rate_consistency with semantic role missing_indicator_view. Focus on missing_col=experience.", + "bindings": { + "missing_col": "experience" + }, + "binding_roles": [ + "missing_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table};", + "notes": [ + "default_facets=missing_indicator_distribution", + "template_selection_mode=deterministic", + "problem_index_within_template=5", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_e598956285297f9b.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e598956285297f9b/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..eb9ab2c6991074bc8952441ab63932312964d9fa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=enrolled_university, measure_col=enrollee_id. +Result preview: [{"enrolled_university": "no_enrollment", "total_measure": 229978469}, {"enrolled_university": "Full time course", "total_measure": 65323820}, {"enrolled_university": "Part time course", "total_measure": 21118449}, {"enrolled_university": "", "total_measure": 6877374}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..35bb21f0094823a1fa2bc6564e5bab59f6d40169 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/generated_sql.sql @@ -0,0 +1,17 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: subgroup_structure +-- canonical_subitem_id: internal_profile_stability +-- intended_facet_id: subgroup_distribution_shift +-- variant_semantic_role: collapsed_target_view +-- template_id: tpl_h2o_group_sum +-- query_record_id: v2q_m9_e78405547a3b2e49 +-- problem_id: v2p_m9_b48ec2ff4338e146 +-- realization_mode: agent +-- source_kind: agent +SELECT "enrolled_university", SUM(CAST("enrollee_id" AS NUMERIC)) AS "total_measure" +FROM "m9" +GROUP BY "enrolled_university" +ORDER BY "total_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..b0503aa8fd92d2361888e34d075094a7985c25d6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_h2o_group_sum\nSELECT \"enrolled_university\", SUM(CAST(\"enrollee_id\" AS NUMERIC)) AS \"total_measure\"\nFROM \"m9\"\nGROUP BY \"enrolled_university\"\nORDER BY \"total_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"enrolled_university\\\", SUM(CAST(\\\"enrollee_id\\\" AS NUMERIC)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"enrolled_university\\\"\\nORDER BY \\\"total_measure\\\" DESC;\", \"columns\": [\"enrolled_university\", \"total_measure\"], \"rows\": [{\"enrolled_university\": \"no_enrollment\", \"total_measure\": 229978469}, {\"enrolled_university\": \"Full time course\", \"total_measure\": 65323820}, {\"enrolled_university\": \"Part time course\", \"total_measure\": 21118449}, {\"enrolled_university\": \"\", \"total_measure\": 6877374}], \"row_count_returned\": 4, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 11.52}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e97c8a68b87332c8496def4b10a558953441bf45 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:29:26.260593+00:00", + "ended_at": "2026-05-19T15:29:34.556605+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_e78405547a3b2e49", + "problem_id": "v2p_m9_b48ec2ff4338e146", + "dataset_id": "m9", + "template_id": "tpl_h2o_group_sum", + "template_name": "Grouped Numeric Sum", + "family_id": "subgroup_structure", + "canonical_subitem_id": "internal_profile_stability", + "intended_facet_id": "subgroup_distribution_shift", + "variant_semantic_role": "collapsed_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Numeric Sum to probe internal_profile_stability with semantic role collapsed_target_view. Focus on group_col=enrolled_university, measure_col=enrollee_id.", + "bindings": { + "group_col": "enrolled_university", + "measure_col": "enrollee_id", + "top_k": 13, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, SUM({measure_col}) AS total_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY total_measure DESC;", + "notes": [ + "default_facets=subgroup_distribution_shift,subgroup_rank_order,subgroup_conditional_contrast", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=1/2", + "binding_index=3" + ], + "template_selection_mode": "rule", + "selected_template_rank": 1, + "problem_index_within_template": 4, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_e78405547a3b2e49.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_e78405547a3b2e49", + "api_calls": 0, + "input_tokens": 14653, + "cached_input_tokens": 12032, + "output_tokens": 342, + "total_tokens": 14995, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8278.27, + "sql_execution_elapsed_ms_total": 11.52, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..049abe915cf8cf3ded0e3cca45aa3e2cd86eb076 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:29:34.543350+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8278.27, "started_at": "2026-05-19T15:29:26.263623+00:00", "ended_at": "2026-05-19T15:29:34.541934+00:00", "prompt_metrics": {"chars": 9312, "bytes_utf8": 9312, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 458, "bytes_utf8": 458, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14653, "cached_input_tokens": 12032, "output_tokens": 342, "reasoning_output_tokens": 218}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_h2o_group_sum\\nSELECT \\\"enrolled_university\\\", SUM(CAST(\\\"enrollee_id\\\" AS NUMERIC)) AS \\\"total_measure\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"enrolled_university\\\"\\nORDER BY \\\"total_measure\\\" DESC;\",\"notes\":\"Used the required Grouped Numeric Sum template with group_col=\\\"enrolled_university\\\" and measure_col=\\\"enrollee_id\\\". CAST was added because \\\"enrollee_id\\\" is stored as TEXT in SQLite schema but represents numeric values for SUM.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..2c41e83e061bd14eba7698cfc02e76be22a95540 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_e78405547a3b2e49", + "api_calls": 0, + "input_tokens": 14653, + "cached_input_tokens": 12032, + "output_tokens": 342, + "total_tokens": 14995, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8278.27, + "sql_execution_elapsed_ms_total": 11.52, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e78405547a3b2e49/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..d6f1b24b07a160803356ab0414860c7cf85a53b2 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=city_development_index, measure_col=enrollee_id. +Result preview: [{"city_development_index": "0.725", "percentile_measure": 33298.0}, {"city_development_index": "0.48700000000000004", "percentile_measure": 33174.0}, {"city_development_index": "0.7879999999999999", "percentile_measure": 33032.0}, {"city_development_index": "0.516", "percentile_measure": 32947.0}, {"city_development_index": "0.479", "percentile_measure": 32820.0}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..49d4333effa58548562807d01fdbfb3b47438129 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/generated_sql.sql @@ -0,0 +1,37 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_concentration_consistency +-- intended_facet_id: rare_target_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_grouped_percentile_point +-- query_record_id: v2q_m9_e84efb012fbfa8e2 +-- problem_id: v2p_m9_2a6decb54fabdafe +-- realization_mode: agent +-- source_kind: agent +WITH "ranked" AS ( + SELECT + "city_development_index", + CAST("enrollee_id" AS REAL) AS "measure_value", + ROW_NUMBER() OVER ( + PARTITION BY "city_development_index" + ORDER BY CAST("enrollee_id" AS REAL) + ) AS "rn", + COUNT(*) OVER ( + PARTITION BY "city_development_index" + ) AS "cnt" + FROM "m9" + WHERE "city_development_index" IS NOT NULL + AND "city_development_index" <> '' + AND "enrollee_id" IS NOT NULL + AND "enrollee_id" <> '' +) +SELECT + "city_development_index", + MIN(CASE WHEN "rn" >= 0.9 * "cnt" THEN "measure_value" END) AS "percentile_measure" +FROM "ranked" +WHERE "cnt" >= 5 +GROUP BY "city_development_index" +ORDER BY "percentile_measure" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..60df866e44348e8f59b9e8fcc5b07972def38d61 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_grouped_percentile_point\nWITH \"ranked\" AS (\n SELECT\n \"city_development_index\",\n CAST(\"enrollee_id\" AS REAL) AS \"measure_value\",\n ROW_NUMBER() OVER (\n PARTITION BY \"city_development_index\"\n ORDER BY CAST(\"enrollee_id\" AS REAL)\n ) AS \"rn\",\n COUNT(*) OVER (\n PARTITION BY \"city_development_index\"\n ) AS \"cnt\"\n FROM \"m9\"\n WHERE \"city_development_index\" IS NOT NULL\n AND \"city_development_index\" <> ''\n AND \"enrollee_id\" IS NOT NULL\n AND \"enrollee_id\" <> ''\n)\nSELECT\n \"city_development_index\",\n MIN(CASE WHEN \"rn\" >= 0.9 * \"cnt\" THEN \"measure_value\" END) AS \"percentile_measure\"\nFROM \"ranked\"\nWHERE \"cnt\" >= 5\nGROUP BY \"city_development_index\"\nORDER BY \"percentile_measure\" DESC;", "result": "{\"query\": \"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"city_development_index\\\",\\n CAST(\\\"enrollee_id\\\" AS REAL) AS \\\"measure_value\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"city_development_index\\\"\\n ORDER BY CAST(\\\"enrollee_id\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"city_development_index\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\n)\\nSELECT\\n \\\"city_development_index\\\",\\n MIN(CASE WHEN \\\"rn\\\" >= 0.9 * \\\"cnt\\\" THEN \\\"measure_value\\\" END) AS \\\"percentile_measure\\\"\\nFROM \\\"ranked\\\"\\nWHERE \\\"cnt\\\" >= 5\\nGROUP BY \\\"city_development_index\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\", \"columns\": [\"city_development_index\", \"percentile_measure\"], \"rows\": [{\"city_development_index\": \"0.725\", \"percentile_measure\": 33298.0}, {\"city_development_index\": \"0.48700000000000004\", \"percentile_measure\": 33174.0}, {\"city_development_index\": \"0.7879999999999999\", \"percentile_measure\": 33032.0}, {\"city_development_index\": \"0.516\", \"percentile_measure\": 32947.0}, {\"city_development_index\": \"0.479\", \"percentile_measure\": 32820.0}, {\"city_development_index\": \"0.555\", \"percentile_measure\": 32720.0}, {\"city_development_index\": \"0.563\", \"percentile_measure\": 32678.0}, {\"city_development_index\": \"0.518\", \"percentile_measure\": 32400.0}, {\"city_development_index\": \"0.64\", \"percentile_measure\": 32030.0}, {\"city_development_index\": \"0.735\", \"percentile_measure\": 31747.0}, {\"city_development_index\": \"0.843\", \"percentile_measure\": 31491.0}, {\"city_development_index\": \"0.9209999999999999\", \"percentile_measure\": 31455.0}, {\"city_development_index\": \"0.512\", \"percentile_measure\": 31443.0}, {\"city_development_index\": \"0.764\", \"percentile_measure\": 31287.0}, {\"city_development_index\": \"0.44799999999999995\", \"percentile_measure\": 31179.0}, {\"city_development_index\": \"0.691\", \"percentile_measure\": 31126.0}, {\"city_development_index\": \"0.83\", \"percentile_measure\": 31124.0}, {\"city_development_index\": \"0.6890000000000001\", \"percentile_measure\": 31016.0}, {\"city_development_index\": \"0.74\", \"percentile_measure\": 30988.0}, {\"city_development_index\": \"0.903\", \"percentile_measure\": 30926.0}, {\"city_development_index\": \"0.682\", \"percentile_measure\": 30841.0}, {\"city_development_index\": \"0.556\", \"percentile_measure\": 30835.0}, {\"city_development_index\": \"0.579\", \"percentile_measure\": 30768.0}, {\"city_development_index\": \"0.6659999999999999\", \"percentile_measure\": 30754.0}, {\"city_development_index\": \"0.9129999999999999\", \"percentile_measure\": 30693.0}, {\"city_development_index\": \"0.856\", \"percentile_measure\": 30661.0}, {\"city_development_index\": \"0.915\", \"percentile_measure\": 30600.0}, {\"city_development_index\": \"0.92\", \"percentile_measure\": 30549.0}, {\"city_development_index\": \"0.624\", \"percentile_measure\": 30467.0}, {\"city_development_index\": \"0.775\", \"percentile_measure\": 30422.0}, {\"city_development_index\": \"0.527\", \"percentile_measure\": 30368.0}, {\"city_development_index\": \"0.848\", \"percentile_measure\": 30325.0}, {\"city_development_index\": \"0.73\", \"percentile_measure\": 30275.0}, {\"city_development_index\": \"0.91\", \"percentile_measure\": 30217.0}, {\"city_development_index\": \"0.767\", \"percentile_measure\": 30126.0}, {\"city_development_index\": \"0.7959999999999999\", \"percentile_measure\": 30121.0}, {\"city_development_index\": \"0.493\", \"percentile_measure\": 30094.0}, {\"city_development_index\": \"0.645\", \"percentile_measure\": 30030.0}, {\"city_development_index\": \"0.8270000000000001\", \"percentile_measure\": 29972.0}, {\"city_development_index\": \"0.701\", \"percentile_measure\": 29881.0}, {\"city_development_index\": \"0.762\", \"percentile_measure\": 29879.0}, {\"city_development_index\": \"0.9490000000000001\", \"percentile_measure\": 29860.0}, {\"city_development_index\": \"0.9229999999999999\", \"percentile_measure\": 29856.0}, {\"city_development_index\": \"0.5579999999999999\", \"percentile_measure\": 29837.0}, {\"city_development_index\": \"0.722\", \"percentile_measure\": 29826.0}, {\"city_development_index\": \"0.754\", \"percentile_measure\": 29801.0}, {\"city_development_index\": \"0.7659999999999999\", \"percentile_measure\": 29742.0}, {\"city_development_index\": \"0.9390000000000001\", \"percentile_measure\": 29719.0}, {\"city_development_index\": \"0.727\", \"percentile_measure\": 29685.0}, {\"city_development_index\": \"0.897\", \"percentile_measure\": 29679.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 51.43}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..8792b95960ab9f64752d0f0ad8778a54a5531ae3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:51:10.966175+00:00", + "ended_at": "2026-05-19T15:51:45.430602+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_e84efb012fbfa8e2", + "problem_id": "v2p_m9_2a6decb54fabdafe", + "dataset_id": "m9", + "template_id": "tpl_grouped_percentile_point", + "template_name": "Grouped Percentile Point", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_concentration_consistency", + "intended_facet_id": "rare_target_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Percentile Point to probe tail_concentration_consistency with semantic role ranked_signal_view. Focus on group_col=city_development_index, measure_col=enrollee_id.", + "bindings": { + "group_col": "city_development_index", + "measure_col": "enrollee_id", + "top_k": 19, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n PERCENTILE_CONT({percentile_value}) WITHIN GROUP (ORDER BY {measure_col}) AS percentile_measure\nFROM {table}\nGROUP BY {group_col}\nORDER BY percentile_measure DESC;", + "notes": [ + "default_facets=rare_target_concentration", + "template_selection_mode=rule", + "problem_index_within_template=1", + "sql_variant_index=2/2", + "binding_index=84" + ], + "template_selection_mode": "rule", + "selected_template_rank": 8, + "problem_index_within_template": 1, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_e84efb012fbfa8e2.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_e84efb012fbfa8e2", + "api_calls": 0, + "input_tokens": 14692, + "cached_input_tokens": 12032, + "output_tokens": 1655, + "total_tokens": 16347, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 34407.87, + "sql_execution_elapsed_ms_total": 51.43, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9ecc0c83807f1f4e5652c0f1126836fdc2c15898 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:51:45.376735+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 34407.87, "started_at": "2026-05-19T15:51:10.967967+00:00", "ended_at": "2026-05-19T15:51:45.375860+00:00", "prompt_metrics": {"chars": 9498, "bytes_utf8": 9498, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 1123, "bytes_utf8": 1123, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14692, "cached_input_tokens": 12032, "output_tokens": 1655, "reasoning_output_tokens": 1338}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_grouped_percentile_point\\nWITH \\\"ranked\\\" AS (\\n SELECT\\n \\\"city_development_index\\\",\\n CAST(\\\"enrollee_id\\\" AS REAL) AS \\\"measure_value\\\",\\n ROW_NUMBER() OVER (\\n PARTITION BY \\\"city_development_index\\\"\\n ORDER BY CAST(\\\"enrollee_id\\\" AS REAL)\\n ) AS \\\"rn\\\",\\n COUNT(*) OVER (\\n PARTITION BY \\\"city_development_index\\\"\\n ) AS \\\"cnt\\\"\\n FROM \\\"m9\\\"\\n WHERE \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\n)\\nSELECT\\n \\\"city_development_index\\\",\\n MIN(CASE WHEN \\\"rn\\\" >= 0.9 * \\\"cnt\\\" THEN \\\"measure_value\\\" END) AS \\\"percentile_measure\\\"\\nFROM \\\"ranked\\\"\\nWHERE \\\"cnt\\\" >= 5\\nGROUP BY \\\"city_development_index\\\"\\nORDER BY \\\"percentile_measure\\\" DESC;\",\"notes\":\"SQLite does not support PERCENTILE_CONT, so this uses a nearest-rank 90th percentile approximation with window functions. It groups by \\\"city_development_index\\\", casts t"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..0445d978df19b28172b41954f59fb96ecb241d8c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_e84efb012fbfa8e2", + "api_calls": 0, + "input_tokens": 14692, + "cached_input_tokens": 12032, + "output_tokens": 1655, + "total_tokens": 16347, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 34407.87, + "sql_execution_elapsed_ms_total": 51.43, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_e84efb012fbfa8e2/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..e78395bc8a8a476a00ca478b8e4786fc837ecffe --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=gender, measure_col=city_development_index. +Result preview: [{"gender": "Female", "city": "city_103", "total_measure": 386.40000000000003, "share_within_group": 36.948215125819}, {"gender": "Other", "city": "city_103", "total_measure": 55.2, "share_within_group": 33.36194079464275}, {"gender": "Male", "city": "city_103", "total_measure": 2851.08, "share_within_group": 25.70134718697138}, {"gender": "", "city": "city_103", "total_measure": 713.9200000000001, "share_within_group": 19.971415855108766}, {"gender": "", "city": "city_21", "total_measure": 610.896, "share_within_group": 17.08939105253043}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..9ea2c0bb8cf174eb856386570e0dcdd5e05793d3 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/generated_sql.sql @@ -0,0 +1,20 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_m9_f05afdd3be04aa2c +-- problem_id: v2p_m9_a8470a5bc880393d +-- realization_mode: agent +-- source_kind: agent +SELECT "gender", "city", + SUM(CAST("city_development_index" AS REAL)) AS "total_measure", + SUM(CAST("city_development_index" AS REAL)) * 100.0 / SUM(SUM(CAST("city_development_index" AS REAL))) OVER (PARTITION BY "gender") AS "share_within_group" +FROM "m9" +GROUP BY "gender", "city" +ORDER BY "share_within_group" DESC +LIMIT 15; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..53d02aba2aa2478fcd840e46c395e957a81f628c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT \"gender\", \"city\",\n SUM(CAST(\"city_development_index\" AS REAL)) AS \"total_measure\",\n SUM(CAST(\"city_development_index\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"city_development_index\" AS REAL))) OVER (PARTITION BY \"gender\") AS \"share_within_group\"\nFROM \"m9\"\nGROUP BY \"gender\", \"city\"\nORDER BY \"share_within_group\" DESC\nLIMIT 15;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"gender\\\", \\\"city\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"city_development_index\\\" AS REAL))) OVER (PARTITION BY \\\"gender\\\") AS \\\"share_within_group\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"gender\\\", \\\"city\\\"\\nORDER BY \\\"share_within_group\\\" DESC\\nLIMIT 15;\", \"columns\": [\"gender\", \"city\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"gender\": \"Female\", \"city\": \"city_103\", \"total_measure\": 386.40000000000003, \"share_within_group\": 36.948215125819}, {\"gender\": \"Other\", \"city\": \"city_103\", \"total_measure\": 55.2, \"share_within_group\": 33.36194079464275}, {\"gender\": \"Male\", \"city\": \"city_103\", \"total_measure\": 2851.08, \"share_within_group\": 25.70134718697138}, {\"gender\": \"\", \"city\": \"city_103\", \"total_measure\": 713.9200000000001, \"share_within_group\": 19.971415855108766}, {\"gender\": \"\", \"city\": \"city_21\", \"total_measure\": 610.896, \"share_within_group\": 17.08939105253043}, {\"gender\": \"Male\", \"city\": \"city_16\", \"total_measure\": 1042.8600000000001, \"share_within_group\": 9.400966275027349}, {\"gender\": \"Female\", \"city\": \"city_21\", \"total_measure\": 95.472, \"share_within_group\": 9.129192532329688}, {\"gender\": \"Other\", \"city\": \"city_16\", \"total_measure\": 14.56, \"share_within_group\": 8.799816267572435}, {\"gender\": \"Male\", \"city\": \"city_21\", \"total_measure\": 974.688, \"share_within_group\": 8.78642292989841}, {\"gender\": \"Female\", \"city\": \"city_16\", \"total_measure\": 87.36, \"share_within_group\": 8.353509506706905}, {\"gender\": \"Male\", \"city\": \"city_114\", \"total_measure\": 918.592, \"share_within_group\": 8.28073990037965}, {\"gender\": \"Other\", \"city\": \"city_114\", \"total_measure\": 12.037999999999998, \"share_within_group\": 7.275562378367924}, {\"gender\": \"\", \"city\": \"city_114\", \"total_measure\": 250.94599999999997, \"share_within_group\": 7.02003995290246}, {\"gender\": \"\", \"city\": \"city_16\", \"total_measure\": 250.25, \"share_within_group\": 7.000569836593693}, {\"gender\": \"Female\", \"city\": \"city_160\", \"total_measure\": 69.92, \"share_within_group\": 6.685867498957724}], \"row_count_returned\": 15, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 18.15}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..45aadea8a7a0164bf46ec97061dbd3a222d13cbc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:34:51.691231+00:00", + "ended_at": "2026-05-19T15:35:12.157547+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_f05afdd3be04aa2c", + "problem_id": "v2p_m9_a8470a5bc880393d", + "dataset_id": "m9", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=gender, measure_col=city_development_index.", + "bindings": { + "group_col": "gender", + "measure_col": "city_development_index", + "item_col": "city", + "top_k": 15, + "top_n": 5, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=2", + "sql_variant_index=2/2", + "binding_index=25" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 2, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_f05afdd3be04aa2c.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_f05afdd3be04aa2c", + "api_calls": 0, + "input_tokens": 14766, + "cached_input_tokens": 12032, + "output_tokens": 1203, + "total_tokens": 15969, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 20443.5, + "sql_execution_elapsed_ms_total": 18.15, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..579631c81d441ccaef60f3e40a94fad28055c6ab --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:35:12.137900+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 20443.5, "started_at": "2026-05-19T15:34:51.693599+00:00", "ended_at": "2026-05-19T15:35:12.137128+00:00", "prompt_metrics": {"chars": 9713, "bytes_utf8": 9713, "lines": 266, "estimated_tokens": null}, "response_metrics": {"chars": 618, "bytes_utf8": 618, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14766, "cached_input_tokens": 12032, "output_tokens": 1203, "reasoning_output_tokens": 1034}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT \\\"gender\\\", \\\"city\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"city_development_index\\\" AS REAL))) OVER (PARTITION BY \\\"gender\\\") AS \\\"share_within_group\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"gender\\\", \\\"city\\\"\\nORDER BY \\\"share_within_group\\\" DESC\\nLIMIT 15;\",\"notes\":\"Uses the planned Within-Group Share of Total template with group_col=\\\"gender\\\", item_col=\\\"city\\\", and casts TEXT \\\"city_development_index\\\" to REAL for SQLite-compatible summation.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..d8825c21fc0d55b961bde8a55400ae1ebbb51dbf --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_f05afdd3be04aa2c", + "api_calls": 0, + "input_tokens": 14766, + "cached_input_tokens": 12032, + "output_tokens": 1203, + "total_tokens": 15969, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 20443.5, + "sql_execution_elapsed_ms_total": 18.15, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f05afdd3be04aa2c/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..4b183a6d192f467ba73103144441b2c08373a0d4 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Window Partition Average to probe direction_consistency with semantic role filtered_stable_view. Focus on group_col=enrolled_university, measure_col=enrollee_id. +Result preview: [{"enrolled_university": "Part time course", "avg_measure": 17628.087646076794}, {"enrolled_university": "Full time course", "avg_measure": 17387.22917221187}, {"enrolled_university": "no_enrollment", "avg_measure": 16644.602229138018}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..0ddb78e68196e92c13c88e5d0d8b787065cc2366 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: direction_consistency +-- intended_facet_id: conditional_rate_shift +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_m4_window_partition_avg +-- query_record_id: v2q_m9_f0d28c375aa5e7d8 +-- problem_id: v2p_m9_c2e5712935a5387b +-- realization_mode: agent +-- source_kind: agent +SELECT DISTINCT "enrolled_university", + AVG(CAST("enrollee_id" AS REAL)) OVER (PARTITION BY "enrolled_university") AS avg_measure +FROM "m9" +WHERE "enrolled_university" IS NOT NULL + AND "enrolled_university" <> '' + AND "enrollee_id" IS NOT NULL + AND "enrollee_id" <> '' +ORDER BY avg_measure DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c0cf78d2b42854de40273915b66d6712ebe8a0f5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_window_partition_avg\nSELECT DISTINCT \"enrolled_university\",\n AVG(CAST(\"enrollee_id\" AS REAL)) OVER (PARTITION BY \"enrolled_university\") AS avg_measure\nFROM \"m9\"\nWHERE \"enrolled_university\" IS NOT NULL\n AND \"enrolled_university\" <> ''\n AND \"enrollee_id\" IS NOT NULL\n AND \"enrollee_id\" <> ''\nORDER BY avg_measure DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"enrolled_university\\\",\\n AVG(CAST(\\\"enrollee_id\\\" AS REAL)) OVER (PARTITION BY \\\"enrolled_university\\\") AS avg_measure\\nFROM \\\"m9\\\"\\nWHERE \\\"enrolled_university\\\" IS NOT NULL\\n AND \\\"enrolled_university\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\nORDER BY avg_measure DESC;\", \"columns\": [\"enrolled_university\", \"avg_measure\"], \"rows\": [{\"enrolled_university\": \"Part time course\", \"avg_measure\": 17628.087646076794}, {\"enrolled_university\": \"Full time course\", \"avg_measure\": 17387.22917221187}, {\"enrolled_university\": \"no_enrollment\", \"avg_measure\": 16644.602229138018}], \"row_count_returned\": 3, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 36.4}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..7d4b4f188d7d33b4d0ac8f6d6eb552290f90133b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:07:35.627212+00:00", + "ended_at": "2026-05-19T16:07:47.200564+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_f0d28c375aa5e7d8", + "problem_id": "v2p_m9_c2e5712935a5387b", + "dataset_id": "m9", + "template_id": "tpl_m4_window_partition_avg", + "template_name": "Window Partition Average", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "direction_consistency", + "intended_facet_id": "conditional_rate_shift", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Window Partition Average to probe direction_consistency with semantic role filtered_stable_view. Focus on group_col=enrolled_university, measure_col=enrollee_id.", + "bindings": { + "group_col": "enrolled_university", + "measure_col": "enrollee_id", + "top_k": 15, + "top_n": 7, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT DISTINCT {group_col},\n AVG({measure_col}) OVER (PARTITION BY {group_col}) AS avg_measure\nFROM {table}\nORDER BY avg_measure DESC;", + "notes": [ + "default_facets=conditional_rate_shift", + "template_selection_mode=rule", + "problem_index_within_template=4", + "sql_variant_index=2/2", + "binding_index=135" + ], + "template_selection_mode": "rule", + "selected_template_rank": 12, + "problem_index_within_template": 4, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_f0d28c375aa5e7d8.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_f0d28c375aa5e7d8", + "api_calls": 0, + "input_tokens": 14664, + "cached_input_tokens": 13696, + "output_tokens": 541, + "total_tokens": 15205, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11532.15, + "sql_execution_elapsed_ms_total": 36.4, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..87547f5a972c0d17bc9d993e68c24f8e8076d31d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:07:47.162179+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 11532.15, "started_at": "2026-05-19T16:07:35.629177+00:00", "ended_at": "2026-05-19T16:07:47.161358+00:00", "prompt_metrics": {"chars": 9399, "bytes_utf8": 9399, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 675, "bytes_utf8": 675, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14664, "cached_input_tokens": 13696, "output_tokens": 541, "reasoning_output_tokens": 365}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_window_partition_avg\\nSELECT DISTINCT \\\"enrolled_university\\\",\\n AVG(CAST(\\\"enrollee_id\\\" AS REAL)) OVER (PARTITION BY \\\"enrolled_university\\\") AS avg_measure\\nFROM \\\"m9\\\"\\nWHERE \\\"enrolled_university\\\" IS NOT NULL\\n AND \\\"enrolled_university\\\" <> ''\\n AND \\\"enrollee_id\\\" IS NOT NULL\\n AND \\\"enrollee_id\\\" <> ''\\nORDER BY avg_measure DESC;\",\"notes\":\"Used the required Window Partition Average template with group_col=\\\"enrolled_university\\\" and measure_col=\\\"enrollee_id\\\". Applied filtered_stable_view-style filtering to exclude null/empty group and measure values, and cast the text identifier to REAL so AVG is SQLite-compatible.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..d59153951deacda4c362ceaf61a20345c494c2e7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_f0d28c375aa5e7d8", + "api_calls": 0, + "input_tokens": 14664, + "cached_input_tokens": 13696, + "output_tokens": 541, + "total_tokens": 15205, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 11532.15, + "sql_execution_elapsed_ms_total": 36.4, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f0d28c375aa5e7d8/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..91cf17cecca8c412fcb489229f72ee6c5885a677 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=company_size, group_col_2=company_type. +Result preview: [{"company_size": "", "company_type": "", "row_count": 1368}, {"company_size": "50-99", "company_type": "Pvt Ltd", "row_count": 527}, {"company_size": "10000+", "company_type": "Pvt Ltd", "row_count": 464}, {"company_size": "100-500", "company_type": "Pvt Ltd", "row_count": 459}, {"company_size": "1000-4999", "company_type": "Pvt Ltd", "row_count": 254}] Results were truncated. \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..fe856fa3bfae1f2d0cc17b58e2cb806c0bea60d6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: slice_level_consistency +-- intended_facet_id: conditional_interaction_hotspots +-- variant_semantic_role: count_distribution +-- template_id: tpl_c2_filtered_group_count_2d +-- query_record_id: v2q_m9_f416f21fe5fff340 +-- problem_id: v2p_m9_5bcff65af4a112ae +-- realization_mode: agent +-- source_kind: agent +SELECT "company_size", "company_type", COUNT(*) AS "row_count" +FROM "m9" +WHERE CAST("enrollee_id" AS REAL) >= 25169.75 +GROUP BY "company_size", "company_type" +ORDER BY "row_count" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..2911412f7b1bac4783903adedd33fbc4985f139c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_c2_filtered_group_count_2d.\nSELECT \"company_size\", \"company_type\", COUNT(*) AS \"row_count\"\nFROM \"m9\"\nWHERE CAST(\"enrollee_id\" AS REAL) >= 25169.75\nGROUP BY \"company_size\", \"company_type\"\nORDER BY \"row_count\" DESC;", "result": "{\"query\": \"-- template_id: tpl_c2_filtered_group_count_2d.\\nSELECT \\\"company_size\\\", \\\"company_type\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m9\\\"\\nWHERE CAST(\\\"enrollee_id\\\" AS REAL) >= 25169.75\\nGROUP BY \\\"company_size\\\", \\\"company_type\\\"\\nORDER BY \\\"row_count\\\" DESC;\", \"columns\": [\"company_size\", \"company_type\", \"row_count\"], \"rows\": [{\"company_size\": \"\", \"company_type\": \"\", \"row_count\": 1368}, {\"company_size\": \"50-99\", \"company_type\": \"Pvt Ltd\", \"row_count\": 527}, {\"company_size\": \"10000+\", \"company_type\": \"Pvt Ltd\", \"row_count\": 464}, {\"company_size\": \"100-500\", \"company_type\": \"Pvt Ltd\", \"row_count\": 459}, {\"company_size\": \"1000-4999\", \"company_type\": \"Pvt Ltd\", \"row_count\": 254}, {\"company_size\": \"10/49\", \"company_type\": \"Pvt Ltd\", \"row_count\": 219}, {\"company_size\": \"<10\", \"company_type\": \"Pvt Ltd\", \"row_count\": 158}, {\"company_size\": \"500-999\", \"company_type\": \"Pvt Ltd\", \"row_count\": 142}, {\"company_size\": \"5000-9999\", \"company_type\": \"Pvt Ltd\", \"row_count\": 110}, {\"company_size\": \"\", \"company_type\": \"Pvt Ltd\", \"row_count\": 103}, {\"company_size\": \"50-99\", \"company_type\": \"Funded Startup\", \"row_count\": 95}, {\"company_size\": \"<10\", \"company_type\": \"Early Stage Startup\", \"row_count\": 78}, {\"company_size\": \"100-500\", \"company_type\": \"Funded Startup\", \"row_count\": 58}, {\"company_size\": \"10/49\", \"company_type\": \"Funded Startup\", \"row_count\": 50}, {\"company_size\": \"1000-4999\", \"company_type\": \"Public Sector\", \"row_count\": 47}, {\"company_size\": \"10/49\", \"company_type\": \"Early Stage Startup\", \"row_count\": 44}, {\"company_size\": \"100-500\", \"company_type\": \"Public Sector\", \"row_count\": 41}, {\"company_size\": \"50-99\", \"company_type\": \"\", \"row_count\": 41}, {\"company_size\": \"<10\", \"company_type\": \"Funded Startup\", \"row_count\": 39}, {\"company_size\": \"10000+\", \"company_type\": \"Public Sector\", \"row_count\": 38}, {\"company_size\": \"100-500\", \"company_type\": \"NGO\", \"row_count\": 36}, {\"company_size\": \"\", \"company_type\": \"Public Sector\", \"row_count\": 29}, {\"company_size\": \"100-500\", \"company_type\": \"\", \"row_count\": 28}, {\"company_size\": \"1000-4999\", \"company_type\": \"NGO\", \"row_count\": 28}, {\"company_size\": \"50-99\", \"company_type\": \"Public Sector\", \"row_count\": 26}, {\"company_size\": \"10/49\", \"company_type\": \"\", \"row_count\": 25}, {\"company_size\": \"50-99\", \"company_type\": \"Early Stage Startup\", \"row_count\": 24}, {\"company_size\": \"50-99\", \"company_type\": \"NGO\", \"row_count\": 23}, {\"company_size\": \"500-999\", \"company_type\": \"Public Sector\", \"row_count\": 21}, {\"company_size\": \"500-999\", \"company_type\": \"Funded Startup\", \"row_count\": 19}, {\"company_size\": \"5000-9999\", \"company_type\": \"Public Sector\", \"row_count\": 17}, {\"company_size\": \"10000+\", \"company_type\": \"\", \"row_count\": 16}, {\"company_size\": \"1000-4999\", \"company_type\": \"\", \"row_count\": 14}, {\"company_size\": \"500-999\", \"company_type\": \"\", \"row_count\": 14}, {\"company_size\": \"500-999\", \"company_type\": \"NGO\", \"row_count\": 13}, {\"company_size\": \"<10\", \"company_type\": \"\", \"row_count\": 13}, {\"company_size\": \"10000+\", \"company_type\": \"NGO\", \"row_count\": 12}, {\"company_size\": \"10/49\", \"company_type\": \"Public Sector\", \"row_count\": 10}, {\"company_size\": \"5000-9999\", \"company_type\": \"\", \"row_count\": 10}, {\"company_size\": \"<10\", \"company_type\": \"Other\", \"row_count\": 8}, {\"company_size\": \"<10\", \"company_type\": \"Public Sector\", \"row_count\": 8}, {\"company_size\": \"10/49\", \"company_type\": \"NGO\", \"row_count\": 7}, {\"company_size\": \"100-500\", \"company_type\": \"Early Stage Startup\", \"row_count\": 7}, {\"company_size\": \"<10\", \"company_type\": \"NGO\", \"row_count\": 7}, {\"company_size\": \"1000-4999\", \"company_type\": \"Other\", \"row_count\": 6}, {\"company_size\": \"5000-9999\", \"company_type\": \"NGO\", \"row_count\": 6}, {\"company_size\": \"\", \"company_type\": \"NGO\", \"row_count\": 5}, {\"company_size\": \"10/49\", \"company_type\": \"Other\", \"row_count\": 5}, {\"company_size\": \"10000+\", \"company_type\": \"Other\", \"row_count\": 5}, {\"company_size\": \"500-999\", \"company_type\": \"Other\", \"row_count\": 4}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 9.42}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..e2c8d992748428a29d4b53c60444fcedb6299756 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/run_manifest.json @@ -0,0 +1,93 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:43:47.655167+00:00", + "ended_at": "2026-05-19T15:44:03.604588+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_f416f21fe5fff340", + "problem_id": "v2p_m9_5bcff65af4a112ae", + "dataset_id": "m9", + "template_id": "tpl_c2_filtered_group_count_2d", + "template_name": "Filtered Two-Dimensional Group Count", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "slice_level_consistency", + "intended_facet_id": "conditional_interaction_hotspots", + "variant_semantic_role": "count_distribution", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Filtered Two-Dimensional Group Count to probe slice_level_consistency with semantic role count_distribution. Focus on group_col=company_size, group_col_2=company_type.", + "bindings": { + "group_col": "company_size", + "group_col_2": "company_type", + "predicate_col": "enrollee_id", + "predicate_op": ">=", + "predicate_value": 25169.75, + "top_k": 11, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "group_col_2", + "predicate_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {group_col_2}, COUNT(*) AS row_count\nFROM {table}\nWHERE {predicate_col} {predicate_op} {predicate_value}\nGROUP BY {group_col}, {group_col_2}\nORDER BY row_count DESC;", + "notes": [ + "default_facets=conditional_interaction_hotspots", + "template_selection_mode=rule", + "problem_index_within_template=9", + "sql_variant_index=1/1", + "binding_index=56" + ], + "template_selection_mode": "rule", + "selected_template_rank": 5, + "problem_index_within_template": 9, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_f416f21fe5fff340.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_f416f21fe5fff340", + "api_calls": 0, + "input_tokens": 14744, + "cached_input_tokens": 13696, + "output_tokens": 636, + "total_tokens": 15380, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15934.61, + "sql_execution_elapsed_ms_total": 9.42, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..f5696b87555f0bb5277974c536674ebacdf4c46e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:44:03.592893+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 15934.61, "started_at": "2026-05-19T15:43:47.657072+00:00", "ended_at": "2026-05-19T15:44:03.591715+00:00", "prompt_metrics": {"chars": 9615, "bytes_utf8": 9615, "lines": 268, "estimated_tokens": null}, "response_metrics": {"chars": 432, "bytes_utf8": 432, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14744, "cached_input_tokens": 13696, "output_tokens": 636, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_c2_filtered_group_count_2d.\\nSELECT \\\"company_size\\\", \\\"company_type\\\", COUNT(*) AS \\\"row_count\\\"\\nFROM \\\"m9\\\"\\nWHERE CAST(\\\"enrollee_id\\\" AS REAL) >= 25169.75\\nGROUP BY \\\"company_size\\\", \\\"company_type\\\"\\nORDER BY \\\"row_count\\\" DESC;\",\"notes\":\"Uses the required template shape with bound grouping columns. \\\"enrollee_id\\\" is cast to REAL for the numeric predicate because the schema stores it as TEXT.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..4f405fd138adbd7b4a392709cd0ac242cbfc607a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_f416f21fe5fff340", + "api_calls": 0, + "input_tokens": 14744, + "cached_input_tokens": 13696, + "output_tokens": 636, + "total_tokens": 15380, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 15934.61, + "sql_execution_elapsed_ms_total": 9.42, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f416f21fe5fff340/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..839bad1a0fce669498d03274b07a00be05b9786c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9266, "bytes_utf8": 9266, "lines": 262, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 360, "bytes_utf8": 360, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14652, "cached_input_tokens": 12032, "output_tokens": 246, "reasoning_output_tokens": 148}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..ccd92a0d9c138b432e3703bfb1b289aede6c51b6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_f5f63b1e437747fd", + "api_calls": 0, + "input_tokens": 14652, + "cached_input_tokens": 12032, + "output_tokens": 246, + "total_tokens": 14898, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8118.79, + "sql_execution_elapsed_ms_total": 6.65, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..96b93ed6113a2cb47eb54e1a1f777d56bbdcccb0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:04:22.415615+00:00", + "ended_at": "2026-05-19T16:04:30.534426+00:00", + "elapsed_ms": 8118.79, + "prompt_metrics": { + "chars": 9266, + "bytes_utf8": 9266, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 713, + "bytes_utf8": 713, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 360, + "bytes_utf8": 360, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14652, + "cached_input_tokens": 12032, + "output_tokens": 246, + "reasoning_output_tokens": 148 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..1b3ebb69da33bdc27e65aba67c5a31a4c6d2a05f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_mass_similarity with semantic role count_distribution. Focus on group_col=gender.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "gender", + "top_k": 11, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..241d2051beb55da3eeb6053f7cf717776aebc7dc --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fb-2a38-7923-997e-840159bca98a"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tail_low_support_group_count_v2\\nSELECT\\n \\\"gender\\\",\\n COUNT(*) AS support\\nFROM \\\"m9\\\"\\nGROUP BY \\\"gender\\\"\\nORDER BY support ASC, \\\"gender\\\"\\nLIMIT 11;\",\"notes\":\"Uses the provided Low-Support Group Count template with group_col bound to \\\"gender\\\" and top_k=11; includes blank gender values as their own group if present.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14652,"cached_input_tokens":12032,"output_tokens":246,"reasoning_output_tokens":148}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..3c29b2afc9f4b2d55214d215430808d13ac0c93f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tail_low_support_group_count_v2\nSELECT\n \"gender\",\n COUNT(*) AS support\nFROM \"m9\"\nGROUP BY \"gender\"\nORDER BY support ASC, \"gender\"\nLIMIT 11;","notes":"Uses the provided Low-Support Group Count template with group_col bound to \"gender\" and top_k=11; includes blank gender values as their own group if present."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f5f63b1e437747fd/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..c650c869ced47cb15596c9e5e3486f1da12f7a09 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=education_level, measure_col=city_development_index. +Result preview: [{"education_level": "Primary School", "training_hours": "15", "total_measure": 9.905000000000001, "share_within_group": 3.781559124800996}, {"education_level": "Primary School", "training_hours": "14", "total_measure": 7.992, "share_within_group": 3.051208533610253}, {"education_level": "Phd", "training_hours": "11", "total_measure": 9.813, "share_within_group": 2.684147038630601}, {"education_level": "Phd", "training_hours": "28", "total_measure": 9.071, "share_within_group": 2.4811879942339936}, {"education_level": "Primary School", "training_hours": "28", "total_measure": 6.146, "share_within_group": 2.346437393339416}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..51304643d59a0fd506677707f572d85d3194657f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/generated_sql.sql @@ -0,0 +1,25 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: focused_target_view +-- template_id: tpl_tpcds_within_group_share +-- query_record_id: v2q_m9_f6d95d112f27cb53 +-- problem_id: v2p_m9_c3e57052ebe95741 +-- realization_mode: agent +-- source_kind: agent +SELECT + "education_level", + "training_hours", + SUM(CAST("city_development_index" AS REAL)) AS total_measure, + SUM(CAST("city_development_index" AS REAL)) * 100.0 / SUM(SUM(CAST("city_development_index" AS REAL))) OVER (PARTITION BY "education_level") AS share_within_group +FROM "m9" +WHERE "education_level" <> '' + AND "training_hours" <> '' + AND "city_development_index" <> '' +GROUP BY "education_level", "training_hours" +ORDER BY share_within_group DESC +LIMIT 18; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..61fbdd607cafc9abcdbcf1131d7254b3c6dbacea --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"education_level\",\n \"training_hours\",\n SUM(CAST(\"city_development_index\" AS REAL)) AS total_measure,\n SUM(CAST(\"city_development_index\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"city_development_index\" AS REAL))) OVER (PARTITION BY \"education_level\") AS share_within_group\nFROM \"m9\"\nWHERE \"education_level\" <> ''\n AND \"training_hours\" <> ''\n AND \"city_development_index\" <> ''\nGROUP BY \"education_level\", \"training_hours\"\nORDER BY share_within_group DESC\nLIMIT 18;", "result": "{\"query\": \"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"education_level\\\",\\n \\\"training_hours\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"city_development_index\\\" AS REAL))) OVER (PARTITION BY \\\"education_level\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nWHERE \\\"education_level\\\" <> ''\\n AND \\\"training_hours\\\" <> ''\\n AND \\\"city_development_index\\\" <> ''\\nGROUP BY \\\"education_level\\\", \\\"training_hours\\\"\\nORDER BY share_within_group DESC\\nLIMIT 18;\", \"columns\": [\"education_level\", \"training_hours\", \"total_measure\", \"share_within_group\"], \"rows\": [{\"education_level\": \"Primary School\", \"training_hours\": \"15\", \"total_measure\": 9.905000000000001, \"share_within_group\": 3.781559124800996}, {\"education_level\": \"Primary School\", \"training_hours\": \"14\", \"total_measure\": 7.992, \"share_within_group\": 3.051208533610253}, {\"education_level\": \"Phd\", \"training_hours\": \"11\", \"total_measure\": 9.813, \"share_within_group\": 2.684147038630601}, {\"education_level\": \"Phd\", \"training_hours\": \"28\", \"total_measure\": 9.071, \"share_within_group\": 2.4811879942339936}, {\"education_level\": \"Primary School\", \"training_hours\": \"28\", \"total_measure\": 6.146, \"share_within_group\": 2.346437393339416}, {\"education_level\": \"Primary School\", \"training_hours\": \"17\", \"total_measure\": 6.042, \"share_within_group\": 2.3067319769861294}, {\"education_level\": \"Phd\", \"training_hours\": \"13\", \"total_measure\": 8.326, \"share_within_group\": 2.2774083607090985}, {\"education_level\": \"Primary School\", \"training_hours\": \"22\", \"total_measure\": 5.91, \"share_within_group\": 2.2563366408454195}, {\"education_level\": \"Primary School\", \"training_hours\": \"7\", \"total_measure\": 5.864, \"share_within_group\": 2.2387746297660813}, {\"education_level\": \"Primary School\", \"training_hours\": \"9\", \"total_measure\": 5.822, \"share_within_group\": 2.2227397500849464}, {\"education_level\": \"Primary School\", \"training_hours\": \"34\", \"total_measure\": 5.755, \"share_within_group\": 2.1971602991650405}, {\"education_level\": \"High School\", \"training_hours\": \"12\", \"total_measure\": 35.265, \"share_within_group\": 2.096666024557123}, {\"education_level\": \"Primary School\", \"training_hours\": \"11\", \"total_measure\": 5.289, \"share_within_group\": 2.0192494912743526}, {\"education_level\": \"Phd\", \"training_hours\": \"18\", \"total_measure\": 7.263, \"share_within_group\": 1.986646279585657}, {\"education_level\": \"Phd\", \"training_hours\": \"10\", \"total_measure\": 7.184, \"share_within_group\": 1.9650374325407354}, {\"education_level\": \"Primary School\", \"training_hours\": \"48\", \"total_measure\": 4.958, \"share_within_group\": 1.8928793680730271}, {\"education_level\": \"Phd\", \"training_hours\": \"23\", \"total_measure\": 6.821, \"share_within_group\": 1.865746148017867}, {\"education_level\": \"Primary School\", \"training_hours\": \"12\", \"total_measure\": 4.792, \"share_within_group\": 1.829503415047589}], \"row_count_returned\": 18, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 34.52}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..f419bc44f19910f83ea516042cee579ad0daf44c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/run_manifest.json @@ -0,0 +1,91 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:36:24.919349+00:00", + "ended_at": "2026-05-19T15:36:41.628848+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_f6d95d112f27cb53", + "problem_id": "v2p_m9_c3e57052ebe95741", + "dataset_id": "m9", + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "focused_target_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=education_level, measure_col=city_development_index.", + "bindings": { + "group_col": "education_level", + "measure_col": "city_development_index", + "item_col": "training_hours", + "top_k": 18, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "item_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=2/2", + "binding_index=28" + ], + "template_selection_mode": "rule", + "selected_template_rank": 3, + "problem_index_within_template": 5, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_f6d95d112f27cb53.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_f6d95d112f27cb53", + "api_calls": 0, + "input_tokens": 14768, + "cached_input_tokens": 12032, + "output_tokens": 740, + "total_tokens": 15508, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16669.34, + "sql_execution_elapsed_ms_total": 34.52, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c7446b273d4a1067480c875bfc190eebbb64adf9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:36:41.592140+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 16669.34, "started_at": "2026-05-19T15:36:24.921607+00:00", "ended_at": "2026-05-19T15:36:41.590978+00:00", "prompt_metrics": {"chars": 9736, "bytes_utf8": 9736, "lines": 266, "estimated_tokens": null}, "response_metrics": {"chars": 852, "bytes_utf8": 852, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14768, "cached_input_tokens": 12032, "output_tokens": 740, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"education_level\\\",\\n \\\"training_hours\\\",\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) AS total_measure,\\n SUM(CAST(\\\"city_development_index\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"city_development_index\\\" AS REAL))) OVER (PARTITION BY \\\"education_level\\\") AS share_within_group\\nFROM \\\"m9\\\"\\nWHERE \\\"education_level\\\" <> ''\\n AND \\\"training_hours\\\" <> ''\\n AND \\\"city_development_index\\\" <> ''\\nGROUP BY \\\"education_level\\\", \\\"training_hours\\\"\\nORDER BY share_within_group DESC\\nLIMIT 18;\",\"notes\":\"Uses the required Within-Group Share of Total template with group_col=education_level, item_col=training_hours, and measure_col=city_development_index. CAST to REAL is needed because city_development_index is stored as TEXT, and blank values are excluded to avoid distorting sums.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..2941f0968b238912b9d02a78072f3d62b6605d33 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_f6d95d112f27cb53", + "api_calls": 0, + "input_tokens": 14768, + "cached_input_tokens": 12032, + "output_tokens": 740, + "total_tokens": 15508, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 16669.34, + "sql_execution_elapsed_ms_total": 34.52, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f6d95d112f27cb53/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..649e09f0e9bdf24601630a4cba83fa171fae3203 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"city_development_index": "0.92", "total_rows": 5200, "missing_rows": 0, "missing_rate": 0.0}, {"city_development_index": "0.624", "total_rows": 2702, "missing_rows": 0, "missing_rate": 0.0}, {"city_development_index": "0.91", "total_rows": 1533, "missing_rows": 0, "missing_rate": 0.0}, {"city_development_index": "0.9259999999999999", "total_rows": 1336, "missing_rows": 0, "missing_rate": 0.0}, {"city_development_index": "0.698", "total_rows": 683, "missing_rows": 0, "missing_rate": 0.0}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..5283c23dbf6c84c2f03bb057d2a4f973276691ab --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/generated_sql.sql @@ -0,0 +1,21 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: missingness_structure +-- canonical_subitem_id: co_missingness_pattern_consistency +-- intended_facet_id: missing_rate_by_subgroup +-- variant_semantic_role: missing_rate_by_subgroup +-- template_id: tpl_missing_rate_by_subgroup +-- query_record_id: v2q_m9_f703aea01bbab1a4 +-- problem_id: v2p_m9_e3e2476298b71947 +-- realization_mode: deterministic +-- source_kind: deterministic +SELECT + "city_development_index", + COUNT(*) AS total_rows, + SUM(CASE WHEN "company_type" IS NULL THEN 1 ELSE 0 END) AS missing_rows, + AVG(CASE WHEN "company_type" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate +FROM "m9" +GROUP BY "city_development_index" +ORDER BY missing_rate DESC, total_rows DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..3882ab0ae6df6c6fc9306fed2fadad93e0272d16 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: missingness_structure\n-- canonical_subitem_id: co_missingness_pattern_consistency\n-- intended_facet_id: missing_rate_by_subgroup\n-- variant_semantic_role: missing_rate_by_subgroup\n-- template_id: tpl_missing_rate_by_subgroup\n-- query_record_id: v2q_m9_f703aea01bbab1a4\n-- problem_id: v2p_m9_e3e2476298b71947\n-- realization_mode: deterministic\n-- source_kind: deterministic\nSELECT\n \"city_development_index\",\n COUNT(*) AS total_rows,\n SUM(CASE WHEN \"company_type\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN \"company_type\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM \"m9\"\nGROUP BY \"city_development_index\"\nORDER BY missing_rate DESC, total_rows DESC;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: missingness_structure\\n-- canonical_subitem_id: co_missingness_pattern_consistency\\n-- intended_facet_id: missing_rate_by_subgroup\\n-- variant_semantic_role: missing_rate_by_subgroup\\n-- template_id: tpl_missing_rate_by_subgroup\\n-- query_record_id: v2q_m9_f703aea01bbab1a4\\n-- problem_id: v2p_m9_e3e2476298b71947\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nSELECT\\n \\\"city_development_index\\\",\\n COUNT(*) AS total_rows,\\n SUM(CASE WHEN \\\"company_type\\\" IS NULL THEN 1 ELSE 0 END) AS missing_rows,\\n AVG(CASE WHEN \\\"company_type\\\" IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\\nFROM \\\"m9\\\"\\nGROUP BY \\\"city_development_index\\\"\\nORDER BY missing_rate DESC, total_rows DESC;\", \"columns\": [\"city_development_index\", \"total_rows\", \"missing_rows\", \"missing_rate\"], \"rows\": [{\"city_development_index\": \"0.92\", \"total_rows\": 5200, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.624\", \"total_rows\": 2702, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.91\", \"total_rows\": 1533, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.9259999999999999\", \"total_rows\": 1336, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.698\", \"total_rows\": 683, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.897\", \"total_rows\": 586, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.9390000000000001\", \"total_rows\": 497, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.855\", \"total_rows\": 431, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.804\", \"total_rows\": 304, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.924\", \"total_rows\": 301, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.754\", \"total_rows\": 280, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.887\", \"total_rows\": 275, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.884\", \"total_rows\": 266, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.55\", \"total_rows\": 247, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.9129999999999999\", \"total_rows\": 197, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.899\", \"total_rows\": 182, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.802\", \"total_rows\": 175, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.925\", \"total_rows\": 171, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.893\", \"total_rows\": 160, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.878\", \"total_rows\": 151, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.743\", \"total_rows\": 146, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.9229999999999999\", \"total_rows\": 143, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.8959999999999999\", \"total_rows\": 140, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.8270000000000001\", \"total_rows\": 137, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.579\", \"total_rows\": 135, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.762\", \"total_rows\": 128, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.767\", \"total_rows\": 128, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.836\", \"total_rows\": 120, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.682\", \"total_rows\": 119, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.6659999999999999\", \"total_rows\": 114, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.89\", \"total_rows\": 113, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.866\", \"total_rows\": 103, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.6890000000000001\", \"total_rows\": 102, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.843\", \"total_rows\": 94, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.915\", \"total_rows\": 94, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.794\", \"total_rows\": 93, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.527\", \"total_rows\": 92, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.895\", \"total_rows\": 86, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.7759999999999999\", \"total_rows\": 82, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.903\", \"total_rows\": 82, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.738\", \"total_rows\": 79, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.9490000000000001\", \"total_rows\": 79, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.5579999999999999\", \"total_rows\": 75, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.74\", \"total_rows\": 67, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.555\", \"total_rows\": 63, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.789\", \"total_rows\": 54, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.727\", \"total_rows\": 53, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.7659999999999999\", \"total_rows\": 49, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.848\", \"total_rows\": 47, \"missing_rows\": 0, \"missing_rate\": 0.0}, {\"city_development_index\": \"0.691\", \"total_rows\": 45, \"missing_rows\": 0, \"missing_rate\": 0.0}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 9.86}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..13fc3c8c4ab6beac0245565a7ec3995353a21c1f --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/run_manifest.json @@ -0,0 +1,59 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.025640+00:00", + "ended_at": "2026-05-19T16:08:56.036305+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_f703aea01bbab1a4", + "problem_id": "v2p_m9_e3e2476298b71947", + "dataset_id": "m9", + "template_id": "tpl_missing_rate_by_subgroup", + "template_name": "Missing Rate by Subgroup", + "family_id": "missingness_structure", + "canonical_subitem_id": "co_missingness_pattern_consistency", + "intended_facet_id": "missing_rate_by_subgroup", + "variant_semantic_role": "missing_rate_by_subgroup", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": false, + "question": "Use template Missing Rate by Subgroup to probe co_missingness_pattern_consistency with semantic role missing_rate_by_subgroup. Focus on group_col=city_development_index, missing_col=company_type.", + "bindings": { + "missing_col": "company_type", + "group_col": "city_development_index" + }, + "binding_roles": [ + "missing_col", + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS total_rows,\n SUM(CASE WHEN {missing_col} IS NULL THEN 1 ELSE 0 END) AS missing_rows,\n AVG(CASE WHEN {missing_col} IS NULL THEN 1.0 ELSE 0.0 END) AS missing_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY missing_rate DESC, total_rows DESC;", + "notes": [ + "default_facets=missing_rate_by_subgroup,missing_target_interaction", + "template_selection_mode=deterministic", + "problem_index_within_template=10", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 10, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_f703aea01bbab1a4.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f703aea01bbab1a4/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/conversation.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/conversation.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..a8b77ebfca65b186abaaf188dde0eaa1dc3c49ed --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/conversation.jsonl @@ -0,0 +1,2 @@ +{"attempt": 1, "phase": "sql_generation", "role": "user", "content_path": "cli/sql_prompt_attempt_1.txt", "metrics": {"chars": 9736, "bytes_utf8": 9736, "lines": 266, "estimated_tokens": null}} +{"attempt": 1, "phase": "sql_generation", "role": "assistant", "content_path": "cli/sql_response_attempt_1.txt", "raw_content_path": "cli/sql_response_attempt_1.raw.txt", "stderr_path": "cli/sql_stderr_attempt_1.txt", "metrics": {"chars": 940, "bytes_utf8": 940, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14771, "cached_input_tokens": 12032, "output_tokens": 777, "reasoning_output_tokens": 516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/session_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/session_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..6a13e5be4f19339d3fb49a547dff48d0fd04707b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/session_summary.json @@ -0,0 +1,25 @@ +{ + "engine": "v2-cli:codex", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "ai_cli_calls": 1, + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_f7eb7b64880fb985", + "api_calls": 0, + "input_tokens": 14771, + "cached_input_tokens": 12032, + "output_tokens": 777, + "total_tokens": 15548, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 14232.09, + "sql_execution_elapsed_ms_total": 45.56, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..1f5f19ad989ca7ab33e455d34967ca85ea4982c1 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_attempt_1.metadata.json @@ -0,0 +1,45 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T15:35:27.456089+00:00", + "ended_at": "2026-05-19T15:35:41.688220+00:00", + "elapsed_ms": 14232.09, + "prompt_metrics": { + "chars": 9736, + "bytes_utf8": 9736, + "lines": 266, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 1368, + "bytes_utf8": 1368, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 940, + "bytes_utf8": 940, + "lines": 1, + "estimated_tokens": null + }, + "usage": { + "input_tokens": 14771, + "cached_input_tokens": 12032, + "output_tokens": 777, + "reasoning_output_tokens": 516 + } + }, + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..5693cbbb49ab65a744c722d5bcd35c44f54b2895 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,266 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tpcds_within_group_share", + "template_name": "Within-Group Share of Total", + "primary_family": "conditional_dependency_structure", + "portability": "partial", + "sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;", + "required_roles": [ + "group_col", + "item_col", + "measure_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Within-Group Share of Total to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=relevent_experience, measure_col=training_hours.", + "planned_template_id": "tpl_tpcds_within_group_share", + "bindings": { + "group_col": "relevent_experience", + "measure_col": "training_hours", + "item_col": "city_development_index", + "top_k": 16, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 70.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col}, {item_col},\n SUM({measure_col}) AS total_measure,\n SUM({measure_col}) * 100.0 / SUM(SUM({measure_col})) OVER (PARTITION BY {group_col}) AS share_within_group\nFROM {table}\nGROUP BY {group_col}, {item_col}\nORDER BY share_within_group DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..cffe6dfc96871b5979fde825bbc4844e6306d811 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40e0-b0e7-7150-b571-70361f7dcabc"} +{"type":"turn.started"} +{"type":"item.completed","item":{"id":"item_0","type":"agent_message","text":"{\"sql\":\"-- template_id: tpl_tpcds_within_group_share\\nSELECT\\n \\\"relevent_experience\\\",\\n \\\"city_development_index\\\",\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) AS \\\"total_measure\\\",\\n SUM(CAST(\\\"training_hours\\\" AS REAL)) * 100.0 / SUM(SUM(CAST(\\\"training_hours\\\" AS REAL))) OVER (PARTITION BY \\\"relevent_experience\\\") AS \\\"share_within_group\\\"\\nFROM \\\"m9\\\"\\nWHERE \\\"relevent_experience\\\" IS NOT NULL\\n AND \\\"relevent_experience\\\" <> ''\\n AND \\\"city_development_index\\\" IS NOT NULL\\n AND \\\"city_development_index\\\" <> ''\\n AND \\\"training_hours\\\" IS NOT NULL\\n AND \\\"training_hours\\\" <> ''\\nGROUP BY \\\"relevent_experience\\\", \\\"city_development_index\\\"\\nORDER BY \\\"share_within_group\\\" DESC;\",\"notes\":\"Uses the planned template with group_col=\\\"relevent_experience\\\", item_col=\\\"city_development_index\\\", and measure_col=\\\"training_hours\\\". CAST to REAL is applied because \\\"training_hours\\\" is stored as TEXT in the schema snapshot.\"}"}} +{"type":"turn.completed","usage":{"input_tokens":14771,"cached_input_tokens":12032,"output_tokens":777,"reasoning_output_tokens":516}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..8054947fd240a5a48045fee1d7cfaac65a6d2d3e --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_response_attempt_1.txt @@ -0,0 +1 @@ +{"sql":"-- template_id: tpl_tpcds_within_group_share\nSELECT\n \"relevent_experience\",\n \"city_development_index\",\n SUM(CAST(\"training_hours\" AS REAL)) AS \"total_measure\",\n SUM(CAST(\"training_hours\" AS REAL)) * 100.0 / SUM(SUM(CAST(\"training_hours\" AS REAL))) OVER (PARTITION BY \"relevent_experience\") AS \"share_within_group\"\nFROM \"m9\"\nWHERE \"relevent_experience\" IS NOT NULL\n AND \"relevent_experience\" <> ''\n AND \"city_development_index\" IS NOT NULL\n AND \"city_development_index\" <> ''\n AND \"training_hours\" IS NOT NULL\n AND \"training_hours\" <> ''\nGROUP BY \"relevent_experience\", \"city_development_index\"\nORDER BY \"share_within_group\" DESC;","notes":"Uses the planned template with group_col=\"relevent_experience\", item_col=\"city_development_index\", and measure_col=\"training_hours\". CAST to REAL is applied because \"training_hours\" is stored as TEXT in the schema snapshot."} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f7eb7b64880fb985/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..6d1d8d75af982b36f9c9ac97909f665316a3f430 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=education_level, condition_col=major_discipline. +Result preview: [{"education_level": "Phd", "condition_rate": 0.9057971014492754}, {"education_level": "Masters", "condition_rate": 0.8880990598486586}, {"education_level": "Graduate", "condition_rate": 0.8832557337471978}, {"education_level": "Primary School", "condition_rate": 0.0}, {"education_level": "High School", "condition_rate": 0.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..f3b11fa30ccf7fb2137b2a4753914628c352d72c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/generated_sql.sql @@ -0,0 +1,18 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: conditional_dependency_structure +-- canonical_subitem_id: dependency_strength_similarity +-- intended_facet_id: pairwise_conditional_dependency +-- variant_semantic_role: within_group_proportion +-- template_id: tpl_m4_group_condition_rate +-- query_record_id: v2q_m9_f8506904d051199f +-- problem_id: v2p_m9_ebcf5390faf97291 +-- realization_mode: agent +-- source_kind: agent +SELECT "education_level", + AVG(CASE WHEN "major_discipline" = 'STEM' THEN 1 ELSE 0 END) AS "condition_rate" +FROM "m9" +GROUP BY "education_level" +ORDER BY "condition_rate" DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c46ec4da64fce1241b6c1207085879193ece6844 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_m4_group_condition_rate\nSELECT \"education_level\",\n AVG(CASE WHEN \"major_discipline\" = 'STEM' THEN 1 ELSE 0 END) AS \"condition_rate\"\nFROM \"m9\"\nGROUP BY \"education_level\"\nORDER BY \"condition_rate\" DESC;", "result": "{\"query\": \"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"education_level\\\",\\n AVG(CASE WHEN \\\"major_discipline\\\" = 'STEM' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"education_level\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\", \"columns\": [\"education_level\", \"condition_rate\"], \"rows\": [{\"education_level\": \"Phd\", \"condition_rate\": 0.9057971014492754}, {\"education_level\": \"Masters\", \"condition_rate\": 0.8880990598486586}, {\"education_level\": \"Graduate\", \"condition_rate\": 0.8832557337471978}, {\"education_level\": \"Primary School\", \"condition_rate\": 0.0}, {\"education_level\": \"High School\", \"condition_rate\": 0.0}, {\"education_level\": \"\", \"condition_rate\": 0.0}], \"row_count_returned\": 6, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 9.06}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..7e6e9a74ce3b28c2dad4cec0ad2a22b8786cd4b8 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/run_manifest.json @@ -0,0 +1,92 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:00:41.407330+00:00", + "ended_at": "2026-05-19T16:00:50.240778+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_f8506904d051199f", + "problem_id": "v2p_m9_ebcf5390faf97291", + "dataset_id": "m9", + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "family_id": "conditional_dependency_structure", + "canonical_subitem_id": "dependency_strength_similarity", + "intended_facet_id": "pairwise_conditional_dependency", + "variant_semantic_role": "within_group_proportion", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role within_group_proportion. Focus on group_col=education_level, condition_col=major_discipline.", + "bindings": { + "group_col": "education_level", + "condition_col": "major_discipline", + "condition_value": "STEM", + "positive_value": "STEM", + "negative_value": "", + "top_k": 10, + "top_n": 3, + "num_tiles": 10, + "percentile_value": 0.95, + "z_threshold": 2.0, + "fraction_threshold": 0.1, + "baseline_multiplier": 1.5, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 5, + "measure_threshold": 0.92, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "condition_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "notes": [ + "default_facets=pairwise_conditional_dependency", + "template_selection_mode=rule", + "problem_index_within_template=5", + "sql_variant_index=1/2", + "binding_index=100" + ], + "template_selection_mode": "rule", + "selected_template_rank": 9, + "problem_index_within_template": 5, + "sql_variant_index": 1, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_f8506904d051199f.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_f8506904d051199f", + "api_calls": 0, + "input_tokens": 14710, + "cached_input_tokens": 12032, + "output_tokens": 343, + "total_tokens": 15053, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8818.31, + "sql_execution_elapsed_ms_total": 9.06, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..468a747971bd3cae39d0fddfff331e6fe6ab36d9 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T16:00:50.230223+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 8818.31, "started_at": "2026-05-19T16:00:41.411098+00:00", "ended_at": "2026-05-19T16:00:50.229446+00:00", "prompt_metrics": {"chars": 9566, "bytes_utf8": 9566, "lines": 267, "estimated_tokens": null}, "response_metrics": {"chars": 365, "bytes_utf8": 365, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14710, "cached_input_tokens": 12032, "output_tokens": 343, "reasoning_output_tokens": 241}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_m4_group_condition_rate\\nSELECT \\\"education_level\\\",\\n AVG(CASE WHEN \\\"major_discipline\\\" = 'STEM' THEN 1 ELSE 0 END) AS \\\"condition_rate\\\"\\nFROM \\\"m9\\\"\\nGROUP BY \\\"education_level\\\"\\nORDER BY \\\"condition_rate\\\" DESC;\",\"notes\":\"Computes the within-group proportion of rows with major_discipline = 'STEM' for each education_level.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..3175f3b3dcec86f21b42a1c73c445d9ea06c3b33 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_f8506904d051199f", + "api_calls": 0, + "input_tokens": 14710, + "cached_input_tokens": 12032, + "output_tokens": 343, + "total_tokens": 15053, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 8818.31, + "sql_execution_elapsed_ms_total": 9.06, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_f8506904d051199f/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..1c4f0420691a42bb5f8226d8fd778647bde3d702 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:04:15.319476+00:00", + "ended_at": "2026-05-19T16:04:18.343513+00:00", + "elapsed_ms": 3024.01, + "returncode": 1, + "prompt_metrics": { + "chars": 9304, + "bytes_utf8": 9304, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..ea9986640f482c098f4e0fdca3e5986eea7e0049 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:04:19.345915+00:00", + "ended_at": "2026-05-19T16:04:22.411559+00:00", + "elapsed_ms": 3065.6, + "returncode": 1, + "prompt_metrics": { + "chars": 9304, + "bytes_utf8": 9304, + "lines": 262, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..1df2c1bba8d407a72ed5762f9dbbf4480b84aaaa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role count_distribution. Focus on group_col=city_development_index.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "city_development_index", + "top_k": 15, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..1df2c1bba8d407a72ed5762f9dbbf4480b84aaaa --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,262 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_tail_low_support_group_count_v2", + "template_name": "Low-Support Group Count", + "primary_family": "tail_rarity_structure", + "portability": "yes", + "sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};", + "required_roles": [ + "group_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Low-Support Group Count to probe tail_set_consistency with semantic role count_distribution. Focus on group_col=city_development_index.", + "planned_template_id": "tpl_tail_low_support_group_count_v2", + "bindings": { + "group_col": "city_development_index", + "top_k": 15, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 25169.75, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT\n {group_col},\n COUNT(*) AS support\nFROM {table}\nGROUP BY {group_col}\nORDER BY support ASC, {group_col}\nLIMIT {top_k};" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..b67cbbff2bfc24d1a67e3ad419032116b2ad6317 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fb-0e65-7732-9450-fa6a7e6bfa08"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_response_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_response_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..ac7b24b4b38a9de8ef269bcf324388b492fb0c65 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_response_attempt_1.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fb-0e65-7732-9450-fa6a7e6bfa08"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_response_attempt_2.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_response_attempt_2.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..969ade8fa0bb8fb0b5490950217b0271c65c17c0 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_response_attempt_2.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fb-1e12-7050-8abd-25170a4decf2"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_response_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_response_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..0b4d31f9ef45034c9bf62b257570d044dcf8d87c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_response_attempt_2.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40fb-1e12-7050-8abd-25170a4decf2"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. Check your plan and billing details."} +{"type":"turn.failed","error":{"message":"Quota exceeded. Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fa2616e910ab28ff/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..0f739c6f156602dbd77a3717b7d9a5543270fb75 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "STEM", "support": 14492, "support_share": 0.7564463931516859, "cumulative_support": 14492}, {"value_label": "", "support": 2813, "support_share": 0.1468316108153252, "cumulative_support": 17305}, {"value_label": "Humanities", "support": 669, "support_share": 0.034920137801440654, "cumulative_support": 17974}, {"value_label": "Other", "support": 381, "support_share": 0.019887253366739743, "cumulative_support": 18355}, {"value_label": "Business Degree", "support": 327, "support_share": 0.017068587535233323, "cumulative_support": 18682}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..acae0dcf25132a1113cb5b976a13fefb13f8801a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/generated_sql.sql @@ -0,0 +1,28 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: value_imbalance_profile +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_cardinality_distinct_share_profile +-- query_record_id: v2q_m9_fb7710d4a5cd450f +-- problem_id: v2p_m9_e25a3a8587d72586 +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "major_discipline" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "major_discipline" +), ranked AS ( + SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support + FROM grouped +) +SELECT * +FROM ranked +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..44e77a8559b3b97b507793ec41076cf6ef1d7ca6 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: value_imbalance_profile\n-- variant_semantic_role: ranked_signal_view\n-- template_id: tpl_cardinality_distinct_share_profile\n-- query_record_id: v2q_m9_fb7710d4a5cd450f\n-- problem_id: v2p_m9_e25a3a8587d72586\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"major_discipline\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"major_discipline\"\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: value_imbalance_profile\\n-- variant_semantic_role: ranked_signal_view\\n-- template_id: tpl_cardinality_distinct_share_profile\\n-- query_record_id: v2q_m9_fb7710d4a5cd450f\\n-- problem_id: v2p_m9_e25a3a8587d72586\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"major_discipline\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"major_discipline\\\"\\n), ranked AS (\\n SELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\\n FROM grouped\\n)\\nSELECT *\\nFROM ranked\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"cumulative_support\"], \"rows\": [{\"value_label\": \"STEM\", \"support\": 14492, \"support_share\": 0.7564463931516859, \"cumulative_support\": 14492}, {\"value_label\": \"\", \"support\": 2813, \"support_share\": 0.1468316108153252, \"cumulative_support\": 17305}, {\"value_label\": \"Humanities\", \"support\": 669, \"support_share\": 0.034920137801440654, \"cumulative_support\": 17974}, {\"value_label\": \"Other\", \"support\": 381, \"support_share\": 0.019887253366739743, \"cumulative_support\": 18355}, {\"value_label\": \"Business Degree\", \"support\": 327, \"support_share\": 0.017068587535233323, \"cumulative_support\": 18682}, {\"value_label\": \"Arts\", \"support\": 253, \"support_share\": 0.013205971395761561, \"cumulative_support\": 18935}, {\"value_label\": \"No Major\", \"support\": 223, \"support_share\": 0.01164004593381355, \"cumulative_support\": 19158}], \"row_count_returned\": 7, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 5.41}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..cb11db1fc2c3441c8e29f1ea785388956ca4c710 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.212089+00:00", + "ended_at": "2026-05-19T16:08:56.218261+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_fb7710d4a5cd450f", + "problem_id": "v2p_m9_e25a3a8587d72586", + "dataset_id": "m9", + "template_id": "tpl_cardinality_distinct_share_profile", + "template_name": "Cardinality Distinct Share Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "value_imbalance_profile", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Distinct Share Profile to probe support_rank_profile_consistency with semantic role ranked_signal_view. Focus on group_col=major_discipline.", + "bindings": { + "group_col": "major_discipline" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=6", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 6, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_fb7710d4a5cd450f.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fb7710d4a5cd450f/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..453b8ab26354f3500c8db987e30f2700c9e4ecd5 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/final_answer.txt @@ -0,0 +1 @@ +{"row_count": null, "preview_rows": [{"value_label": "28", "support": 329, "support_share": 0.017172982566029858, "cumulative_support": 329}, {"value_label": "12", "support": 292, "support_share": 0.015241674496293977, "cumulative_support": 621}, {"value_label": "18", "support": 291, "support_share": 0.015189476980895709, "cumulative_support": 912}, {"value_label": "22", "support": 282, "support_share": 0.014719699342311305, "cumulative_support": 1194}, {"value_label": "50", "support": 279, "support_share": 0.014563106796116505, "cumulative_support": 1473}]} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..e5dfd1bd6f5f338769ee784510bafd1fd4298911 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/generated_sql.sql @@ -0,0 +1,28 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: cardinality_structure +-- canonical_subitem_id: support_rank_profile_consistency +-- intended_facet_id: support_concentration +-- variant_semantic_role: ranked_signal_view +-- template_id: tpl_cardinality_distinct_share_profile +-- query_record_id: v2q_m9_fe78892a2f55fc1c +-- problem_id: v2p_m9_69466bf5e57f70b2 +-- realization_mode: deterministic +-- source_kind: deterministic +WITH grouped AS ( + SELECT "training_hours" AS value_label, COUNT(*) AS support + FROM "m9" + GROUP BY "training_hours" +), ranked AS ( + SELECT + value_label, + support, + CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share, + SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support + FROM grouped +) +SELECT * +FROM ranked +ORDER BY support DESC, value_label; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..9c8be988094b02e5696ca3c0bb4f6c8840b8361b --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/query_results.jsonl @@ -0,0 +1 @@ +{"node_name": "v2_template", "tool_name": "sqlite_query", "query": "-- sql_source_version: v2\n-- sql_source_label: v2_current\n-- sql_source_run_id: v2_cli_20260502_081223_a\n-- sql_source_dataset_id: m9\n-- family_id: cardinality_structure\n-- canonical_subitem_id: support_rank_profile_consistency\n-- intended_facet_id: support_concentration\n-- variant_semantic_role: ranked_signal_view\n-- template_id: tpl_cardinality_distinct_share_profile\n-- query_record_id: v2q_m9_fe78892a2f55fc1c\n-- problem_id: v2p_m9_69466bf5e57f70b2\n-- realization_mode: deterministic\n-- source_kind: deterministic\nWITH grouped AS (\n SELECT \"training_hours\" AS value_label, COUNT(*) AS support\n FROM \"m9\"\n GROUP BY \"training_hours\"\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", "result": "{\"query\": \"-- sql_source_version: v2\\n-- sql_source_label: v2_current\\n-- sql_source_run_id: v2_cli_20260502_081223_a\\n-- sql_source_dataset_id: m9\\n-- family_id: cardinality_structure\\n-- canonical_subitem_id: support_rank_profile_consistency\\n-- intended_facet_id: support_concentration\\n-- variant_semantic_role: ranked_signal_view\\n-- template_id: tpl_cardinality_distinct_share_profile\\n-- query_record_id: v2q_m9_fe78892a2f55fc1c\\n-- problem_id: v2p_m9_69466bf5e57f70b2\\n-- realization_mode: deterministic\\n-- source_kind: deterministic\\nWITH grouped AS (\\n SELECT \\\"training_hours\\\" AS value_label, COUNT(*) AS support\\n FROM \\\"m9\\\"\\n GROUP BY \\\"training_hours\\\"\\n), ranked AS (\\n SELECT\\n value_label,\\n support,\\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\\n FROM grouped\\n)\\nSELECT *\\nFROM ranked\\nORDER BY support DESC, value_label;\", \"columns\": [\"value_label\", \"support\", \"support_share\", \"cumulative_support\"], \"rows\": [{\"value_label\": \"28\", \"support\": 329, \"support_share\": 0.017172982566029858, \"cumulative_support\": 329}, {\"value_label\": \"12\", \"support\": 292, \"support_share\": 0.015241674496293977, \"cumulative_support\": 621}, {\"value_label\": \"18\", \"support\": 291, \"support_share\": 0.015189476980895709, \"cumulative_support\": 912}, {\"value_label\": \"22\", \"support\": 282, \"support_share\": 0.014719699342311305, \"cumulative_support\": 1194}, {\"value_label\": \"50\", \"support\": 279, \"support_share\": 0.014563106796116505, \"cumulative_support\": 1473}, {\"value_label\": \"20\", \"support\": 278, \"support_share\": 0.014510909280718238, \"cumulative_support\": 1751}, {\"value_label\": \"17\", \"support\": 273, \"support_share\": 0.014249921703726902, \"cumulative_support\": 2024}, {\"value_label\": \"24\", \"support\": 273, \"support_share\": 0.014249921703726902, \"cumulative_support\": 2297}, {\"value_label\": \"34\", \"support\": 261, \"support_share\": 0.013623551518947698, \"cumulative_support\": 2558}, {\"value_label\": \"6\", \"support\": 261, \"support_share\": 0.013623551518947698, \"cumulative_support\": 2819}, {\"value_label\": \"23\", \"support\": 258, \"support_share\": 0.013466958972752897, \"cumulative_support\": 3077}, {\"value_label\": \"21\", \"support\": 256, \"support_share\": 0.013362563941956363, \"cumulative_support\": 3333}, {\"value_label\": \"26\", \"support\": 254, \"support_share\": 0.013258168911159829, \"cumulative_support\": 3587}, {\"value_label\": \"56\", \"support\": 250, \"support_share\": 0.013049378849566761, \"cumulative_support\": 3837}, {\"value_label\": \"42\", \"support\": 242, \"support_share\": 0.012631798726380624, \"cumulative_support\": 4079}, {\"value_label\": \"10\", \"support\": 241, \"support_share\": 0.012579601210982358, \"cumulative_support\": 4320}, {\"value_label\": \"11\", \"support\": 237, \"support_share\": 0.01237081114938929, \"cumulative_support\": 4557}, {\"value_label\": \"48\", \"support\": 237, \"support_share\": 0.01237081114938929, \"cumulative_support\": 4794}, {\"value_label\": \"9\", \"support\": 234, \"support_share\": 0.012214218603194488, \"cumulative_support\": 5028}, {\"value_label\": \"14\", \"support\": 231, \"support_share\": 0.012057626056999686, \"cumulative_support\": 5259}, {\"value_label\": \"15\", \"support\": 230, \"support_share\": 0.01200542854160142, \"cumulative_support\": 5489}, {\"value_label\": \"8\", \"support\": 227, \"support_share\": 0.011848835995406619, \"cumulative_support\": 5716}, {\"value_label\": \"4\", \"support\": 224, \"support_share\": 0.011692243449211817, \"cumulative_support\": 5940}, {\"value_label\": \"46\", \"support\": 223, \"support_share\": 0.01164004593381355, \"cumulative_support\": 6163}, {\"value_label\": \"13\", \"support\": 213, \"support_share\": 0.01111807077983088, \"cumulative_support\": 6376}, {\"value_label\": \"36\", \"support\": 211, \"support_share\": 0.011013675749034346, \"cumulative_support\": 6587}, {\"value_label\": \"7\", \"support\": 209, \"support_share\": 0.010909280718237812, \"cumulative_support\": 6796}, {\"value_label\": \"32\", \"support\": 207, \"support_share\": 0.010804885687441278, \"cumulative_support\": 7003}, {\"value_label\": \"44\", \"support\": 205, \"support_share\": 0.010700490656644744, \"cumulative_support\": 7208}, {\"value_label\": \"25\", \"support\": 199, \"support_share\": 0.010387305564255142, \"cumulative_support\": 7407}, {\"value_label\": \"43\", \"support\": 199, \"support_share\": 0.010387305564255142, \"cumulative_support\": 7606}, {\"value_label\": \"52\", \"support\": 196, \"support_share\": 0.01023071301806034, \"cumulative_support\": 7802}, {\"value_label\": \"16\", \"support\": 192, \"support_share\": 0.010021922956467273, \"cumulative_support\": 7994}, {\"value_label\": \"40\", \"support\": 192, \"support_share\": 0.010021922956467273, \"cumulative_support\": 8186}, {\"value_label\": \"30\", \"support\": 187, \"support_share\": 0.009760935379475937, \"cumulative_support\": 8373}, {\"value_label\": \"31\", \"support\": 184, \"support_share\": 0.009604342833281135, \"cumulative_support\": 8557}, {\"value_label\": \"29\", \"support\": 179, \"support_share\": 0.009343355256289801, \"cumulative_support\": 8736}, {\"value_label\": \"39\", \"support\": 178, \"support_share\": 0.009291157740891533, \"cumulative_support\": 8914}, {\"value_label\": \"51\", \"support\": 176, \"support_share\": 0.009186762710095, \"cumulative_support\": 9090}, {\"value_label\": \"45\", \"support\": 175, \"support_share\": 0.009134565194696732, \"cumulative_support\": 9265}, {\"value_label\": \"55\", \"support\": 171, \"support_share\": 0.008925775133103664, \"cumulative_support\": 9436}, {\"value_label\": \"78\", \"support\": 165, \"support_share\": 0.008612590040714062, \"cumulative_support\": 9601}, {\"value_label\": \"19\", \"support\": 163, \"support_share\": 0.008508195009917528, \"cumulative_support\": 9764}, {\"value_label\": \"37\", \"support\": 163, \"support_share\": 0.008508195009917528, \"cumulative_support\": 9927}, {\"value_label\": \"35\", \"support\": 162, \"support_share\": 0.00845599749451926, \"cumulative_support\": 10089}, {\"value_label\": \"54\", \"support\": 161, \"support_share\": 0.008403799979120994, \"cumulative_support\": 10250}, {\"value_label\": \"47\", \"support\": 157, \"support_share\": 0.008195009917527927, \"cumulative_support\": 10407}, {\"value_label\": \"72\", \"support\": 153, \"support_share\": 0.007986219855934857, \"cumulative_support\": 10560}, {\"value_label\": \"33\", \"support\": 150, \"support_share\": 0.007829627309740057, \"cumulative_support\": 10710}, {\"value_label\": \"41\", \"support\": 145, \"support_share\": 0.007568639732748721, \"cumulative_support\": 10855}], \"row_count_returned\": 50, \"row_limit\": 50, \"truncated\": true, \"elapsed_ms\": 9.03}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..43e929965b38bfe92599f6f4a5fae8caf091fc84 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/run_manifest.json @@ -0,0 +1,57 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T16:08:56.253662+00:00", + "ended_at": "2026-05-19T16:08:56.263563+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_fe78892a2f55fc1c", + "problem_id": "v2p_m9_69466bf5e57f70b2", + "dataset_id": "m9", + "template_id": "tpl_cardinality_distinct_share_profile", + "template_name": "Cardinality Distinct Share Profile", + "family_id": "cardinality_structure", + "canonical_subitem_id": "support_rank_profile_consistency", + "intended_facet_id": "support_concentration", + "variant_semantic_role": "ranked_signal_view", + "subitem_assignment_source": "template_fixed", + "source_kind": "deterministic", + "realization_mode": "deterministic", + "gate_priority": "deterministic", + "extended_family": true, + "question": "Use template Cardinality Distinct Share Profile to probe support_rank_profile_consistency with semantic role ranked_signal_view. Focus on group_col=training_hours.", + "bindings": { + "group_col": "training_hours" + }, + "binding_roles": [ + "group_col" + ], + "coverage_target_min": "enumerate_all_applicable", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col} AS value_label, COUNT(*) AS support\n FROM {table}\n GROUP BY {group_col}\n), ranked AS (\n SELECT\n value_label,\n support,\n CAST(support AS FLOAT) / NULLIF(SUM(support) OVER (), 0) AS support_share,\n SUM(support) OVER (ORDER BY support DESC, value_label ROWS UNBOUNDED PRECEDING) AS cumulative_support\n FROM grouped\n)\nSELECT *\nFROM ranked\nORDER BY support DESC, value_label;", + "notes": [ + "default_facets=support_concentration,value_imbalance_profile", + "template_selection_mode=deterministic", + "problem_index_within_template=11", + "sql_variant_index=1/1" + ], + "template_selection_mode": "deterministic", + "selected_template_rank": 0, + "problem_index_within_template": 11, + "sql_variant_index": 1, + "sql_variant_total": 1 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_fe78892a2f55fc1c.sql", + "usage_summary": { + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..96c9ff4feec395919fc26411d18d078b8af6e1c7 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fe78892a2f55fc1c/usage_summary.json @@ -0,0 +1,9 @@ +{ + "engine": "template", + "input_tokens": 0, + "cached_input_tokens": 0, + "output_tokens": 0, + "total_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "none" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/final_answer.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/final_answer.txt new file mode 100644 index 0000000000000000000000000000000000000000..c703e6c3aad8a93e87ca4fe7f5cbd2c2efaded25 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/final_answer.txt @@ -0,0 +1,2 @@ +SQL executed successfully for: Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=experience, measure_col=enrollee_id. +Result preview: [{"experience": ">20", "group_value": 54456108.0}, {"experience": "5", "group_value": 24561810.0}, {"experience": "4", "group_value": 23932474.0}, {"experience": "3", "group_value": 23669243.0}, {"experience": "6", "group_value": 20681608.0}] \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/generated_sql.sql b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/generated_sql.sql new file mode 100644 index 0000000000000000000000000000000000000000..c0c6d8d52b07c4d072c6839da71a1e82de1d0d94 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/generated_sql.sql @@ -0,0 +1,32 @@ +-- sql_source_version: v2 +-- sql_source_label: v2_current +-- sql_source_run_id: v2_cli_20260502_081223_a +-- sql_source_dataset_id: m9 +-- family_id: tail_rarity_structure +-- canonical_subitem_id: tail_mass_similarity +-- intended_facet_id: tail_ranked_signal +-- variant_semantic_role: filtered_stable_view +-- template_id: tpl_tpch_relative_total_threshold +-- query_record_id: v2q_m9_fef72908b4f36fae +-- problem_id: v2p_m9_6dafced33d353f4d +-- realization_mode: agent +-- source_kind: agent +WITH grouped AS ( + SELECT + "experience", + SUM(CAST("enrollee_id" AS REAL)) AS group_value + FROM "m9" + WHERE COALESCE("experience", '') <> '' + AND COALESCE("enrollee_id", '') <> '' + GROUP BY "experience" +), total AS ( + SELECT SUM(group_value) AS total_value + FROM grouped +) +SELECT + g."experience", + g.group_value +FROM grouped AS g +CROSS JOIN total AS t +WHERE g.group_value > t.total_value * 0.05 +ORDER BY g.group_value DESC; diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/query_results.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/query_results.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..fa2bf830dcdf42d2ecb87c28de1359e32601fbfe --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/query_results.jsonl @@ -0,0 +1 @@ +{"step_index": 1, "message_index": 0, "node_name": "v2-cli:codex", "tool_name": "sqlite_query", "query": "-- template_id: tpl_tpch_relative_total_threshold\nWITH grouped AS (\n SELECT\n \"experience\",\n SUM(CAST(\"enrollee_id\" AS REAL)) AS group_value\n FROM \"m9\"\n WHERE COALESCE(\"experience\", '') <> ''\n AND COALESCE(\"enrollee_id\", '') <> ''\n GROUP BY \"experience\"\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT\n g.\"experience\",\n g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * 0.05\nORDER BY g.group_value DESC;", "result": "{\"query\": \"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT\\n \\\"experience\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS group_value\\n FROM \\\"m9\\\"\\n WHERE COALESCE(\\\"experience\\\", '') <> ''\\n AND COALESCE(\\\"enrollee_id\\\", '') <> ''\\n GROUP BY \\\"experience\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT\\n g.\\\"experience\\\",\\n g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\", \"columns\": [\"experience\", \"group_value\"], \"rows\": [{\"experience\": \">20\", \"group_value\": 54456108.0}, {\"experience\": \"5\", \"group_value\": 24561810.0}, {\"experience\": \"4\", \"group_value\": 23932474.0}, {\"experience\": \"3\", \"group_value\": 23669243.0}, {\"experience\": \"6\", \"group_value\": 20681608.0}, {\"experience\": \"2\", \"group_value\": 19864312.0}, {\"experience\": \"7\", \"group_value\": 17338063.0}, {\"experience\": \"9\", \"group_value\": 16457366.0}, {\"experience\": \"10\", \"group_value\": 16341566.0}], \"row_count_returned\": 9, \"row_limit\": 50, \"truncated\": false, \"elapsed_ms\": 16.6}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/run_manifest.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/run_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..6b784f90cba7b4cf0f67768556953b2ab4bd4d60 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/run_manifest.json @@ -0,0 +1,89 @@ +{ + "run_id": "v2_cli_20260502_081223_a", + "dataset_id": "m9", + "started_at": "2026-05-19T15:49:11.006739+00:00", + "ended_at": "2026-05-19T15:49:24.729339+00:00", + "status": "completed", + "engine": "cli", + "question_record": { + "query_record_id": "v2q_m9_fef72908b4f36fae", + "problem_id": "v2p_m9_6dafced33d353f4d", + "dataset_id": "m9", + "template_id": "tpl_tpch_relative_total_threshold", + "template_name": "Relative-to-Total Extreme Threshold", + "family_id": "tail_rarity_structure", + "canonical_subitem_id": "tail_mass_similarity", + "intended_facet_id": "tail_ranked_signal", + "variant_semantic_role": "filtered_stable_view", + "subitem_assignment_source": "planner_selected", + "source_kind": "agent", + "realization_mode": "agent", + "gate_priority": "primary", + "extended_family": false, + "question": "Use template Relative-to-Total Extreme Threshold to probe tail_mass_similarity with semantic role filtered_stable_view. Focus on group_col=experience, measure_col=enrollee_id.", + "bindings": { + "group_col": "experience", + "measure_col": "enrollee_id", + "top_k": 18, + "top_n": 6, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 22283.62, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "binding_roles": [ + "group_col", + "measure_col" + ], + "coverage_target_min": "5", + "runtime_sql_skeleton": "WITH grouped AS (\n SELECT {group_col}, SUM({measure_col}) AS group_value\n FROM {table}\n GROUP BY {group_col}\n), total AS (\n SELECT SUM(group_value) AS total_value\n FROM grouped\n)\nSELECT g.{group_col}, g.group_value\nFROM grouped AS g\nCROSS JOIN total AS t\nWHERE g.group_value > t.total_value * {fraction_threshold}\nORDER BY g.group_value DESC;", + "notes": [ + "default_facets=tail_ranked_signal", + "template_selection_mode=rule", + "problem_index_within_template=7", + "sql_variant_index=2/2", + "binding_index=78" + ], + "template_selection_mode": "rule", + "selected_template_rank": 7, + "problem_index_within_template": 7, + "sql_variant_index": 2, + "sql_variant_total": 2 + }, + "mode": "subitem_workload_v2", + "sql_source_version": "v2", + "sql_source_label": "v2_current", + "generated_sql_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/sql/v2q_m9_fef72908b4f36fae.sql", + "usage_summary": { + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_fef72908b4f36fae", + "api_calls": 0, + "input_tokens": 14786, + "cached_input_tokens": 13696, + "output_tokens": 728, + "total_tokens": 15514, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13699.55, + "sql_execution_elapsed_ms_total": 16.6, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." + } +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/trace.jsonl b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/trace.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8c8506f0312196e7d828947b4386a32c9ee8180d --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/trace.jsonl @@ -0,0 +1 @@ +{"timestamp": "2026-05-19T15:49:24.710497+00:00", "event_type": "ai_cli_sql_generation", "engine": "v2-cli:codex", "attempt": 1, "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", "returncode": 0, "elapsed_ms": 13699.55, "started_at": "2026-05-19T15:49:11.009739+00:00", "ended_at": "2026-05-19T15:49:24.709329+00:00", "prompt_metrics": {"chars": 9852, "bytes_utf8": 9852, "lines": 264, "estimated_tokens": null}, "response_metrics": {"chars": 825, "bytes_utf8": 825, "lines": 1, "estimated_tokens": null}, "usage": {"input_tokens": 14786, "cached_input_tokens": 13696, "output_tokens": 728, "reasoning_output_tokens": 516}, "stderr_preview": "", "stdout_preview": "{\"sql\":\"-- template_id: tpl_tpch_relative_total_threshold\\nWITH grouped AS (\\n SELECT\\n \\\"experience\\\",\\n SUM(CAST(\\\"enrollee_id\\\" AS REAL)) AS group_value\\n FROM \\\"m9\\\"\\n WHERE COALESCE(\\\"experience\\\", '') <> ''\\n AND COALESCE(\\\"enrollee_id\\\", '') <> ''\\n GROUP BY \\\"experience\\\"\\n), total AS (\\n SELECT SUM(group_value) AS total_value\\n FROM grouped\\n)\\nSELECT\\n g.\\\"experience\\\",\\n g.group_value\\nFROM grouped AS g\\nCROSS JOIN total AS t\\nWHERE g.group_value > t.total_value * 0.05\\nORDER BY g.group_value DESC;\",\"notes\":\"Uses the planned Relative-to-Total Extreme Threshold template with group_col=\\\"experience\\\" and measure_col=\\\"enrollee_id\\\", casting the text identifier to REAL for SQLite aggregation and filtering out empty group/measure values for a stable grouped view.\"}"} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/usage_summary.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/usage_summary.json new file mode 100644 index 0000000000000000000000000000000000000000..c16a40ff73aba0d938410b8405b343c933235323 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/usage_summary.json @@ -0,0 +1,20 @@ +{ + "dataset_id": "m9", + "model": "v2-cli:codex", + "run_id": "v2q_m9_fef72908b4f36fae", + "api_calls": 0, + "input_tokens": 14786, + "cached_input_tokens": 13696, + "output_tokens": 728, + "total_tokens": 15514, + "cost_usd": 0.0, + "ai_cli_calls": 1, + "estimated_input_tokens": 0, + "estimated_output_tokens": 0, + "estimated_total_tokens": 0, + "usage_source": "ai_cli_json_usage", + "cli_elapsed_ms_total": 13699.55, + "sql_execution_elapsed_ms_total": 16.6, + "conversation_log_path": "/data/jialinzhang/TabQueryBench/sql_workloads/v2_current/runs_and_launches/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_fef72908b4f36fae/cli/conversation.jsonl", + "note": "Executed through a local AI CLI with structured usage metadata." +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_attempt_1.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_attempt_1.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..c11d77b0a5d6a92956d56f995d54e2001ea8f62c --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_attempt_1.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 1, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:02:24.355708+00:00", + "ended_at": "2026-05-19T16:02:27.601475+00:00", + "elapsed_ms": 3245.74, + "returncode": 1, + "prompt_metrics": { + "chars": 9533, + "bytes_utf8": 9533, + "lines": 267, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_1.txt", + "response_path": "cli/sql_response_attempt_1.txt", + "raw_response_path": "cli/sql_response_attempt_1.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_1.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_attempt_2.metadata.json b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_attempt_2.metadata.json new file mode 100644 index 0000000000000000000000000000000000000000..2f3ef3c8bbe7975c74cb24aa12c4a57daf965f2a --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_attempt_2.metadata.json @@ -0,0 +1,43 @@ +{ + "attempt": 2, + "phase": "sql_generation", + "command": "codex exec --skip-git-repo-check --disable plugins --sandbox read-only --cd \"/data/jialinzhang/SQLagent\" -m gpt-5.4 --json -", + "started_at": "2026-05-19T16:02:28.603164+00:00", + "ended_at": "2026-05-19T16:02:31.901814+00:00", + "elapsed_ms": 3298.6, + "returncode": 1, + "prompt_metrics": { + "chars": 9533, + "bytes_utf8": 9533, + "lines": 267, + "estimated_tokens": null + }, + "stdout_metrics": { + "chars": 281, + "bytes_utf8": 281, + "lines": 4, + "estimated_tokens": null + }, + "stderr_metrics": { + "chars": 0, + "bytes_utf8": 0, + "lines": 0, + "estimated_tokens": null + }, + "parsed_output": { + "format": "jsonl_events", + "text_metrics": { + "chars": 280, + "bytes_utf8": 280, + "lines": 4, + "estimated_tokens": null + }, + "usage": {} + }, + "status": "failed", + "error": "AI CLI command failed with exit code 1: ", + "prompt_path": "cli/sql_prompt_attempt_2.txt", + "response_path": "cli/sql_response_attempt_2.txt", + "raw_response_path": "cli/sql_response_attempt_2.raw.txt", + "stderr_path": "cli/sql_stderr_attempt_2.txt" +} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_prompt_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_prompt_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..0a5f2f38516922099905c337cbb582f9d8920293 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_prompt_attempt_1.txt @@ -0,0 +1,267 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=company_type, condition_col=gender.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "company_type", + "condition_col": "gender", + "condition_value": "", + "positive_value": "Male", + "negative_value": "", + "top_k": 19, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_prompt_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_prompt_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..0a5f2f38516922099905c337cbb582f9d8920293 --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_prompt_attempt_2.txt @@ -0,0 +1,267 @@ +You are generating one SQLite SELECT query for a single-table SQL QA task. +Return strict JSON only, with this schema: {"sql": "...", "notes": "..."}. +Rules: +- Use only the provided table and columns. +- Do not write INSERT, UPDATE, DELETE, DROP, ALTER, CREATE, PRAGMA, ATTACH, DETACH, or VACUUM. +- Prefer the planned template and bound roles when provided. +- Add a leading SQL comment exactly like: -- template_id: . +- Generate SQLite-compatible SQL. SQLite does not support PERCENTILE_CONT or STDDEV. +- Quote identifiers with double quotes. +- Return no markdown and no extra prose. + +Dataset context: +Dataset context for SQL QA: +- dataset_id: m9 +- dataset_name: Hr Analytics Job Change Of Data Scientists +- table_name: m9 +- table_layout: single-table dataset (do not assume joins). +- row_semantics: One row is one tabular observation with 13 feature columns and target `target`. +- task_type: classification +- target_column: target +- main_row_count: 19158 +- important_fields: +- enrollee_id: role=feature, type=identifier_numeric. tags=['identifier', 'probe_exclude', 'high_cardinality_candidate'] desc=Identifier-like field for enrollee id. +- city: role=feature, type=categorical_nominal. tags=['condition_candidate'] desc=Categorical field for city. +- city_development_index: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure'] desc=Numeric field for city development index. +- gender: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for gender. +- relevent_experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate'] desc=Categorical field for relevent experience. +- enrolled_university: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for enrolled university. +- education_level: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for education level. +- major_discipline: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for major discipline. +- experience: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for experience. +- company_size: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company size. +- company_type: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for company type. +- last_new_job: role=feature, type=categorical_nominal. tags=['subgroup_candidate', 'condition_candidate', 'missingness_candidate'] desc=Categorical field for last new job. +- training_hours: role=feature, type=numeric_discrete. tags=['subgroup_candidate', 'condition_candidate', 'measure', 'high_cardinality_candidate'] desc=Numeric field for training hours. +- target: role=target, type=categorical_ordinal_target. ordered=['0.0', '1.0'] tags=['subgroup_candidate', 'condition_candidate', 'target_candidate'] desc=Target field for target. +- useful_field_combinations: [['city_development_index', 'gender', 'target'], ['city_development_index', 'city_development_index', 'target'], ['city_development_index', 'city', 'target']] +- fields_requiring_caution: ['target', 'training_hours', 'gender', 'enrolled_university', 'education_level'] +- source_url: https://www.kaggle.com/datasets/arashnic/hr-analytics-job-change-of-data-scientists + +SQLite schema snapshot: +{ + "table_name": "m9", + "quoted_table_name": "\"m9\"", + "row_count": 19158, + "columns": [ + { + "name": "enrollee_id", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "city_development_index", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "gender", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "relevent_experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "enrolled_university", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "education_level", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "major_discipline", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "experience", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_size", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "company_type", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "last_new_job", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "training_hours", + "type": "TEXT", + "notnull": false, + "pk": false + }, + { + "name": "target", + "type": "TEXT", + "notnull": false, + "pk": false + } + ], + "sample_rows": [ + { + "enrollee_id": "8949", + "city": "city_103", + "city_development_index": "0.92", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "", + "company_type": "", + "last_new_job": "1", + "training_hours": "36", + "target": "1.0" + }, + { + "enrollee_id": "29725", + "city": "city_40", + "city_development_index": "0.7759999999999999", + "gender": "Male", + "relevent_experience": "No relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "15", + "company_size": "50-99", + "company_type": "Pvt Ltd", + "last_new_job": ">4", + "training_hours": "47", + "target": "0.0" + }, + { + "enrollee_id": "11561", + "city": "city_21", + "city_development_index": "0.624", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "Full time course", + "education_level": "Graduate", + "major_discipline": "STEM", + "experience": "5", + "company_size": "", + "company_type": "", + "last_new_job": "never", + "training_hours": "83", + "target": "0.0" + }, + { + "enrollee_id": "33241", + "city": "city_115", + "city_development_index": "0.789", + "gender": "", + "relevent_experience": "No relevent experience", + "enrolled_university": "", + "education_level": "Graduate", + "major_discipline": "Business Degree", + "experience": "<1", + "company_size": "", + "company_type": "Pvt Ltd", + "last_new_job": "never", + "training_hours": "52", + "target": "1.0" + }, + { + "enrollee_id": "666", + "city": "city_162", + "city_development_index": "0.767", + "gender": "Male", + "relevent_experience": "Has relevent experience", + "enrolled_university": "no_enrollment", + "education_level": "Masters", + "major_discipline": "STEM", + "experience": ">20", + "company_size": "50-99", + "company_type": "Funded Startup", + "last_new_job": "4", + "training_hours": "8", + "target": "0.0" + } + ] +} + +Shortlisted templates: +[ + { + "template_id": "tpl_m4_group_condition_rate", + "template_name": "Grouped Condition Rate", + "primary_family": "conditional_dependency_structure", + "portability": "yes", + "sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;", + "required_roles": [ + "group_col", + "condition_col" + ] + } +] + +Problem instance: +{ + "dataset_id": "m9", + "question": "Use template Grouped Condition Rate to probe dependency_strength_similarity with semantic role focused_target_view. Focus on group_col=company_type, condition_col=gender.", + "planned_template_id": "tpl_m4_group_condition_rate", + "bindings": { + "group_col": "company_type", + "condition_col": "gender", + "condition_value": "", + "positive_value": "Male", + "negative_value": "", + "top_k": 19, + "top_n": 4, + "num_tiles": 10, + "percentile_value": 0.9, + "z_threshold": 2.0, + "fraction_threshold": 0.05, + "baseline_multiplier": 1.75, + "baseline_fraction": 0.1, + "min_group_size": 5, + "min_support": 4, + "measure_threshold": 88.0, + "time_grain": "month", + "lookback_rows": 3, + "current_period_start": "'2024-01-01'", + "current_period_end": "'2024-04-01'", + "previous_period_start": "'2023-10-01'", + "previous_period_end": "'2024-01-01'", + "drift_ratio_threshold": 0.8 + }, + "can_vary": [], + "must_fix": [], + "runtime_sql_skeleton": "SELECT {group_col},\n AVG(CASE WHEN {condition_col} = {condition_value} THEN 1 ELSE 0 END) AS condition_rate\nFROM {table}\nGROUP BY {group_col}\nORDER BY condition_rate DESC;" +} + +Repair context: +{} diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_response_attempt_1.raw.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_response_attempt_1.raw.txt new file mode 100644 index 0000000000000000000000000000000000000000..fde6ee025541b244677b367ddb5cd96ad3b985ea --- /dev/null +++ b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_response_attempt_1.raw.txt @@ -0,0 +1,4 @@ +{"type":"thread.started","thread_id":"019e40f9-5d07-77b3-a47e-1bcfcbf0ff9b"} +{"type":"turn.started"} +{"type":"error","message":"Quota exceeded. 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Check your plan and billing details."}} \ No newline at end of file diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_stderr_attempt_1.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_stderr_attempt_1.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391 diff --git a/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_stderr_attempt_2.txt b/Query/sql/v2/runs/v2_cli_20260502_081223_a/m9/artifacts/v2q_m9_ff4b3eaa47b51f0a/cli/sql_stderr_attempt_2.txt new file mode 100644 index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391