datasets/vertica_snowflake_pairs.jsonl

{"id": "zeroifnull_basic", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(amount) AS amount FROM staging.orders", "target_sql": "SELECT COALESCE(amount, 0) AS amount FROM staging.orders", "notes": "ZEROIFNULL \u2192 COALESCE(expr, 0)"}
{"id": "nvl_basic", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT NVL(discount, 0) AS discount FROM staging.orders", "target_sql": "SELECT COALESCE(discount, 0) AS discount FROM staging.orders", "notes": "NVL \u2192 COALESCE"}
{"id": "date_sub_days", "category": "date", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT * FROM t WHERE order_date >= CURRENT_DATE - 30", "target_sql": "SELECT * FROM t WHERE order_date >= DATEADD(day, -30, CURRENT_DATE)", "notes": "Date arithmetic \u2192 DATEADD"}
{"id": "local_temp", "category": "ddl", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "CREATE LOCAL TEMP TABLE tmp_x ON COMMIT PRESERVE ROWS AS SELECT 1 AS id", "target_sql": "CREATE OR REPLACE TEMPORARY TABLE tmp_x AS SELECT 1 AS id", "notes": "LOCAL TEMP \u2192 TEMPORARY TABLE"}
{"id": "string_agg", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT STRING_AGG(name, ',') FROM users", "target_sql": "SELECT LISTAGG(name, ',') FROM users", "notes": "STRING_AGG \u2192 LISTAGG"}
{"id": "approx_distinct", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT APPROXIMATE_COUNT_DISTINCT(user_id) FROM events", "target_sql": "SELECT APPROX_COUNT_DISTINCT(user_id) FROM events", "notes": "APPROXIMATE_COUNT_DISTINCT \u2192 APPROX_COUNT_DISTINCT"}
{"id": "datediff_quoted", "category": "date", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT DATEDIFF('day', start_dt, end_dt) FROM t", "target_sql": "SELECT DATEDIFF(day, start_dt, end_dt) FROM t", "notes": "Quoted DATEDIFF unit \u2192 unquoted"}
{"id": "sysdate", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT SYSDATE FROM dual", "target_sql": "SELECT CURRENT_TIMESTAMP()", "notes": "SYSDATE + drop DUAL"}
{"id": "getdate_redshift", "category": "function", "source_dialect": "redshift", "target_dialect": "snowflake", "source_sql": "SELECT GETDATE(), NVL(x, 0) FROM t", "target_sql": "SELECT CURRENT_TIMESTAMP(), COALESCE(x, 0) FROM t", "notes": "GETDATE/NVL mappings"}
{"id": "bigquery_ifnull", "category": "function", "source_dialect": "bigquery", "target_dialect": "snowflake", "source_sql": "SELECT IFNULL(a, 0), STRING_AGG(b, ',') FROM t GROUP BY a", "target_sql": "SELECT COALESCE(a, 0), LISTAGG(b, ',') FROM t GROUP BY a", "notes": "IFNULL/STRING_AGG \u2192 COALESCE/LISTAGG"}
{"id": "feature_rfm", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT customer_id, ZEROIFNULL(SUM(order_amount)) AS monetary, COUNT(DISTINCT order_id) AS frequency, DATEDIFF('day', MAX(order_date), CURRENT_DATE) AS recency FROM staging.orders GROUP BY customer_id", "target_sql": "SELECT customer_id, COALESCE(SUM(order_amount), 0) AS monetary, COUNT(DISTINCT order_id) AS frequency, DATEDIFF(day, MAX(order_date), CURRENT_DATE) AS recency FROM staging.orders GROUP BY customer_id", "notes": "ML RFM feature SQL migration"}
{"id": "feature_label", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT user_id, CASE WHEN ZEROIFNULL(churn_score) > 0.7 THEN 1 ELSE 0 END AS churn_label FROM ml.user_scores", "target_sql": "SELECT user_id, CASE WHEN COALESCE(churn_score, 0) > 0.7 THEN 1 ELSE 0 END AS churn_label FROM ml.user_scores", "notes": "Training label feature SQL"}
{"id": "date_sub_7", "category": "date", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT * FROM events WHERE event_date >= CURRENT_DATE - 7", "target_sql": "SELECT * FROM events WHERE event_date >= DATEADD(day, -7, CURRENT_DATE)", "notes": "CURRENT_DATE - 7 \u2192 DATEADD"}
{"id": "date_sub_14", "category": "date", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT * FROM events WHERE event_date >= CURRENT_DATE - 14", "target_sql": "SELECT * FROM events WHERE event_date >= DATEADD(day, -14, CURRENT_DATE)", "notes": "CURRENT_DATE - 14 \u2192 DATEADD"}
{"id": "date_sub_30", "category": "date", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT * FROM events WHERE event_date >= CURRENT_DATE - 30", "target_sql": "SELECT * FROM events WHERE event_date >= DATEADD(day, -30, CURRENT_DATE)", "notes": "CURRENT_DATE - 30 \u2192 DATEADD"}
{"id": "date_sub_60", "category": "date", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT * FROM events WHERE event_date >= CURRENT_DATE - 60", "target_sql": "SELECT * FROM events WHERE event_date >= DATEADD(day, -60, CURRENT_DATE)", "notes": "CURRENT_DATE - 60 \u2192 DATEADD"}
{"id": "date_sub_90", "category": "date", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT * FROM events WHERE event_date >= CURRENT_DATE - 90", "target_sql": "SELECT * FROM events WHERE event_date >= DATEADD(day, -90, CURRENT_DATE)", "notes": "CURRENT_DATE - 90 \u2192 DATEADD"}
{"id": "date_sub_180", "category": "date", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT * FROM events WHERE event_date >= CURRENT_DATE - 180", "target_sql": "SELECT * FROM events WHERE event_date >= DATEADD(day, -180, CURRENT_DATE)", "notes": "CURRENT_DATE - 180 \u2192 DATEADD"}
{"id": "date_sub_365", "category": "date", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT * FROM events WHERE event_date >= CURRENT_DATE - 365", "target_sql": "SELECT * FROM events WHERE event_date >= DATEADD(day, -365, CURRENT_DATE)", "notes": "CURRENT_DATE - 365 \u2192 DATEADD"}
{"id": "zeroifnull_amount", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(amount) AS amount FROM staging.facts", "target_sql": "SELECT COALESCE(amount, 0) AS amount FROM staging.facts", "notes": "ZEROIFNULL expansion"}
{"id": "zeroifnull_revenue", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(revenue) AS revenue FROM staging.facts", "target_sql": "SELECT COALESCE(revenue, 0) AS revenue FROM staging.facts", "notes": "ZEROIFNULL expansion"}
{"id": "zeroifnull_fee", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(fee) AS fee FROM staging.facts", "target_sql": "SELECT COALESCE(fee, 0) AS fee FROM staging.facts", "notes": "ZEROIFNULL expansion"}
{"id": "zeroifnull_tax", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(tax) AS tax FROM staging.facts", "target_sql": "SELECT COALESCE(tax, 0) AS tax FROM staging.facts", "notes": "ZEROIFNULL expansion"}
{"id": "zeroifnull_balance", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(balance) AS balance FROM staging.facts", "target_sql": "SELECT COALESCE(balance, 0) AS balance FROM staging.facts", "notes": "ZEROIFNULL expansion"}
{"id": "zeroifnull_score", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score) AS score FROM staging.facts", "target_sql": "SELECT COALESCE(score, 0) AS score FROM staging.facts", "notes": "ZEROIFNULL expansion"}
{"id": "zeroifnull_qty", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(qty) AS qty FROM staging.facts", "target_sql": "SELECT COALESCE(qty, 0) AS qty FROM staging.facts", "notes": "ZEROIFNULL expansion"}
{"id": "agg_mix_1", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_1)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_1), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_2", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_2)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_2), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_3", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_3)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_3), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_4", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_4)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_4), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_5", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_5)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_5), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_6", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_6)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_6), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_7", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_7)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_7), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_8", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_8)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_8), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_9", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_9)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_9), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_10", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_10)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_10), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_11", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_11)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_11), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_12", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_12)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_12), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_13", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_13)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_13), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_14", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_14)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_14), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_15", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_15)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_15), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_16", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_16)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_16), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_17", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_17)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_17), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_18", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_18)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_18), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_19", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_19)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_19), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_20", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_20)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_20), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_21", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_21)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_21), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_22", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_22)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_22), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_23", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_23)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_23), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_24", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_24)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_24), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_25", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_25)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_25), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_26", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_26)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_26), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_27", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_27)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_27), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_28", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_28)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_28), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_29", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_29)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_29), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_30", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_30)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_30), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_31", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_31)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_31), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_32", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_32)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_32), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_33", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_33)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_33), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_34", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_34)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_34), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_35", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_35)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_35), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_36", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_36)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_36), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_37", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_37)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_37), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_38", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_38)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_38), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_39", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_39)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_39), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_40", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_40)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_40), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_41", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_41)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_41), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_42", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_42)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_42), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_43", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_43)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_43), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_44", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_44)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_44), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_45", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_45)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_45), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_46", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_46)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_46), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_47", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_47)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_47), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_48", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_48)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_48), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_49", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_49)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_49), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_50", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_50)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_50), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_51", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_51)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_51), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_52", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_52)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_52), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_53", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_53)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_53), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_54", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_54)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_54), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_55", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_55)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_55), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_56", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_56)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_56), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_57", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_57)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_57), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_58", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_58)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_58), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_59", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_59)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_59), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_60", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_60)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_60), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_61", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_61)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_61), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_62", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_62)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_62), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_63", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_63)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_63), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_64", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_64)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_64), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_65", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_65)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_65), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_66", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_66)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_66), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_67", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_67)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_67), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_68", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_68)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_68), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_69", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_69)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_69), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_70", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_70)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_70), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_71", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_71)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_71), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_72", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_72)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_72), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_73", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_73)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_73), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_74", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_74)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_74), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_75", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_75)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_75), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_76", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_1, ZEROIFNULL(SUM(metric_76)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_1, COALESCE(SUM(metric_76), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_77", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_2, ZEROIFNULL(SUM(metric_77)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_2, COALESCE(SUM(metric_77), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_78", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_3, ZEROIFNULL(SUM(metric_78)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "target_sql": "SELECT dim_3, COALESCE(SUM(metric_78), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_0 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_79", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_4, ZEROIFNULL(SUM(metric_79)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "target_sql": "SELECT dim_4, COALESCE(SUM(metric_79), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_1 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "agg_mix_80", "category": "aggregate", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT dim_0, ZEROIFNULL(SUM(metric_80)), APPROXIMATE_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "target_sql": "SELECT dim_0, COALESCE(SUM(metric_80), 0), APPROX_COUNT_DISTINCT(user_id) FROM fact_2 GROUP BY 1", "notes": "Synthetic aggregate pair"}
{"id": "oracle_nvl_1", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_1, 0) FROM dual", "target_sql": "SELECT COALESCE(col_1, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_2", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_2, 0) FROM dual", "target_sql": "SELECT COALESCE(col_2, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_3", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_3, 0) FROM dual", "target_sql": "SELECT COALESCE(col_3, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_4", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_4, 0) FROM dual", "target_sql": "SELECT COALESCE(col_4, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_5", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_5, 0) FROM dual", "target_sql": "SELECT COALESCE(col_5, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_6", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_6, 0) FROM dual", "target_sql": "SELECT COALESCE(col_6, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_7", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_7, 0) FROM dual", "target_sql": "SELECT COALESCE(col_7, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_8", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_8, 0) FROM dual", "target_sql": "SELECT COALESCE(col_8, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_9", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_9, 0) FROM dual", "target_sql": "SELECT COALESCE(col_9, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_10", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_10, 0) FROM dual", "target_sql": "SELECT COALESCE(col_10, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_11", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_11, 0) FROM dual", "target_sql": "SELECT COALESCE(col_11, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_12", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_12, 0) FROM dual", "target_sql": "SELECT COALESCE(col_12, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_13", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_13, 0) FROM dual", "target_sql": "SELECT COALESCE(col_13, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_14", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_14, 0) FROM dual", "target_sql": "SELECT COALESCE(col_14, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_15", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_15, 0) FROM dual", "target_sql": "SELECT COALESCE(col_15, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_16", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_16, 0) FROM dual", "target_sql": "SELECT COALESCE(col_16, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_17", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_17, 0) FROM dual", "target_sql": "SELECT COALESCE(col_17, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_18", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_18, 0) FROM dual", "target_sql": "SELECT COALESCE(col_18, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_19", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_19, 0) FROM dual", "target_sql": "SELECT COALESCE(col_19, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_20", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_20, 0) FROM dual", "target_sql": "SELECT COALESCE(col_20, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_21", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_21, 0) FROM dual", "target_sql": "SELECT COALESCE(col_21, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_22", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_22, 0) FROM dual", "target_sql": "SELECT COALESCE(col_22, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_23", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_23, 0) FROM dual", "target_sql": "SELECT COALESCE(col_23, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_24", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_24, 0) FROM dual", "target_sql": "SELECT COALESCE(col_24, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_25", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_25, 0) FROM dual", "target_sql": "SELECT COALESCE(col_25, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_26", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_26, 0) FROM dual", "target_sql": "SELECT COALESCE(col_26, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_27", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_27, 0) FROM dual", "target_sql": "SELECT COALESCE(col_27, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_28", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_28, 0) FROM dual", "target_sql": "SELECT COALESCE(col_28, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_29", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_29, 0) FROM dual", "target_sql": "SELECT COALESCE(col_29, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_30", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_30, 0) FROM dual", "target_sql": "SELECT COALESCE(col_30, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_31", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_31, 0) FROM dual", "target_sql": "SELECT COALESCE(col_31, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_32", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_32, 0) FROM dual", "target_sql": "SELECT COALESCE(col_32, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_33", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_33, 0) FROM dual", "target_sql": "SELECT COALESCE(col_33, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_34", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_34, 0) FROM dual", "target_sql": "SELECT COALESCE(col_34, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_35", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_35, 0) FROM dual", "target_sql": "SELECT COALESCE(col_35, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_36", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_36, 0) FROM dual", "target_sql": "SELECT COALESCE(col_36, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_37", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_37, 0) FROM dual", "target_sql": "SELECT COALESCE(col_37, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_38", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_38, 0) FROM dual", "target_sql": "SELECT COALESCE(col_38, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_39", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_39, 0) FROM dual", "target_sql": "SELECT COALESCE(col_39, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_40", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_40, 0) FROM dual", "target_sql": "SELECT COALESCE(col_40, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_41", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_41, 0) FROM dual", "target_sql": "SELECT COALESCE(col_41, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_42", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_42, 0) FROM dual", "target_sql": "SELECT COALESCE(col_42, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_43", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_43, 0) FROM dual", "target_sql": "SELECT COALESCE(col_43, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_44", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_44, 0) FROM dual", "target_sql": "SELECT COALESCE(col_44, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_45", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_45, 0) FROM dual", "target_sql": "SELECT COALESCE(col_45, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_46", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_46, 0) FROM dual", "target_sql": "SELECT COALESCE(col_46, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_47", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_47, 0) FROM dual", "target_sql": "SELECT COALESCE(col_47, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_48", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_48, 0) FROM dual", "target_sql": "SELECT COALESCE(col_48, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_49", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_49, 0) FROM dual", "target_sql": "SELECT COALESCE(col_49, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_50", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_50, 0) FROM dual", "target_sql": "SELECT COALESCE(col_50, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_51", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_51, 0) FROM dual", "target_sql": "SELECT COALESCE(col_51, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_52", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_52, 0) FROM dual", "target_sql": "SELECT COALESCE(col_52, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_53", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_53, 0) FROM dual", "target_sql": "SELECT COALESCE(col_53, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_54", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_54, 0) FROM dual", "target_sql": "SELECT COALESCE(col_54, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_55", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_55, 0) FROM dual", "target_sql": "SELECT COALESCE(col_55, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_56", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_56, 0) FROM dual", "target_sql": "SELECT COALESCE(col_56, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_57", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_57, 0) FROM dual", "target_sql": "SELECT COALESCE(col_57, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_58", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_58, 0) FROM dual", "target_sql": "SELECT COALESCE(col_58, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_59", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_59, 0) FROM dual", "target_sql": "SELECT COALESCE(col_59, 0)", "notes": "Oracle NVL expansion"}
{"id": "oracle_nvl_60", "category": "function", "source_dialect": "oracle", "target_dialect": "snowflake", "source_sql": "SELECT NVL(col_60, 0) FROM dual", "target_sql": "SELECT COALESCE(col_60, 0)", "notes": "Oracle NVL expansion"}
{"id": "ml_feature_1", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_1)) AS f_1 FROM ml.training_window WHERE ds >= CURRENT_DATE - 8 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_1), 0) AS f_1 FROM ml.training_window WHERE ds >= DATEADD(day, -8, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_2", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_2)) AS f_2 FROM ml.training_window WHERE ds >= CURRENT_DATE - 9 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_2), 0) AS f_2 FROM ml.training_window WHERE ds >= DATEADD(day, -9, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_3", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_3)) AS f_3 FROM ml.training_window WHERE ds >= CURRENT_DATE - 10 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_3), 0) AS f_3 FROM ml.training_window WHERE ds >= DATEADD(day, -10, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_4", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_4)) AS f_4 FROM ml.training_window WHERE ds >= CURRENT_DATE - 11 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_4), 0) AS f_4 FROM ml.training_window WHERE ds >= DATEADD(day, -11, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_5", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_5)) AS f_5 FROM ml.training_window WHERE ds >= CURRENT_DATE - 12 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_5), 0) AS f_5 FROM ml.training_window WHERE ds >= DATEADD(day, -12, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_6", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_6)) AS f_6 FROM ml.training_window WHERE ds >= CURRENT_DATE - 13 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_6), 0) AS f_6 FROM ml.training_window WHERE ds >= DATEADD(day, -13, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_7", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_7)) AS f_7 FROM ml.training_window WHERE ds >= CURRENT_DATE - 14 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_7), 0) AS f_7 FROM ml.training_window WHERE ds >= DATEADD(day, -14, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_8", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_8)) AS f_8 FROM ml.training_window WHERE ds >= CURRENT_DATE - 15 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_8), 0) AS f_8 FROM ml.training_window WHERE ds >= DATEADD(day, -15, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_9", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_9)) AS f_9 FROM ml.training_window WHERE ds >= CURRENT_DATE - 16 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_9), 0) AS f_9 FROM ml.training_window WHERE ds >= DATEADD(day, -16, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_10", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_10)) AS f_10 FROM ml.training_window WHERE ds >= CURRENT_DATE - 17 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_10), 0) AS f_10 FROM ml.training_window WHERE ds >= DATEADD(day, -17, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_11", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_11)) AS f_11 FROM ml.training_window WHERE ds >= CURRENT_DATE - 18 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_11), 0) AS f_11 FROM ml.training_window WHERE ds >= DATEADD(day, -18, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_12", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_12)) AS f_12 FROM ml.training_window WHERE ds >= CURRENT_DATE - 19 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_12), 0) AS f_12 FROM ml.training_window WHERE ds >= DATEADD(day, -19, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_13", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_13)) AS f_13 FROM ml.training_window WHERE ds >= CURRENT_DATE - 20 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_13), 0) AS f_13 FROM ml.training_window WHERE ds >= DATEADD(day, -20, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_14", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_14)) AS f_14 FROM ml.training_window WHERE ds >= CURRENT_DATE - 21 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_14), 0) AS f_14 FROM ml.training_window WHERE ds >= DATEADD(day, -21, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_15", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_15)) AS f_15 FROM ml.training_window WHERE ds >= CURRENT_DATE - 22 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_15), 0) AS f_15 FROM ml.training_window WHERE ds >= DATEADD(day, -22, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_16", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_16)) AS f_16 FROM ml.training_window WHERE ds >= CURRENT_DATE - 23 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_16), 0) AS f_16 FROM ml.training_window WHERE ds >= DATEADD(day, -23, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_17", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_17)) AS f_17 FROM ml.training_window WHERE ds >= CURRENT_DATE - 24 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_17), 0) AS f_17 FROM ml.training_window WHERE ds >= DATEADD(day, -24, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_18", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_18)) AS f_18 FROM ml.training_window WHERE ds >= CURRENT_DATE - 25 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_18), 0) AS f_18 FROM ml.training_window WHERE ds >= DATEADD(day, -25, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_19", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_19)) AS f_19 FROM ml.training_window WHERE ds >= CURRENT_DATE - 26 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_19), 0) AS f_19 FROM ml.training_window WHERE ds >= DATEADD(day, -26, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_20", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_20)) AS f_20 FROM ml.training_window WHERE ds >= CURRENT_DATE - 27 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_20), 0) AS f_20 FROM ml.training_window WHERE ds >= DATEADD(day, -27, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_21", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_21)) AS f_21 FROM ml.training_window WHERE ds >= CURRENT_DATE - 28 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_21), 0) AS f_21 FROM ml.training_window WHERE ds >= DATEADD(day, -28, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_22", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_22)) AS f_22 FROM ml.training_window WHERE ds >= CURRENT_DATE - 29 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_22), 0) AS f_22 FROM ml.training_window WHERE ds >= DATEADD(day, -29, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_23", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_23)) AS f_23 FROM ml.training_window WHERE ds >= CURRENT_DATE - 30 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_23), 0) AS f_23 FROM ml.training_window WHERE ds >= DATEADD(day, -30, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_24", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_24)) AS f_24 FROM ml.training_window WHERE ds >= CURRENT_DATE - 31 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_24), 0) AS f_24 FROM ml.training_window WHERE ds >= DATEADD(day, -31, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_25", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_25)) AS f_25 FROM ml.training_window WHERE ds >= CURRENT_DATE - 32 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_25), 0) AS f_25 FROM ml.training_window WHERE ds >= DATEADD(day, -32, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_26", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_26)) AS f_26 FROM ml.training_window WHERE ds >= CURRENT_DATE - 33 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_26), 0) AS f_26 FROM ml.training_window WHERE ds >= DATEADD(day, -33, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_27", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_27)) AS f_27 FROM ml.training_window WHERE ds >= CURRENT_DATE - 34 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_27), 0) AS f_27 FROM ml.training_window WHERE ds >= DATEADD(day, -34, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_28", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_28)) AS f_28 FROM ml.training_window WHERE ds >= CURRENT_DATE - 35 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_28), 0) AS f_28 FROM ml.training_window WHERE ds >= DATEADD(day, -35, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_29", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_29)) AS f_29 FROM ml.training_window WHERE ds >= CURRENT_DATE - 36 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_29), 0) AS f_29 FROM ml.training_window WHERE ds >= DATEADD(day, -36, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_30", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_30)) AS f_30 FROM ml.training_window WHERE ds >= CURRENT_DATE - 37 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_30), 0) AS f_30 FROM ml.training_window WHERE ds >= DATEADD(day, -37, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_31", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_31)) AS f_31 FROM ml.training_window WHERE ds >= CURRENT_DATE - 38 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_31), 0) AS f_31 FROM ml.training_window WHERE ds >= DATEADD(day, -38, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_32", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_32)) AS f_32 FROM ml.training_window WHERE ds >= CURRENT_DATE - 39 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_32), 0) AS f_32 FROM ml.training_window WHERE ds >= DATEADD(day, -39, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_33", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_33)) AS f_33 FROM ml.training_window WHERE ds >= CURRENT_DATE - 40 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_33), 0) AS f_33 FROM ml.training_window WHERE ds >= DATEADD(day, -40, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_34", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_34)) AS f_34 FROM ml.training_window WHERE ds >= CURRENT_DATE - 41 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_34), 0) AS f_34 FROM ml.training_window WHERE ds >= DATEADD(day, -41, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_35", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_35)) AS f_35 FROM ml.training_window WHERE ds >= CURRENT_DATE - 42 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_35), 0) AS f_35 FROM ml.training_window WHERE ds >= DATEADD(day, -42, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_36", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_36)) AS f_36 FROM ml.training_window WHERE ds >= CURRENT_DATE - 43 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_36), 0) AS f_36 FROM ml.training_window WHERE ds >= DATEADD(day, -43, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_37", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_37)) AS f_37 FROM ml.training_window WHERE ds >= CURRENT_DATE - 44 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_37), 0) AS f_37 FROM ml.training_window WHERE ds >= DATEADD(day, -44, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_38", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_38)) AS f_38 FROM ml.training_window WHERE ds >= CURRENT_DATE - 45 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_38), 0) AS f_38 FROM ml.training_window WHERE ds >= DATEADD(day, -45, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_39", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_39)) AS f_39 FROM ml.training_window WHERE ds >= CURRENT_DATE - 46 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_39), 0) AS f_39 FROM ml.training_window WHERE ds >= DATEADD(day, -46, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_40", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_40)) AS f_40 FROM ml.training_window WHERE ds >= CURRENT_DATE - 47 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_40), 0) AS f_40 FROM ml.training_window WHERE ds >= DATEADD(day, -47, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_41", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_41)) AS f_41 FROM ml.training_window WHERE ds >= CURRENT_DATE - 48 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_41), 0) AS f_41 FROM ml.training_window WHERE ds >= DATEADD(day, -48, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_42", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_42)) AS f_42 FROM ml.training_window WHERE ds >= CURRENT_DATE - 49 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_42), 0) AS f_42 FROM ml.training_window WHERE ds >= DATEADD(day, -49, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_43", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_43)) AS f_43 FROM ml.training_window WHERE ds >= CURRENT_DATE - 50 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_43), 0) AS f_43 FROM ml.training_window WHERE ds >= DATEADD(day, -50, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_44", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_44)) AS f_44 FROM ml.training_window WHERE ds >= CURRENT_DATE - 51 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_44), 0) AS f_44 FROM ml.training_window WHERE ds >= DATEADD(day, -51, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_45", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_45)) AS f_45 FROM ml.training_window WHERE ds >= CURRENT_DATE - 52 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_45), 0) AS f_45 FROM ml.training_window WHERE ds >= DATEADD(day, -52, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_46", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_46)) AS f_46 FROM ml.training_window WHERE ds >= CURRENT_DATE - 53 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_46), 0) AS f_46 FROM ml.training_window WHERE ds >= DATEADD(day, -53, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_47", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_47)) AS f_47 FROM ml.training_window WHERE ds >= CURRENT_DATE - 54 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_47), 0) AS f_47 FROM ml.training_window WHERE ds >= DATEADD(day, -54, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_48", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_48)) AS f_48 FROM ml.training_window WHERE ds >= CURRENT_DATE - 55 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_48), 0) AS f_48 FROM ml.training_window WHERE ds >= DATEADD(day, -55, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_49", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_49)) AS f_49 FROM ml.training_window WHERE ds >= CURRENT_DATE - 56 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_49), 0) AS f_49 FROM ml.training_window WHERE ds >= DATEADD(day, -56, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ml_feature_50", "category": "ml_feature", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT entity_id, ZEROIFNULL(AVG(feature_50)) AS f_50 FROM ml.training_window WHERE ds >= CURRENT_DATE - 57 GROUP BY 1", "target_sql": "SELECT entity_id, COALESCE(AVG(feature_50), 0) AS f_50 FROM ml.training_window WHERE ds >= DATEADD(day, -57, CURRENT_DATE) GROUP BY 1", "notes": "ML feature window SQL"}
{"id": "ai_codegen_1", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_1), NVL(flag_1, 0) FROM ml.inference_logs WHERE run_id = 1", "target_sql": "SELECT COALESCE(score_1, 0), COALESCE(flag_1, 0) FROM ml.inference_logs WHERE run_id = 1", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_2", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_2), NVL(flag_2, 0) FROM ml.inference_logs WHERE run_id = 2", "target_sql": "SELECT COALESCE(score_2, 0), COALESCE(flag_2, 0) FROM ml.inference_logs WHERE run_id = 2", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_3", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_3), NVL(flag_3, 0) FROM ml.inference_logs WHERE run_id = 3", "target_sql": "SELECT COALESCE(score_3, 0), COALESCE(flag_3, 0) FROM ml.inference_logs WHERE run_id = 3", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_4", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_4), NVL(flag_4, 0) FROM ml.inference_logs WHERE run_id = 4", "target_sql": "SELECT COALESCE(score_4, 0), COALESCE(flag_4, 0) FROM ml.inference_logs WHERE run_id = 4", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_5", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_5), NVL(flag_5, 0) FROM ml.inference_logs WHERE run_id = 5", "target_sql": "SELECT COALESCE(score_5, 0), COALESCE(flag_5, 0) FROM ml.inference_logs WHERE run_id = 5", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_6", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_6), NVL(flag_6, 0) FROM ml.inference_logs WHERE run_id = 6", "target_sql": "SELECT COALESCE(score_6, 0), COALESCE(flag_6, 0) FROM ml.inference_logs WHERE run_id = 6", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_7", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_7), NVL(flag_7, 0) FROM ml.inference_logs WHERE run_id = 7", "target_sql": "SELECT COALESCE(score_7, 0), COALESCE(flag_7, 0) FROM ml.inference_logs WHERE run_id = 7", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_8", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_8), NVL(flag_8, 0) FROM ml.inference_logs WHERE run_id = 8", "target_sql": "SELECT COALESCE(score_8, 0), COALESCE(flag_8, 0) FROM ml.inference_logs WHERE run_id = 8", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_9", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_9), NVL(flag_9, 0) FROM ml.inference_logs WHERE run_id = 9", "target_sql": "SELECT COALESCE(score_9, 0), COALESCE(flag_9, 0) FROM ml.inference_logs WHERE run_id = 9", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_10", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_10), NVL(flag_10, 0) FROM ml.inference_logs WHERE run_id = 10", "target_sql": "SELECT COALESCE(score_10, 0), COALESCE(flag_10, 0) FROM ml.inference_logs WHERE run_id = 10", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_11", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_11), NVL(flag_11, 0) FROM ml.inference_logs WHERE run_id = 11", "target_sql": "SELECT COALESCE(score_11, 0), COALESCE(flag_11, 0) FROM ml.inference_logs WHERE run_id = 11", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_12", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_12), NVL(flag_12, 0) FROM ml.inference_logs WHERE run_id = 12", "target_sql": "SELECT COALESCE(score_12, 0), COALESCE(flag_12, 0) FROM ml.inference_logs WHERE run_id = 12", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_13", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_13), NVL(flag_13, 0) FROM ml.inference_logs WHERE run_id = 13", "target_sql": "SELECT COALESCE(score_13, 0), COALESCE(flag_13, 0) FROM ml.inference_logs WHERE run_id = 13", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_14", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_14), NVL(flag_14, 0) FROM ml.inference_logs WHERE run_id = 14", "target_sql": "SELECT COALESCE(score_14, 0), COALESCE(flag_14, 0) FROM ml.inference_logs WHERE run_id = 14", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_15", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_15), NVL(flag_15, 0) FROM ml.inference_logs WHERE run_id = 15", "target_sql": "SELECT COALESCE(score_15, 0), COALESCE(flag_15, 0) FROM ml.inference_logs WHERE run_id = 15", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_16", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_16), NVL(flag_16, 0) FROM ml.inference_logs WHERE run_id = 16", "target_sql": "SELECT COALESCE(score_16, 0), COALESCE(flag_16, 0) FROM ml.inference_logs WHERE run_id = 16", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_17", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_17), NVL(flag_17, 0) FROM ml.inference_logs WHERE run_id = 17", "target_sql": "SELECT COALESCE(score_17, 0), COALESCE(flag_17, 0) FROM ml.inference_logs WHERE run_id = 17", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_18", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_18), NVL(flag_18, 0) FROM ml.inference_logs WHERE run_id = 18", "target_sql": "SELECT COALESCE(score_18, 0), COALESCE(flag_18, 0) FROM ml.inference_logs WHERE run_id = 18", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_19", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_19), NVL(flag_19, 0) FROM ml.inference_logs WHERE run_id = 19", "target_sql": "SELECT COALESCE(score_19, 0), COALESCE(flag_19, 0) FROM ml.inference_logs WHERE run_id = 19", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_20", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_20), NVL(flag_20, 0) FROM ml.inference_logs WHERE run_id = 20", "target_sql": "SELECT COALESCE(score_20, 0), COALESCE(flag_20, 0) FROM ml.inference_logs WHERE run_id = 20", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_21", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_21), NVL(flag_21, 0) FROM ml.inference_logs WHERE run_id = 21", "target_sql": "SELECT COALESCE(score_21, 0), COALESCE(flag_21, 0) FROM ml.inference_logs WHERE run_id = 21", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_22", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_22), NVL(flag_22, 0) FROM ml.inference_logs WHERE run_id = 22", "target_sql": "SELECT COALESCE(score_22, 0), COALESCE(flag_22, 0) FROM ml.inference_logs WHERE run_id = 22", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_23", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_23), NVL(flag_23, 0) FROM ml.inference_logs WHERE run_id = 23", "target_sql": "SELECT COALESCE(score_23, 0), COALESCE(flag_23, 0) FROM ml.inference_logs WHERE run_id = 23", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_24", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_24), NVL(flag_24, 0) FROM ml.inference_logs WHERE run_id = 24", "target_sql": "SELECT COALESCE(score_24, 0), COALESCE(flag_24, 0) FROM ml.inference_logs WHERE run_id = 24", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_25", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_25), NVL(flag_25, 0) FROM ml.inference_logs WHERE run_id = 25", "target_sql": "SELECT COALESCE(score_25, 0), COALESCE(flag_25, 0) FROM ml.inference_logs WHERE run_id = 25", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_26", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_26), NVL(flag_26, 0) FROM ml.inference_logs WHERE run_id = 26", "target_sql": "SELECT COALESCE(score_26, 0), COALESCE(flag_26, 0) FROM ml.inference_logs WHERE run_id = 26", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_27", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_27), NVL(flag_27, 0) FROM ml.inference_logs WHERE run_id = 27", "target_sql": "SELECT COALESCE(score_27, 0), COALESCE(flag_27, 0) FROM ml.inference_logs WHERE run_id = 27", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_28", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_28), NVL(flag_28, 0) FROM ml.inference_logs WHERE run_id = 28", "target_sql": "SELECT COALESCE(score_28, 0), COALESCE(flag_28, 0) FROM ml.inference_logs WHERE run_id = 28", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_29", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_29), NVL(flag_29, 0) FROM ml.inference_logs WHERE run_id = 29", "target_sql": "SELECT COALESCE(score_29, 0), COALESCE(flag_29, 0) FROM ml.inference_logs WHERE run_id = 29", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_30", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_30), NVL(flag_30, 0) FROM ml.inference_logs WHERE run_id = 30", "target_sql": "SELECT COALESCE(score_30, 0), COALESCE(flag_30, 0) FROM ml.inference_logs WHERE run_id = 30", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_31", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_31), NVL(flag_31, 0) FROM ml.inference_logs WHERE run_id = 31", "target_sql": "SELECT COALESCE(score_31, 0), COALESCE(flag_31, 0) FROM ml.inference_logs WHERE run_id = 31", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_32", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_32), NVL(flag_32, 0) FROM ml.inference_logs WHERE run_id = 32", "target_sql": "SELECT COALESCE(score_32, 0), COALESCE(flag_32, 0) FROM ml.inference_logs WHERE run_id = 32", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_33", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_33), NVL(flag_33, 0) FROM ml.inference_logs WHERE run_id = 33", "target_sql": "SELECT COALESCE(score_33, 0), COALESCE(flag_33, 0) FROM ml.inference_logs WHERE run_id = 33", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_34", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_34), NVL(flag_34, 0) FROM ml.inference_logs WHERE run_id = 34", "target_sql": "SELECT COALESCE(score_34, 0), COALESCE(flag_34, 0) FROM ml.inference_logs WHERE run_id = 34", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_35", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_35), NVL(flag_35, 0) FROM ml.inference_logs WHERE run_id = 35", "target_sql": "SELECT COALESCE(score_35, 0), COALESCE(flag_35, 0) FROM ml.inference_logs WHERE run_id = 35", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_36", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_36), NVL(flag_36, 0) FROM ml.inference_logs WHERE run_id = 36", "target_sql": "SELECT COALESCE(score_36, 0), COALESCE(flag_36, 0) FROM ml.inference_logs WHERE run_id = 36", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_37", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_37), NVL(flag_37, 0) FROM ml.inference_logs WHERE run_id = 37", "target_sql": "SELECT COALESCE(score_37, 0), COALESCE(flag_37, 0) FROM ml.inference_logs WHERE run_id = 37", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_38", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_38), NVL(flag_38, 0) FROM ml.inference_logs WHERE run_id = 38", "target_sql": "SELECT COALESCE(score_38, 0), COALESCE(flag_38, 0) FROM ml.inference_logs WHERE run_id = 38", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_39", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_39), NVL(flag_39, 0) FROM ml.inference_logs WHERE run_id = 39", "target_sql": "SELECT COALESCE(score_39, 0), COALESCE(flag_39, 0) FROM ml.inference_logs WHERE run_id = 39", "notes": "AI inference-log SQL pair"}
{"id": "ai_codegen_40", "category": "function", "source_dialect": "vertica", "target_dialect": "snowflake", "source_sql": "SELECT ZEROIFNULL(score_40), NVL(flag_40, 0) FROM ml.inference_logs WHERE run_id = 40", "target_sql": "SELECT COALESCE(score_40, 0), COALESCE(flag_40, 0) FROM ml.inference_logs WHERE run_id = 40", "notes": "AI inference-log SQL pair"}