tasks/offline-compute/MySQL/mysql_020_en/task.md

metadata

id: offline-compute_MySQL_mysql_020
name: Build Volume-Lift Candidate Ad List
category: offline-compute/MySQL
timeout_seconds: 1800
modality: pure-text
engine: mysql

Prompt

I need you to generate a MySQL script that builds a volume-lift candidate ad list, outputting to table internal_platform_db.dwm_union_raise_candidate_new_ads_hf_cand_mysql_020 with partition key p_partition='2026060905'.

Business Background and Objective: The ad volume-lift system needs to jointly filter qualifying ads from multiple dimensions (creative, ad group, ecology budget, advertiser, conversion link, volume-lift configuration, creative platform) to generate a candidate list for downstream consumption. This task requires multi-table JOINs, aggregation, window function ranking, and filtering across 7 input tables, ultimately writing to the output table.

Input Tables (full name + brief description):

• internal_platform_db.dim_creative_info_f_mysql_020 (creative information)
• internal_platform_db.dim_adgroup_info_f_mysql_020 (ad group information)
• internal_platform_db.dim_adgroup_ecology_budget_info_di_mysql_020 (ecology budget information)
• internal_platform_db.f_union_dim_advertiser_info_d_mysql_020 (advertiser information)
• internal_platform_db.t_daily_conv_link_tid_dimension_mysql_020 (conversion link dimension)
• internal_platform_db.dim_union_ad_raised_config_hf_mysql_020 (volume-lift configuration)
• internal_platform_db.dim_tbl_creative_f_mysql_020 (creative platform information)

(Please connect to the database and query to confirm the table structures and field semantics.)

Processing Rules:

1. Main table a (dim_creative_info_f): creative_id > 0, aggregate by creative_id taking MAX(adgroup_id), MAX(advertiser_id), MAX(landing_page_type)
2. Subquery e (dim_adgroup_info_f) INNER JOIN:
   • Filter adgroup_id > 0
   • Filter placement_group_id_list containing 15 or 136 (using the FIND_IN_SET function)
   • begin_time >= MIN(begintime) from the config table AND <= MAX(endtime), config table conditions: partition_time = 2026060905, strategyid > 0, 20260609 within the begintime-endtime range (use FROM_UNIXTIME to convert unix timestamps to date format yyyyMMdd for comparison)
   • Aggregate by adgroup_id taking MAX(product_id), MAX(optimization_goal), MAX(second_optimization_goal), MAX(deep_conversion_optimization_goal), MAX(marketing_target_id), MAX(begin_time), MAX(end_time), MAX(created_time), MAX(exploration_strategy_id), MAX(placement_group_id_list)
3. Subquery b (dim_adgroup_ecology_budget_info_di) LEFT JOIN: partition_time between 20260607–20260608, take the latest partition's ecology_level2_id per creative_id (using the ROW_NUMBER window function ranked by partition_time DESC, taking rn=1)
4. Subquery c (f_union_dim_advertiser_info_d) LEFT JOIN: partition_time between 20260607–20260608, first aggregate by advertiser_id + partition_time taking MAX(operation_industry_name) AS team, MAX(short_advertiser_name), then take the latest partition's team, short_advertiser_name per advertiser_id (ROW_NUMBER)
5. Subquery d (t_daily_conv_link_tid_dimension) LEFT JOIN: partition_time between 20260607–20260608, first aggregate by tid + partition_time taking MAX(landingpage_link_type), then take the latest partition's landingpage_link_type per tid (ROW_NUMBER), join condition a.creative_id = d.tid
6. Subquery f (dim_tbl_creative_f) LEFT JOIN: ftid > 0, aggregate by ftid taking MAX(fsmartdeliveryplatform) AS smart_delivery_platform, join condition a.creative_id = f.ftid
7. Final SELECT: partition_time = 2026060905, adgroup_id, COALESCE(advertiser_id, 0), COALESCE(product_id, ''), CONCAT(COALESCE(optimization_goal, 0), '_', COALESCE(second_optimization_goal, 0), '_', COALESCE(deep_conversion_optimization_goal, 0)) AS mix_goal, COALESCE(landing_page_type, ''), COALESCE(marketing_target_id, 0), COALESCE(ecology_level2_id, 0), COALESCE(team, ''), COALESCE(short_advertiser_name, ''), COALESCE(landingpage_link_type, ''), COALESCE(begin_time, 0), COALESCE(end_time, 0), COALESCE(created_time, 0), COALESCE(smart_delivery_platform, 0), COALESCE(exploration_strategy_id, 0), COALESCE(placement_group_id_list, '')

Output Requirements:

• Target table: internal_platform_db.dwm_union_raise_candidate_new_ads_hf_cand_mysql_020
• Output field order: partition_time, adgroup_id, advertiser_id, product_id, mix_goal, landing_page_type, marketing_target_id, ecology_level2_id, team, short_advertiser_name, landingpage_link_type, begin_time, end_time, created_time, smart_delivery_platform, exploration_strategy_id, placement_group_id_list, p_partition
• mix_goal is generated by concatenating three optimization goal fields with underscores; null values are replaced with defaults using COALESCE (0 for numeric, empty string for string)
• Final deduplication by GROUP BY on all non-partition_time fields
• p_partition is fixed as '2026060905'
• If the target table does not exist, first create it using standard MySQL InnoDB format, then write the data
• Use standard MySQL syntax; do not use Hive/Spark SQL dialects (e.g., INSERT OVERWRITE, ARRAY type, array_contains, concat_ws for arrays, and other Hive-specific functions are not supported)

Environment and Execution Notes:

• Your final output must be written to the file /tmp_workspace/result.py, not result.sql
• The local MySQL is running at localhost:3306, username root, password root123
• Use Python pymysql in result.py to execute the SQL (do not use the mysql command-line tool)
• The script must include complete table creation (if the target table does not exist) and data writing logic
• After writing result.py, you must execute python3 /tmp_workspace/result.py yourself to verify that it runs successfully and produces correct data