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Text-to-SQL Data

This directory contains the data for the Text-to-SQL benchmark, supporting Spider2-lite and Bird datasets.

Structure

data/text2sql/
β”œβ”€β”€ README.md
β”œβ”€β”€ spider2-lite/
β”‚   β”œβ”€β”€ spider2-lite.jsonl                          # Spider2-lite questions (546 instances)
β”‚   β”œβ”€β”€ golden_lite_spider_total.json               # Gold labels for evaluation
β”‚   β”œβ”€β”€ sqlite/                                     # Local SQLite databases
β”‚   β”‚   └── <DB_Name>/
β”‚   β”‚       β”œβ”€β”€ <DB_Name>.sqlite                    # SQLite database file
β”‚   β”‚       └── <DB_Name>_db_summary.json           # Auto-generated schema summary
β”‚   β”œβ”€β”€ bigquery/                                   # BigQuery dataset schemas
β”‚   β”‚   └── <dataset_group>/
β”‚   β”‚       └── <dataset_group>_bigquery_summary.json
β”‚   └── snowflake/                                  # Snowflake database schemas
β”‚       └── <DATABASE>/
β”‚           └── <DATABASE>_db_summary.json
└── bird/
    β”œβ”€β”€ bird.jsonl                                  # Bird questions (129 instances)
    └── databases/
        └── <DB_Name>/
            β”œβ”€β”€ <DB_Name>.sqlite
            └── <DB_Name>_db_summary.json

Included Example Databases

Backend Benchmark Database Description
SQLite Spider2-lite Pagila DVD rental store (16 tables)
SQLite Bird superhero Superhero database (10 tables)
BigQuery Spider2-lite san_francisco SF city data: bikeshare, crime, film locations, fire dept, street trees (8 tables, 118 columns, schema only)
Snowflake Spider2-lite AUSTIN Austin 311 service requests (schema only)

Adding a New SQLite Database

  1. Place the .sqlite file:
    data/text2sql/spider2-lite/sqlite/MyDB/MyDB.sqlite
    
  2. The schema summary is auto-generated on first run, or generate manually:
    python -m src.indexing.extract_db_summary \
        --db-path data/text2sql/spider2-lite/sqlite/MyDB/MyDB.sqlite
    

Adding a BigQuery Database

  1. Generate the summary using the BigQuery extractor:
    python -m src.indexing.extract_db_summary_bigquery \
        --datasets project_id.dataset_id \
        --output-dir data/text2sql/spider2-lite/bigquery/my_dataset/
    

Adding a Snowflake Database

  1. Generate the summary using the Snowflake extractor:
    python -m src.indexing.extract_db_summary_snowflake \
        --databases MY_DATABASE \
        --output-dir data/text2sql/spider2-lite/snowflake/MY_DATABASE/
    

Full Spider2-lite Data

To run the full benchmark, clone Spider2 and copy the databases into spider2-lite/sqlite/.