ucalyptus/birdbench-duckdb

BirdBench Dataset in DuckDB format

BirdBench is a benchmark for text-to-SQL capabilities, now available in DuckDB format for improved performance and usability.

About BirdBench

BirdBench is a comprehensive benchmark dataset for evaluating text-to-SQL capabilities of language models. It features a diverse collection of databases spanning various domains including:

• —Business and finance
• —Entertainment and media
• —Sports and recreation
• —Health and medicine
• —Education
• —Travel and geography
• —And many more

Why DuckDB?

This repository contains the BirdBench dataset converted from SQLite to DuckDB format, which offers several advantages:

• —Performance: DuckDB is significantly faster for analytical queries
• —Integration: Better integration with Python data science tools
• —Features: Support for vectorized operations and advanced analytical functions
• —Compatibility: Works well in environments where SQLite might have limitations

Dataset Structure

The dataset maintains the original BirdBench structure, with both training and validation databases converted to DuckDB format:

• —/train - Contains training databases
• —/validation - Contains validation databases

Each database preserves the original schema and data from the SQLite version.

Usage

Loading a database

import duckdb

# Connect to a database
conn = duckdb.connect('path/to/database.duckdb')

# List tables
tables = conn.execute('SELECT name FROM sqlite_master WHERE type="table"').fetchall()
print(tables)

# Run a query
result = conn.execute('SELECT * FROM your_table LIMIT 5').fetchall()
print(result)