README.md

metadata

license: mit
configs:
  - config_name: default
    data_files:
      - split: dw
        path: data/dw-*
      - split: nova
        path: data/nova-*
      - split: neutron
        path: data/neutron-*
dataset_info:
  features:
    - name: db
      dtype: string
    - name: table_name
      dtype: string
    - name: column_names
      dtype: string
    - name: column_types
      dtype: string
    - name: example_rows
      dtype: string
    - name: example_columns
      dtype: string
  splits:
    - name: dw
      num_bytes: 157140
      num_examples: 97
    - name: nova
      num_bytes: 172217
      num_examples: 109
    - name: neutron
      num_bytes: 70285
      num_examples: 175
  download_size: 154931
  dataset_size: 399642

Dataset Card for beaver-table

Homepage and leaderboard | Github repository | Paper

Beaver is a holistic framework for evaluating performance on complex, private‑enterprise text‑to‑SQL tasks. This repository includes the full collection of tables. Each table contains:

• db: ID of the database the table belongs to
• table_name: name of the table in the database
• column_names: names of the columns in the table
• column_types: data types of the columns in the table
• example_rows: example rows of the table
• example_columns: example values for each column in the table

Getting started

We use MySQL as the execution engine for running SQL queries. You can download the anonymized MySQL dump here. A free MySQL installation is available here. After installing MySQL, import the dump files to your local MySQL using mysql -u root -p < xxx.sql.

from datasets import load_dataset
import json

domain = 'dw'
data = load_dataset('beaverbench/beaver-table')
json_fields = ['column_names', 'column_types', 'example_rows', 'example_columns']
for sample in data[domain]:
    sample = {k: (json.loads(v) if k in json_fields else v)  for k, v in sample.items()}
    print(json.dumps(sample, indent=2))

Citation

@article{chen2024beaver,
  title={BEAVER: an enterprise benchmark for text-to-sql},
  author={Chen, Peter Baile and Yang, Devin and Li, Weiyue and Wenz, Fabian and Zhang, Yi and Tatbul, Nesime and Cafarella, Michael and Demiralp, {\c{C}}a{\u{g}}atay and Stonebraker, Michael},
  journal={arXiv preprint arXiv:2409.02038},
  year={2024}
}