README.md

---
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](https://beaverbench.github.io) | 
[Github repository](https://github.com/beaverbench/beaver) |
[Paper](https://arxiv.org/abs/2409.02038)

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](https://huggingface.co/datasets/beaverbench/beaver-table/blob/main/beaver_db.zip).
A free MySQL installation is available [here](https://dev.mysql.com/downloads/mysql/).
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}
}
```