| --- |
| license: cc-by-sa-4.0 |
| task_categories: |
| - text2text-generation |
| - table-question-answering |
| language: |
| - en |
| - sql |
| tags: |
| - text-to-sql |
| - sql |
| - spider |
| - flan-t5 |
| - seq2seq |
| - nlp |
| size_categories: |
| - 1K<n<10K |
| --- |
| |
| # SPIDER Text-to-SQL — Easy Access Version |
|
|
| A clean, HuggingFace-native version of the [SPIDER](https://yale-seas.yale.edu/spider/) Text-to-SQL benchmark. The original SPIDER dataset requires manually downloading a ZIP file from the Spider website. This version makes it instantly accessible via `load_dataset`. |
|
|
| ## What's Included |
|
|
| Each row contains the question, gold SQL, the database identifier, and a pre-parsed compact schema string — everything needed to train or evaluate a Text-to-SQL model without any additional preprocessing. |
|
|
| | Column | Description | |
| |---|---| |
| | `db_id` | Database identifier (e.g. `"concert_singer"`) | |
| | `question` | Natural language question | |
| | `query` | Gold standard SQL answer | |
| | `db_schema` | Compact schema: `"table: col (type), col (type) | table2: ..."` | |
| | `question_toks` | Tokenized question words (list of strings) | |
|
|
| ## Splits |
|
|
| | Split | Source file | Examples | |
| |---|---|---| |
| | train | `train_spider.json` | 7,000 | |
| | test | `train_others.json` | 1,034 | |
|
|
| > **Note**: Following standard SPIDER practice, `train_others.json` is used as the held-out evaluation set. The original SPIDER test set is withheld for the official leaderboard. |
| |
| ## Usage |
| |
| ```python |
| from datasets import load_dataset |
|
|
| dataset = load_dataset("YOUR_USERNAME/spider-text2sql") |
|
|
| train = dataset["train"] |
| test = dataset["test"] |
|
|
| # Access fields |
| example = train[0] |
| print(example["question"]) # "How many heads of the departments are older than 56?" |
| print(example["query"]) # "SELECT count(*) FROM head WHERE age > 56" |
| print(example["db_id"]) # "department_management" |
| print(example["db_schema"]) # "department: Department_ID (number), ... | head: ..." |
| ``` |
| |
| ## Schema Format |
| |
| The `db_schema` column uses a compact linear format widely used in the Text-to-SQL literature: |
| |
| ``` |
| table1: col1 (type), col2 (type), col3 (type) | table2: col4 (type), col5 (type) |
| ``` |
| |
| This format is: |
| - Human-readable and model-friendly |
| - Fits within typical 512-token input limits for most seq2seq models |
| - Derived directly from the official SPIDER `tables.json` |
| |
| ## Fine-tuning Example (Flan-T5 prompt format) |
| |
| This dataset pairs naturally with prompt-based fine-tuning: |
| |
| ```python |
| def build_prompt(example): |
| return ( |
| f"Translate to SQL: {example['question']}\n" |
| f"Database schema:\n{example['db_schema']}" |
| ) |
| |
| # example["query"] is the target output |
| ``` |
| |
| ## Difference from Original SPIDER |
| |
| | | Original SPIDER | This Dataset | |
| |---|---|---| |
| | Download method | Manual ZIP from website | `load_dataset(...)` ✅ | |
| | Schema included | Separate `tables.json` | ✅ Pre-joined per example | |
| | Complex `sql` dict | ✅ Included | ❌ Omitted (noisy for most use cases) | |
| | `query_toks_no_value` | ✅ Included | ❌ Omitted | |
| | Ready to train | Requires preprocessing | ✅ Yes | |
| |
| ## Source & License |
| |
| - Original dataset: [SPIDER (Yu et al., 2018)](https://yale-seas.yale.edu/spider/) |
| - License: **Creative Commons Attribution-ShareAlike 4.0 (CC BY-SA 4.0)** |
| - This derived dataset is released under the same license. |
| |
| ## Citation |
| |
| ```bibtex |
| @inproceedings{yu-etal-2018-spider, |
| title = "{S}pider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-{SQL} Task", |
| author = "Yu, Tao and others", |
| booktitle = "Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing", |
| year = "2018", |
| url = "https://aclanthology.org/D18-1425", |
| } |
| ``` |
| |
