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import datasets
import pandas as pd
import json
_DESCRIPTION = """
BIRD SQL Dataset with complete database content.
Total rows: 366,787,649
Total chunks: 3660
"""
class BirdSQLDatabase(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.0.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="database_content", description="Complete database content"),
datasets.BuilderConfig(name="table_metadata", description="Table metadata"),
]
DEFAULT_CONFIG_NAME = "database_content"
def _info(self):
if self.config.name == "database_content":
features = datasets.Features({
"db_id": datasets.Value("string"),
"table_name": datasets.Value("string"),
"row_index": datasets.Value("int64"),
"row_data": datasets.Value("string"),
"split": datasets.Value("string")
})
else: # table_metadata
features = datasets.Features({
"db_id": datasets.Value("string"),
"table_name": datasets.Value("string"),
"columns": datasets.Value("string"),
"column_types": datasets.Value("string"),
"primary_keys": datasets.Value("string"),
"total_rows": datasets.Value("int64"),
"split": datasets.Value("string")
})
return datasets.DatasetInfo(description=_DESCRIPTION, features=features)
def _split_generators(self, dl_manager):
if self.config.name == "database_content":
manifest_file = dl_manager.download("database_content_manifest.json")
with open(manifest_file) as f:
manifest = json.load(f)
chunk_files = []
for chunk_name in manifest["files"]:
chunk_file = dl_manager.download(chunk_name)
chunk_files.append(chunk_file)
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"chunk_files": chunk_files})]
else:
metadata_file = dl_manager.download("table_metadata.parquet")
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": metadata_file})]
def _generate_examples(self, filepath=None, chunk_files=None):
if self.config.name == "database_content":
idx = 0
for chunk_file in chunk_files:
df = pd.read_parquet(chunk_file)
for _, row in df.iterrows():
yield idx, {
"db_id": row["db_id"],
"table_name": row["table_name"],
"row_index": row["row_index"],
"row_data": row["row_data"],
"split": row["split"]
}
idx += 1
else:
df = pd.read_parquet(filepath)
for idx, row in df.iterrows():
yield idx, {
"db_id": row["db_id"],
"table_name": row["table_name"],
"columns": row["columns"],
"column_types": row["column_types"],
"primary_keys": row["primary_keys"],
"total_rows": row["total_rows"],
"split": row["split"]
}
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