/
parquet.py
79 lines (66 loc) 路 3.6 KB
/
parquet.py
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import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
logger = datasets.utils.logging.get_logger(__name__)
@dataclass
class ParquetConfig(datasets.BuilderConfig):
"""BuilderConfig for Parquet."""
batch_size: int = 10_000
columns: Optional[List[str]] = None
features: Optional[datasets.Features] = None
class Parquet(datasets.ArrowBasedBuilder):
BUILDER_CONFIG_CLASS = ParquetConfig
def _info(self):
return datasets.DatasetInfo(features=self.config.features)
def _split_generators(self, dl_manager):
"""We handle string, list and dicts in datafiles"""
if not self.config.data_files:
raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}")
data_files = dl_manager.download_and_extract(self.config.data_files)
if isinstance(data_files, (str, list, tuple)):
files = data_files
if isinstance(files, str):
files = [files]
# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
files = [dl_manager.iter_files(file) for file in files]
return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"files": files})]
splits = []
for split_name, files in data_files.items():
if isinstance(files, str):
files = [files]
# Use `dl_manager.iter_files` to skip hidden files in an extracted archive
files = [dl_manager.iter_files(file) for file in files]
splits.append(datasets.SplitGenerator(name=split_name, gen_kwargs={"files": files}))
return splits
def _cast_table(self, pa_table: pa.Table) -> pa.Table:
if self.config.features is not None:
# more expensive cast to support nested features with keys in a different order
# allows str <-> int/float or str to Audio for example
pa_table = table_cast(pa_table, self.config.features.arrow_schema)
return pa_table
def _generate_tables(self, files):
schema = self.config.features.arrow_schema if self.config.features is not None else None
if self.config.features is not None and self.config.columns is not None:
if sorted(field.name for field in schema) != sorted(self.config.columns):
raise ValueError(
f"Tried to load parquet data with columns '{self.config.columns}' with mismatching features '{self.config.features}'"
)
for file_idx, file in enumerate(itertools.chain.from_iterable(files)):
with open(file, "rb") as f:
parquet_file = pq.ParquetFile(f)
try:
for batch_idx, record_batch in enumerate(
parquet_file.iter_batches(batch_size=self.config.batch_size, columns=self.config.columns)
):
pa_table = pa.Table.from_batches([record_batch])
# Uncomment for debugging (will print the Arrow table size and elements)
# logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
# logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table)
except ValueError as e:
logger.error(f"Failed to read file '{file}' with error {type(e)}: {e}")
raise