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fix(breadbox): workaround for memory problem reading parquet files. #122

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Merged
merged 3 commits into from
Nov 6, 2024
Merged

fix(breadbox): workaround for memory problem reading parquet files. #122

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c20e4cb
workaround for memory problem reading parquet files.
pgm Nov 5, 2024
c8b4f5c
Switched to using fastparquet
pgm Nov 5, 2024
fa48279
fixed type check error
pgm Nov 6, 2024
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7 changes: 5 additions & 2 deletions breadbox/breadbox/io/data_validation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -177,8 +177,11 @@ def _validate_data_value_type(
return df.astype(np.float64)


def _read_parquet(file: BinaryIO, value_type: ValueType) -> pd.DataFrame:
df = pd.read_parquet(file, use_nullable_dtypes=True) # pyright: ignore
def _read_parquet(file, value_type: ValueType) -> pd.DataFrame:
# It appears that pd.read_parquet() by default uses pyarrow. However, for some reason
# when reading a file with 20k columns, the memory usage balloons
# to > 30GB and would take down breadbox. However, using fastparquet seems to avoid this problem.
df = pd.read_parquet(file, engine="fastparquet").convert_dtypes()

# the first column will be treated as the index. Make sure it's of type string
df[df.columns[0]] = df[df.columns[0]].astype("string")
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