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[SPARK-55059][PYTHON] Remove empty table workaround in toPandas #53824

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[SPARK-55059][PYTHON] Remove empty table workaround in toPandas #53824

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12 changes: 2 additions & 10 deletions python/pyspark/sql/pandas/conversion.py
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Original file line number Diff line number Diff line change
Expand Up @@ -254,16 +254,8 @@ def _convert_arrow_table_to_pandas(
error_on_duplicated_field_names = True
struct_handling_mode = "dict"

# SPARK-51112: If the table is empty, we avoid using pyarrow to_pandas to create the
# DataFrame, as it may fail with a segmentation fault.
if arrow_table.num_rows == 0:
# For empty tables, create empty Series to preserve dtypes
column_data = (
pd.Series([], name=temp_col_names[i], dtype="object") for i in range(len(schema.fields))
)
else:
# For non-empty tables, convert arrow columns directly
column_data = (arrow_col.to_pandas(**pandas_options) for arrow_col in arrow_table.columns)
# Convert arrow columns to pandas Series
column_data = (arrow_col.to_pandas(**pandas_options) for arrow_col in arrow_table.columns)

# Apply Spark-specific type converters to each column
pdf = pd.concat(
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