Yicong-Huang commented on code in PR #53045:
URL: https://github.com/apache/spark/pull/53045#discussion_r2532634980
##########
python/pyspark/sql/connect/client/core.py:
##########
@@ -1030,37 +1031,15 @@ def to_pandas(
error_on_duplicated_field_names = True
struct_in_pandas = "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 table.num_rows == 0:
- # For empty tables, create empty Series with converters to
preserve dtypes
- pdf = pd.concat(
- [
- _create_converter_to_pandas(
- field.dataType,
- field.nullable,
- timezone=timezone,
- struct_in_pandas=struct_in_pandas,
-
error_on_duplicated_field_names=error_on_duplicated_field_names,
- )(pd.Series([], name=temp_col_names[i],
dtype="object"))
- for i, field in enumerate(schema.fields)
- ],
- axis="columns",
- )
- else:
- pdf = pd.concat(
- [
- _create_converter_to_pandas(
- field.dataType,
- field.nullable,
- timezone=timezone,
- struct_in_pandas=struct_in_pandas,
-
error_on_duplicated_field_names=error_on_duplicated_field_names,
- )(arrow_col.to_pandas(**pandas_options))
- for arrow_col, field in zip(table.columns,
schema.fields)
- ],
- axis="columns",
- )
Review Comment:
yes after reading more, I moved more common logic into the helper function
to unify them. Thanks!
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