[SPARK-54316][PYTHON] Consolidate GroupPandasIterUDFSerializer with GroupPandasUDFSerializer #53043
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| safecheck, | ||
| assign_cols_by_name, | ||
| int_to_decimal_coercion_enabled, | ||
| use_iterator=False, |
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please keep in line with GroupArrowUDFSerializer, we should not add such use_iterator argument, this serializer always return iterator,
and then adjust the function wrappers, you can refer to wrap_grouped_map_arrow_udf and wrap_grouped_map_arrow_iter_udf
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rewrote to align with GroupArrowUDFSerializer.
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What changes were proposed in this pull request?
This PR consolidates
GroupPandasIterUDFSerializerwithGroupPandasUDFSerializerto eliminate code duplication and improve maintainability.Modified
GroupPandasUDFSerializer(python/pyspark/sql/pandas/serializers.py):use_iteratorparameter to support both regular and iterator modes_convert_batches_to_pandashelper methodload_stream()anddump_stream()methods to handle both modes with minimal branchingWhy are the changes needed?
When
Iterator[pandas.DataFrame]API was added togroupBy().applyInPandas()in SPARK-53614 (#52716), a newGroupPandasIterUDFSerializerclass was created. However, this class is nearly identical toGroupPandasUDFSerializer, differing only in whether batches are processed lazily (iterator mode) or all at once (regular mode).Does this PR introduce any user-facing change?
No.
How was this patch tested?
All existing tests pass without modification:
test_apply_in_pandas_iterator_*ApplyInPandasTestsWas this patch authored or co-authored using generative AI tooling?
Co-Generated-by: Cursor with Claude 4.5 Sonnet