Spenserrrr commented on code in PR #58751:
URL: https://github.com/apache/spark/pull/58751#discussion_r4010234767
##########
python/pyspark/sql/conversion.py:
##########
@@ -410,105 +401,159 @@ def convert_column(
assign_cols_by_name=assign_cols_by_name,
int_to_decimal_coercion_enabled=int_to_decimal_coercion_enabled,
ignore_unexpected_complex_type_values=ignore_unexpected_complex_type_values,
- is_legacy=is_legacy,
+ use_legacy_error_handling=use_legacy_error_handling,
)
# Wrap the nested RecordBatch as a single StructArray column
- return
ArrowBatchTransformer.wrap_struct(nested_batch).column(0)
+
converted.append(ArrowBatchTransformer.wrap_struct(nested_batch).column(0))
+ else:
Review Comment:
Added an explicit type check with PySparkTypeError (UDF_RETURN_TYPE). Some
scalar pandas UDF paths currently check the result’s length without requiring a
Series, so an invalid return such as a list can reach here. I chose an
exception rather than an assertion because this can be invalid user input, not
just an internal programming error.
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