Yicong-Huang commented on code in PR #58751:
URL: https://github.com/apache/spark/pull/58751#discussion_r4010967174
##########
python/pyspark/sql/conversion.py:
##########
@@ -410,105 +402,168 @@ 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))
+ elif isinstance(col, pd.Series):
+ converted.append(
+ cls._convert_column(
+ col,
+ field,
+ timezone=timezone,
+ safecheck=safecheck,
+ arrow_cast=arrow_cast,
+ prefers_large_types=prefers_large_types,
+
int_to_decimal_coercion_enabled=int_to_decimal_coercion_enabled,
+
ignore_unexpected_complex_type_values=ignore_unexpected_complex_type_values,
+ use_legacy_error_handling=use_legacy_error_handling,
+ )
+ )
+ else:
+ raise PySparkTypeError(
+ errorClass="UDF_RETURN_TYPE",
Review Comment:
This is kind of a historical issue in PySpark, many error classes are not
picked/designed carefully. I also wanted to revise the error class, that to be
said, I’d suggest doing that separately in a new PR if possible, to maintain
no behavioral change for this PR.
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