ueshin commented on a change in pull request #24177: [SPARK-27240][PYTHON] Use
pandas DataFrame for struct type argument in Scalar Pandas UDF.
URL: https://github.com/apache/spark/pull/24177#discussion_r268107198
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File path: python/pyspark/serializers.py
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@@ -378,6 +379,29 @@ class
ArrowStreamPandasUDFSerializer(ArrowStreamPandasSerializer):
Serializer used by Python worker to evaluate Pandas UDFs
"""
+ def __init__(self, timezone, safecheck, assign_cols_by_name,
df_for_struct=False):
+ super(ArrowStreamPandasUDFSerializer, self) \
+ .__init__(timezone, safecheck, assign_cols_by_name)
+ self._df_for_struct = df_for_struct
+
+ def arrow_to_pandas(self, arrow_column, data_type):
+ from pyspark.sql.types import StructType, \
+ _arrow_column_to_pandas, _check_dataframe_localize_timestamps
+
+ if self._df_for_struct and type(data_type) == StructType:
+ import pandas as pd
+ import pyarrow as pa
+ column_arrays = zip(*[[chunk.field(i)
+ for i in range(chunk.type.num_children)]
+ for chunk in arrow_column.data.iterchunks()])
+ series = [_arrow_column_to_pandas(pa.column(field.name,
pa.chunked_array(arrays)),
+ field.dataType)
+ for arrays, field in zip(column_arrays, data_type)]
+ s = _check_dataframe_localize_timestamps(pd.concat(series,
axis=1), self._timezone)
+ else:
+ s = super(ArrowStreamPandasUDFSerializer,
self).arrow_to_pandas(arrow_column, data_type)
Review comment:
No, this is just calling super class's method.
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