BryanCutler commented on a change in pull request #24095: [SPARK-27163][PYTHON]
Cleanup and consolidate Pandas UDF functionality
URL: https://github.com/apache/spark/pull/24095#discussion_r266626633
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File path: python/pyspark/serializers.py
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@@ -352,28 +364,17 @@ def dump_stream(self, iterator, stream):
Make ArrowRecordBatches from Pandas Series and serialize. Input is a
single series or
a list of series accompanied by an optional pyarrow type to coerce the
data to.
"""
- import pyarrow as pa
- writer = None
- try:
- for series in iterator:
- batch = _create_batch(series, self._timezone, self._safecheck,
- self._assign_cols_by_name)
- if writer is None:
- write_int(SpecialLengths.START_ARROW_STREAM, stream)
- writer = pa.RecordBatchStreamWriter(stream, batch.schema)
- writer.write_batch(batch)
- finally:
- if writer is not None:
- writer.close()
+ batches = (_create_batch(series, self._timezone, self._safecheck,
self._assign_cols_by_name)
+ for series in iterator)
Review comment:
The only issue with this is that `createDataFrame` would need to handle
`SpecialLengths.START_ARROW_STREAM` for regular and encrypted options and I'm a
little hesitant to change that. I'll keep an option in
`ArrowStreamPandasSerializer` to not write the start stream for these cases.
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