Yicong-Huang commented on code in PR #58903:
URL: https://github.com/apache/spark/pull/58903#discussion_r4078051593
##########
python/pyspark/sql/conversion.py:
##########
@@ -180,6 +181,26 @@ def select_columns(cls, batch: "pa.RecordBatch",
column_indices: list[int]) -> "
[batch.schema.names[i] for i in column_indices],
)
+ @classmethod
+ def concat_batches(cls, batches: Iterable["pa.RecordBatch"]) ->
"pa.RecordBatch":
Review Comment:
the only remaining concern is that if we need to do some validity checks
- are all batches sharing the same schema
- will the total size exceeding the upper limit of a record batch (I recall
2GB). otherwise it would need chunked arrays.
But since this is the current behavior we can keep it this way and rely on
arrow's error messages for now.
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