[jira] [Updated] (ARROW-17912) [C++] IPC writer does not write an empty batch in the case of an empty table, which PySpark cannot handle

["David Li (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/ARROW-17912?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

David Li updated ARROW-17912:
-----------------------------
    Summary: [C++] IPC writer does not write an empty batch in the case of an empty table, which PySpark cannot handle  (was: Arrow C++ IPC fails to send an empty table, but Arrow Java can do it.)

> [C++] IPC writer does not write an empty batch in the case of an empty table, which PySpark cannot handle
> ---------------------------------------------------------------------------------------------------------
>
>                 Key: ARROW-17912
>                 URL: https://issues.apache.org/jira/browse/ARROW-17912
>             Project: Apache Arrow
>          Issue Type: Bug
>          Components: C++
>            Reporter: Liangcai li
>            Priority: Major
>
> My current work is about Pyspark Cogroup Pandas UDF. And two processes are involved, the JVM one (sender) and the Python one (receiver).
> [Spark is using the Arrow Java `ArrowStreamWriter`|https://github.com/apache/spark/blob/branch-3.3/sql/core/src/main/scala/org/apache/spark/sql/execution/python/CoGroupedArrowPythonRunner.scala#L99] to serialize Arrow tables being sent from the JVM process to the Python process, and ArrowStreamWriter can handle empty tables correctly.
> [While cuDF is using the Arrow C++ RecordBatchWriter |https://github.com/rapidsai/cudf/blob/branch-22.10/java/src/main/native/src/TableJni.cpp#L254]to do the same serialization, but it leads to an error as below on the Python side, where [the Pyspark is calling Pyarrow *Table.from_batches*|https://github.com/apache/spark/blob/branch-3.3/python/pyspark/sql/pandas/serializers.py#L366] to deserialize the arrow stream.
> ``` 
> _E                     File "/usr/local/spark/python/lib/pyspark.zip/pyspark/sql/pandas/serializers.py", line 297, in load_stream_
> _E                       [self.arrow_to_pandas(c) for c in pa.Table.from_batches(batch2).itercolumns()]_
> _E                     File "pyarrow/table.pxi", line 1609, in pyarrow.lib.Table.from_batches_
> _E                   {color:#de350b}*ValueError: Must pass schema, or at least one RecordBatch*{color}_
> ```



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