[
https://issues.apache.org/jira/browse/ARROW-17912?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Liangcai li updated ARROW-17912:
--------------------------------
Description:
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}_
```
was:
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.
``` Error
{color:#de350b}_'Must pass schema, or at least one RecordBatch'_{color}
```
> Arrow C++ IPC fails to send an empty table, but Arrow Java can do it.
> ---------------------------------------------------------------------
>
> 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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