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https://issues.apache.org/jira/browse/SPARK-60211?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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ASF GitHub Bot updated SPARK-60211:
-----------------------------------
Labels: pull-request-available (was: )
> Fix applyInPandasWithState failure with PyArrow 26 due to float slice offsets
> -----------------------------------------------------------------------------
>
> Key: SPARK-60211
> URL: https://issues.apache.org/jira/browse/SPARK-60211
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 3.5.8, 4.1.3, 4.0.4
> Reporter: L. C. Hsieh
> Priority: Major
> Labels: pull-request-available
>
> PyArrow 26.0.0 made {{RecordBatch.slice}} validate {{offset}}/{{length}} with
> {{operator.index}} (previously a float was silently truncated by the Cython
> int64 conversion).
> In {{ApplyInPandasWithStateSerializer.load_stream}},
> {{startOffset}}/{{numRows}} are read from the state struct column converted
> to pandas. When an Arrow batch contains null padding rows
> ({{ApplyInPandasWithStateWriter.EMPTY_STATE_METADATA_ROW}}, i.e. whenever a
> group has more than one data row), the int32 fields of the struct are
> promoted to float64 by the pandas conversion, so
> {{data_batch.slice(data_start_offset, num_data_rows)}} fails with:
> {noformat}
> TypeError: 'float' object cannot be interpreted as an integer
> {noformat}
> This breaks {{applyInPandasWithState}} for users on PyArrow 26, and
> {{FlatMapGroupsInPandasWithStateSuite}} in the branch-4.0 / branch-4.1
> scheduled builds since PyArrow 26.0.0 was released (the JVM build job
> installs an unpinned pyarrow).
> branch-4.2 and later are not affected: SPARK-54962 converts nullable integers
> with {{integer_object_nulls=True}}, so the values stay ints.
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