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[SPARK-55059][PYTHON] Remove empty table workaround in toPandas - #53824
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[SPARK-55059][PYTHON] Remove empty table workaround in toPandas#53824Yicong-Huang wants to merge 1 commit into
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January 15, 2026 23:30
JIRA Issue Information=== Improvement SPARK-55059 === This comment was automatically generated by GitHub Actions |
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waiting for #53822 |
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depends on #54820 |
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cc @ueshin@HyukjinKwon@zhengruifeng this is ready for review. |
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### What changes were proposed in this pull request? Remove the SPARK-51112 workaround in `_convert_arrow_table_to_pandas()` that bypassed PyArrow's `to_pandas()` for empty tables. ### Why are the changes needed? The workaround was added because arrow-java's `ListVector.getBufferSizeFor(0)` returned 0, causing the offset buffer to be omitted for empty nested arrays in IPC serialization, which led to a segmentation fault in PyArrow. This has been fixed upstream in arrow-java 19.0.0 ([apache/arrow-java#343](apache/arrow-java#343)), which Spark adopted in SPARK-56000 (PR apache#54820). The workaround is no longer necessary. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Existing test `test_to_pandas_for_empty_df_with_nested_array_columns` passes. ### Was this patch authored or co-authored using generative AI tooling? No. Closesapache#53824 from Yicong-Huang/SPARK-55059/refactor/remove-empty-table-workaround. Authored-by: Yicong Huang <17627829+Yicong-Huang@users.noreply.github.com> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
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What changes were proposed in this pull request?
Remove the SPARK-51112 workaround in
_convert_arrow_table_to_pandas()that bypassed PyArrow'sto_pandas()for empty tables.Why are the changes needed?
The workaround was added because arrow-java's
ListVector.getBufferSizeFor(0)returned 0, causing the offset buffer to be omitted for empty nested arrays in IPC serialization, which led to a segmentation fault in PyArrow.This has been fixed upstream in arrow-java 19.0.0 (apache/arrow-java#343), which Spark adopted in SPARK-56000 (PR #54820). The workaround is no longer necessary.
Does this PR introduce any user-facing change?
No.
How was this patch tested?
Existing test
test_to_pandas_for_empty_df_with_nested_array_columnspasses.Was this patch authored or co-authored using generative AI tooling?
No.