[SPARK-56937][PYTHON] Raise error on wrong column count in Arrow grouped/cogrouped map UDF#55978
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[SPARK-56937][PYTHON] Raise error on wrong column count in Arrow grouped/cogrouped map UDF#55978Yicong-Huang wants to merge 1 commit into
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Yicong-Huang
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does these query also fail before this PR? |
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No. They either silently drops data (too many) or surfaces a JVM ArrayIndexOutOfBoundsException (too few). |
zhengruifeng
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…ped/cogrouped map UDF ### What changes were proposed in this pull request? In `verify_arrow_result` (`python/pyspark/worker.py`), the positional branch zips expected and actual columns without a length check, silently truncating to the shorter list. This PR raises `RESULT_COLUMN_SCHEMA_MISMATCH` on length mismatch. ### Why are the changes needed? Latent since SPARK-40559. Under `assignColumnsByName=false`, a UDF returning the wrong number of columns either silently drops data (too many) or surfaces a JVM `ArrayIndexOutOfBoundsException` (too few). The name-based branch already raises a friendly error; positional should be symmetric. Affects `SQL_GROUPED_MAP_ARROW_UDF`, `SQL_GROUPED_MAP_ARROW_ITER_UDF`, `SQL_COGROUPED_MAP_ARROW_UDF`. ### Does this PR introduce _any_ user-facing change? Yes. Wrong column count under positional mode now raises `RESULT_COLUMN_SCHEMA_MISMATCH` instead of silent truncation or a JVM error. ### How was this patch tested? Added `test_apply_in_arrow_returning_wrong_column_count_positional_assignment` in `test_arrow_grouped_map.py` (covers iterator variant via `function_variations`) and `test_arrow_cogrouped_map.py`, exercising both too-many and too-few columns. Full grouped/cogrouped Arrow map suites pass. ### Was this patch authored or co-authored using generative AI tooling? No. Closes #55978 from Yicong-Huang/SPARK-56937. Authored-by: Yicong Huang <17627829+Yicong-Huang@users.noreply.github.com> Signed-off-by: Ruifeng Zheng <ruifengz@foxmail.com> (cherry picked from commit 4306d02) Signed-off-by: Ruifeng Zheng <ruifengz@foxmail.com>
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thanks, merged into master/4.x |
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What changes were proposed in this pull request?
In
verify_arrow_result(python/pyspark/worker.py), the positional branch zips expected and actual columns without a length check, silently truncating to the shorter list. This PR raisesRESULT_COLUMN_SCHEMA_MISMATCHon length mismatch.Why are the changes needed?
Latent since SPARK-40559. Under
assignColumnsByName=false, a UDF returning the wrong number of columns either silently drops data (too many) or surfaces a JVMArrayIndexOutOfBoundsException(too few). The name-based branch already raises a friendly error; positional should be symmetric.Affects
SQL_GROUPED_MAP_ARROW_UDF,SQL_GROUPED_MAP_ARROW_ITER_UDF,SQL_COGROUPED_MAP_ARROW_UDF.Does this PR introduce any user-facing change?
Yes. Wrong column count under positional mode now raises
RESULT_COLUMN_SCHEMA_MISMATCHinstead of silent truncation or a JVM error.How was this patch tested?
Added
test_apply_in_arrow_returning_wrong_column_count_positional_assignmentintest_arrow_grouped_map.py(covers iterator variant viafunction_variations) andtest_arrow_cogrouped_map.py, exercising both too-many and too-few columns. Full grouped/cogrouped Arrow map suites pass.Was this patch authored or co-authored using generative AI tooling?
No.