[SPARK-57271][PYTHON] Propagate traceback locals to Python planner runner - #57509
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The implementation is consistent with the existing Python worker contract and the regression test covers the affected end-to-end path.
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I traced the SQL config read through PythonPlannerRunner.runInPython to the worker environment and compared it with BasePythonRunner, which uses the same conditional environment variable. Python's shared handle_worker_exception consumes that variable as the TracebackException.capture_locals switch, and the new UDTF test exercises the planner-worker exception path.
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…nner ### What changes were proposed in this pull request? This PR propagates `SPARK_TRACEBACK_WITH_LOCALS` from `PythonPlannerRunner` when `spark.sql.execution.pyspark.udf.tracebackWithLocals.enabled` is enabled. It also adds a UDTF `analyze` regression test that raises from the planner-side Python worker and verifies the surfaced traceback includes the local variable. ### Why are the changes needed? `PythonPlannerRunner` already reads `spark.sql.execution.pyspark.udf.tracebackWithLocals.enabled`, but it did not add `SPARK_TRACEBACK_WITH_LOCALS` to the Python worker environment. As a result, planner-driven Python paths such as UDTF `analyze` did not honor the traceback-locals config, unlike regular Python UDF execution. ### Does this PR introduce _any_ user-facing change? Yes. When `spark.sql.execution.pyspark.udf.tracebackWithLocals.enabled` is enabled, Python exceptions raised through planner-driven Python paths can now include local variables in their tracebacks. ### How was this patch tested? Passed: ``` python3 python/run-tests.py --testnames "pyspark.sql.tests.test_udtf UDTFTests.test_udtf_analyze_traceback_with_locals" python3 python/run-tests.py --testnames "pyspark.sql.tests.test_udf UDFTests.test_udf_traceback_with_locals" ``` ### Was this patch authored or co-authored using generative AI tooling? Generated-by: OpenAI Codex (GPT-5) Closes #57509 from linhongliu-db/task/oss-spark-spark-57271-pythonplannerrunner-which-doesn-t-extend-basepythonrunner-f822ad87ff/implementation. Authored-by: Linhong Liu <linhong.liu@databricks.com> Signed-off-by: Wenchen Fan <wenchen@databricks.com> (cherry picked from commit 87dbc24) Signed-off-by: Wenchen Fan <wenchen@databricks.com>
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thanks, merging to master/4.x |
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What changes were proposed in this pull request?
This PR propagates
SPARK_TRACEBACK_WITH_LOCALSfromPythonPlannerRunnerwhenspark.sql.execution.pyspark.udf.tracebackWithLocals.enabledis enabled.It also adds a UDTF
analyzeregression test that raises from the planner-side Python worker and verifies the surfaced traceback includes the local variable.Why are the changes needed?
PythonPlannerRunneralready readsspark.sql.execution.pyspark.udf.tracebackWithLocals.enabled, but it did not addSPARK_TRACEBACK_WITH_LOCALSto the Python worker environment. As a result, planner-driven Python paths such as UDTFanalyzedid not honor the traceback-locals config, unlike regular Python UDF execution.Does this PR introduce any user-facing change?
Yes. When
spark.sql.execution.pyspark.udf.tracebackWithLocals.enabledis enabled, Python exceptions raised through planner-driven Python paths can now include local variables in their tracebacks.How was this patch tested?
Passed:
Was this patch authored or co-authored using generative AI tooling?
Generated-by: OpenAI Codex (GPT-5)