[SPARK-59007][PYTHON][TESTS] Fix flaky Arrow grouped map worker logging tests - #58289
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[SPARK-59007][PYTHON][TESTS] Fix flaky Arrow grouped map worker logging tests#58289Yicong-Huang wants to merge 1 commit into
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…ests to fix flakiness
zhengruifeng
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Aug 26, 2026
uros-b
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Thank you @Yicong-Huang and @zhengruifeng! |
HyukjinKwon
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…g tests ### What changes were proposed in this pull request? Wrap the log read-and-assert step of `ApplyInArrowTests.test_apply_in_arrow_with_logging` and `test_apply_in_arrow_iter_with_logging` in `eventually` so it polls until the asynchronously captured worker logs are visible. The `applyInArrow` call that produces the logs stays outside the poll so it runs once. ### Why are the changes needed? Observed on fork CI: the `pyspark-sql` job failed with `[DIFFERENT_ROWS]` (100%) where `spark.tvf.python_worker_logs()` returned no rows instead of the expected two WARNING rows, then re-ran green on the next attempt: https://github.com/Yicong-Huang/spark/actions/runs/32828898783/job/97748219772 Root cause: worker logs are captured asynchronously. Python workers emit log records on stdout; on the JVM side a per-worker `RedirectThread` (`PythonWorkerLogCapture`) drains stdout and only saves the log block to the `BlockManager` once it reads the trailing marker line. That drain runs independently of the query result, which returns over a separate socket channel, so `python_worker_logs()` invoked right after the query can observe zero blocks. Polling the read side waits out the race. ### Does this PR introduce _any_ user-facing change? No. ### How was this patch tested? Built with `build/sbt -Phive package` and ran `python/run-tests --testnames 'pyspark.sql.tests.arrow.test_arrow_grouped_map'`; both logging tests and the full module pass. ### Was this patch authored or co-authored using generative AI tooling? No. Closes #58289 from Yicong-Huang/flaky-worker-logs. Authored-by: Yicong Huang <17627829+Yicong-Huang@users.noreply.github.com> Signed-off-by: Yicong-Huang <17627829+Yicong-Huang@users.noreply.github.com> (cherry picked from commit 02cb44f) Signed-off-by: Yicong-Huang <17627829+Yicong-Huang@users.noreply.github.com>
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What changes were proposed in this pull request?
Wrap the log read-and-assert step of
ApplyInArrowTests.test_apply_in_arrow_with_loggingandtest_apply_in_arrow_iter_with_loggingin@eventuallyso it polls until the asynchronously captured worker logs are visible. TheapplyInArrowcall that produces the logs stays outside the poll so it runs once.Why are the changes needed?
Observed on fork CI: the
pyspark-sqljob failed with[DIFFERENT_ROWS](100%) wherespark.tvf.python_worker_logs()returned no rows instead of the expected two WARNING rows, then re-ran green on the next attempt: https://github.com/Yicong-Huang/spark/actions/runs/32828898783/job/97748219772Root cause: worker logs are captured asynchronously. Python workers emit log records on stdout; on the JVM side a per-worker
RedirectThread(PythonWorkerLogCapture) drains stdout and only saves the log block to theBlockManageronce it reads the trailing marker line. That drain runs independently of the query result, which returns over a separate socket channel, sopython_worker_logs()invoked right after the query can observe zero blocks. Polling the read side waits out the race.Does this PR introduce any user-facing change?
No.
How was this patch tested?
Built with
build/sbt -Phive packageand ranpython/run-tests --testnames 'pyspark.sql.tests.arrow.test_arrow_grouped_map'; both logging tests and the full module pass.Was this patch authored or co-authored using generative AI tooling?
No.