Dheeraj-1103 commented on issue #39704: URL: https://github.com/apache/beam/issues/39704#issuecomment-5248749756
I’d like to work on this issue. Proposed approach I’ll start by analyzing the recent failed Python tests workflow runs to identify the specific test(s) contributing to the high failure rate and compare the failure signatures across runs. From the initial investigation, I’ll focus on common sources of Python test flakiness such as: * race conditions or timing-sensitive behavior in concurrent tests * improper cleanup of temporary files, processes, or resources * shared/global state leaking between tests * nondeterministic ordering or asynchronous execution * network/service dependencies and transient failures * test isolation issues across parallel workers Once the failing test(s) are identified, I’ll reproduce the failure by running them repeatedly and use the failure traces to narrow down the root cause. The fix will aim to address the underlying nondeterministic behavior rather than simply increasing retries, timeouts, or skipping the affected test. I’ll then run the affected tests repeatedly and the relevant Python test suite to verify that the failure rate is eliminated or significantly reduced. I’ll start by narrowing down the flaky test(s) from the recent workflow failures and will update the issue with the findings before implementing the fix. -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
