polyzos commented on PR #29662: URL: https://github.com/apache/flink/pull/29662#issuecomment-6819674378
Some test evidence for this PR from a Flink Kubernetes Operator autoscaling lab (operator 1.16.1, Flink 2.3.0, application mode, Fluss sources and sinks). **Without the fix (Flink 2.3.0):** - Default scheduler: the autoscaler wrote correct overrides, each decision triggered a savepoint restart, and every vertex came back at parallelism 1. - Adaptive scheduler: the in-place rescale worked, but any redeploy (configuration change, restart nonce, suspend and resume) returned the job to its configured parallelism, and the autoscaler stayed stuck until `autoscalerResetNonce` was changed. **With this PR (commit `c7936e92`) backported onto release-2.3.0** (main sources of `flink-core` and `flink-runtime` only): - Default scheduler: every decision took effect, with a redeploy of about 1.5 to 2 minutes each. - Adaptive scheduler: rescaled in place, and the scaled parallelism survived a restart, a suspend and resume, and spec edits. - Steady-state autoscaling then behaved as expected: no scaling at steady load, a load step absorbed in two steps, and a backlog cleared by a scale-out. We tested streaming SQL jobs only, in application mode. The PR's own tests were not run on the backport. -- 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]
