[ https://issues.apache.org/jira/browse/FLINK-31608?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Matthias Pohl closed FLINK-31608. --------------------------------- Resolution: Invalid This topic was covered by [FLIP-472|https://cwiki.apache.org/confluence/display/FLINK/FLIP-472%3A+Aligning+timeout+logic+in+the+AdaptiveScheduler's+WaitingForResources+and+Executing+states] > Re-evaluate 'min-parallelism-increase' option > --------------------------------------------- > > Key: FLINK-31608 > URL: https://issues.apache.org/jira/browse/FLINK-31608 > Project: Flink > Issue Type: Sub-task > Components: Runtime / Configuration, Runtime / Coordination > Reporter: Chesnay Schepler > Priority: Major > Fix For: 2.0.0 > > > This option was meant to prevent scale up operations where the benefit > doesn't outweigh the cost, like scaling up to increase a single vertices > parallelism by 1. Meanwhile, scale-down operations were always immediately > executed, because they were always the result of a stopped TaskManager, > causing the job to restart anyway. > Now that users can change the requirements at will this has changed, and the > expected behavior is overall undefined. > We need to answer: > * should there be a dedicated option for limiting scale-down operations if > the requirements were changed? > * should the min-parallelism-{*}increase{*} option be generalized to a > min-parallelism-{*}change{*} option? > * How shall operations be handled that scale different vertices up or down > at the same? So far the decision was made on the cumulative parallelism > change, but in this case the parallelism distribution can change > significantly while the cumulative change is 0. > * If a rescale operation was not applied due to these limits, should they be > _eventually_ applied anyway (e.g., after a timeout)? > > See [https://github.com/apache/flink/pull/22169#discussion_r1147447567] for > the background. -- This message was sent by Atlassian Jira (v8.20.10#820010)