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Biao Geng commented on FLINK-35035: ----------------------------------- I am not very familiar with adaptive scheduler, maybe others can share more insights. I just want to ask a question to make sure we are on the same page. Do you mean that instead of triggering onNewResourcesAvailable repeatedly once a new slot is found(in your example, 5 new slots so 5 times of rescheduling), you are expecting the JM can discover the 5 new slots at the same time after a configurable period of time and only trigger 1 time of rescheduling? > Reduce job pause time when cluster resources are expanded in adaptive mode > -------------------------------------------------------------------------- > > Key: FLINK-35035 > URL: https://issues.apache.org/jira/browse/FLINK-35035 > Project: Flink > Issue Type: Improvement > Components: Runtime / Task > Affects Versions: 1.19.0 > Reporter: yuanfenghu > Priority: Minor > > When 'jobmanager.scheduler = adaptive' , job graph changes triggered by > cluster expansion will cause long-term task stagnation. We should reduce this > impact. > As an example: > I have jobgraph for : [v1 (maxp=10 minp = 1)] -> [v2 (maxp=10, minp=1)] > When my cluster has 5 slots, the job will be executed as [v1 p5]->[v2 p5] > When I add slots the task will trigger jobgraph changes,by > org.apache.flink.runtime.scheduler.adaptive.ResourceListener#onNewResourcesAvailable, > However, the five new slots I added were not discovered at the same time (for > convenience, I assume that a taskmanager has one slot), because no matter > what environment we add, we cannot guarantee that the new slots will be added > at once, so this will cause onNewResourcesAvailable triggers repeatedly > ,If each new slot action has a certain interval, then the jobgraph will > continue to change during this period. What I hope is that there will be a > stable time to configure the cluster resources and then go to it after the > number of cluster slots has been stable for a certain period of time. Trigger > jobgraph changes to avoid this situation -- This message was sent by Atlassian Jira (v8.20.10#820010)