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https://issues.apache.org/jira/browse/FLINK-35035?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17835106#comment-17835106
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yuanfenghu commented on FLINK-35035:
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[~bgeng777]
Thank you for your comment. As you understand, I hope that if a new tm occurs
during the running of the task, the task should not restart immediately, but
wait for a period of time.
Below I will explain this process in detail:
Taking the example I gave at the beginning, assume that the current task is [v1
(maxp=10 minp = 1)] -> [v2 (maxp=10, minp=1)], but the total number of slots in
the cluster is 5, so the task is running [v1 p5]->[v2 p5] runs. I have now
added 5 slots. I hope the task will run with [v1 p10]->[v2 p10]. When the
number of cluster slots becomes 6, the task will immediately trigger a restart.
At this time, according to the
jobmanager.adaptive-scheduler.resource-stabilization-timeout parameter, the
task will wait for a period of time during the restart phase for resources. If
the slot does not reach the target slot number of 10 during this period, the
task will run with a lower degree of parallelism. , but my slots will be added
to 10 over a period of time, so this will trigger another expansion and restart
process. In this process, I have one more restart process and one more resource
waiting process. Why don't we start before the first restart? Should I wait for
a period of time or determine that the number of slots meets my p=10 before
triggering the restart (scale up) action?
[~echauchot] hi, can you help me look into this issue, it seems similar to
FLINK-21883.
Thanks
> 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
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