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https://issues.apache.org/jira/browse/FLINK-34726?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17828262#comment-17828262
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Fei Feng edited comment on FLINK-34726 at 3/19/24 10:39 AM:
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I think this two things (rest cluster client and sessionjob's secondary
resource) should be contained in xxxContext , then we do not need to create
them again and again, and we can avoid unnecessary runtime overhead and GC
pressure finally.
The difficulty lies in how to promptly update when changes occur. for example,
rest cluster client should be recreate or update if jobmanager rest address
changed, and if FlinkDeployment object changed, sessionjob's SecondaryResource
should be update
was (Author: fei feng):
I think this two things (rest cluster client and flink deployment resource
info ) should be contained in Context, to avoid unnecessary runtime overhead
and GC pressure. The difficulty lies in how to promptly update when changes
occur. for example, rest cluster client should be recreate or update if
jobmanager rest address changed, and if FlinkDeployment object changed,
sessionjob's SecondaryResource should be update
> Flink Kubernetes Operator has some room for optimizing performance.
> -------------------------------------------------------------------
>
> Key: FLINK-34726
> URL: https://issues.apache.org/jira/browse/FLINK-34726
> Project: Flink
> Issue Type: Improvement
> Components: Kubernetes Operator
> Affects Versions: kubernetes-operator-1.5.0, kubernetes-operator-1.6.0,
> kubernetes-operator-1.7.0
> Reporter: Fei Feng
> Priority: Major
> Attachments: operator_no_submit_no_kill.flamegraph.html
>
>
> When there is a huge number of FlinkDeployment and FlinkSessionJob in a
> kubernetes cluster, there will be a significant delay between event submit
> into reconcile thread pool and event is processed.
> this is our test：we give operator enough resource（cpu: 10core, memory: 20g,
> reconcile thread pool size was 200 ) and we deployed 10000 jobs firstly (one
> FlinkDeployment and one SessionJob per job) , then we do submit/delete job
> tests. we found that
> 1. it cost about 2min between create new FlinkDeployment and FlinkSessionJob
> CR to k8s and the flink job submited to jobmanager.
> 2. it cost about 1min between delete a FlinkDeployment and FlinkSessionJob CR
> and the flink job and session cluster cleared.
>
> I use async-profiler to get flamegraph when there is a huge number
> FlinkDeployment and FlinkSessionJob. I found two obvious areas for
> optimization
> 1. For Flinkdeployment: in the observe step, we call
> AbstractFlinkService.getClusterInfo/listJobs/getTaskManagerInfo , every time
> we call these method we need create RestClusterClient/ send requests/ close,
> I think we should reuse RestClusterClient as much as possible to avoid
> frequently creating objects to reduce GC pressure
> 2. For FlinkSessionJob （This issue is more obvious）: in the whole reconcile
> loop, we call getSecondaryResource 5 times to get FlinkDeployement resource
> info. Based on my current understanding of the Flink Operator, I think we do
> not need to call it 5 times in a single reconcile loop, calling it once is
> enough. If yes, we cloud save 30% cpu usage (every getSecondaryResource cost
> 6% cpu usage)
> [^operator_no_submit_no_kill.flamegraph.html]
> I hope we can discuss solutions to address this problem together. I'm very
> willing to optimize and resolve this issue.
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