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https://issues.apache.org/jira/browse/FLINK-24093?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Flink Jira Bot updated FLINK-24093:
-----------------------------------
Labels: auto-deprioritized-minor pull-request-available (was:
pull-request-available stale-minor)
Priority: Not a Priority (was: Minor)
This issue was labeled "stale-minor" 7 days ago and has not received any
updates so it is being deprioritized. If this ticket is actually Minor, please
raise the priority and ask a committer to assign you the issue or revive the
public discussion.
> Supports setting the percentage of kubernetes Request resources
> ---------------------------------------------------------------
>
> Key: FLINK-24093
> URL: https://issues.apache.org/jira/browse/FLINK-24093
> Project: Flink
> Issue Type: Improvement
> Components: Deployment / Kubernetes
> Reporter: liuzhuo
> Priority: Not a Priority
> Labels: auto-deprioritized-minor, pull-request-available
>
> For the current native Kubernetes, we start the job to apply for resources
> (CPU,Memory) of the same *limit* and *request*, so as to achieve the best
> performance. However, in general, when the kubernetes cluster resources are
> used up by request allocation, In fact, there are still some physical
> resources left. If there is a way to reduce the number of requests per job,
> more jobs can be run and the resource utilization of the cluster can be
> improved.
> Here are some simple configurations to scale down the value of request:
>
> {code:java}
> kubernetes.cpu.request.percent
> kubernetes.mem.request.percent
> {code}
>
> *kubernetes.mem.request.percent*： the default value is 1.0, the effective
> range of 0.0 to 1.0, the meaning of this value is: If the value is 0.5 and
> the total memory of taskmanager/jobmanager is 2048MB, the value of request is
> 2048MB*0.5=1024MB. That is, if the remaining memory of nodes is larger than
> 1024MB, pods can be allocated to run
> *kubernetes.cpu.request.percent：*the default value is 1.0, the effective
> range of 0.0 to 1.0, the meaning of this value is: If the value is 0.5 and
> the number of cpus requested by TaskManager/JobManager is 1, the value of
> request is 1 x 0.5=0.5, that is, the remaining CPU usage of Nodes is greater
> than 0.5 to allocate pods to run
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