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Posted to issues@spark.apache.org by "TommyLike (JIRA)" <ji...@apache.org> on 2019/04/01 07:05:00 UTC

[jira] [Updated] (SPARK-27334) Support specify scheduler name for executor pods when submit

     [ https://issues.apache.org/jira/browse/SPARK-27334?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

TommyLike updated SPARK-27334:
------------------------------
    Description: Currently, there are some external schedulers which bring a lot a great value into kubernetes scheduling especially for HPC case, take a look at the *kube-batch* ([https://github.com/kubernetes-sigs/kube-batch]). In order to support it, we had to use Pod Template which seems cumbersome. It would be much convenient if this can be configured via option such as *"spark.kubernetes.executor.schedulerName"* just like others.  (was: Now, there are some external schedulers which bring a lot a great value into kubernetes scheduling especially for HPC case, take a look at the [link kube-batch|[https://github.com/kubernetes-sigs/kube-batch]]. Currently, we had to use Pod Template to support this which seems cumbersome. It would be much convenient if this can be configured via option such as *"spark.kubernetes.executor.schedulerName"* just like others.)

> Support specify scheduler name for executor pods when submit
> ------------------------------------------------------------
>
>                 Key: SPARK-27334
>                 URL: https://issues.apache.org/jira/browse/SPARK-27334
>             Project: Spark
>          Issue Type: Improvement
>          Components: Kubernetes
>    Affects Versions: 2.4.0
>            Reporter: TommyLike
>            Priority: Major
>              Labels: easyfix, features
>
> Currently, there are some external schedulers which bring a lot a great value into kubernetes scheduling especially for HPC case, take a look at the *kube-batch* ([https://github.com/kubernetes-sigs/kube-batch]). In order to support it, we had to use Pod Template which seems cumbersome. It would be much convenient if this can be configured via option such as *"spark.kubernetes.executor.schedulerName"* just like others.



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