[jira] [Commented] (SPARK-52504) Spark on Kubernetes with storage decommissioning

["Dongjoon Hyun (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-52504?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18004791#comment-18004791 ] 

Dongjoon Hyun commented on SPARK-52504:
---------------------------------------

According to the Apache Spark community policy, I lower the priority from `Blocker` to `Major`.
- https://spark.apache.org/contributing.html

bq. Priority. Set to Major or below; higher priorities are generally reserved for committers to set. 

> Spark on Kubernetes with storage decommissioning
> ------------------------------------------------
>
>                 Key: SPARK-52504
>                 URL: https://issues.apache.org/jira/browse/SPARK-52504
>             Project: Spark
>          Issue Type: Umbrella
>          Components: k8s, Kubernetes
>    Affects Versions: 4.1.0
>            Reporter: Enrico Minack
>            Priority: Blocker
>
> Spark on Kubernetes provides the storage decommissioning feature where shuffle data stored on an executor are migrated to other executors and optionally the fallback storage when an executor gets decommissioned.
> Using this feature allows for dynamic allocation on Kubernetes. However, using this in anger has showed a number of issues that render this setup not fit for production use.
> This issue collects those issues to provide an overview.
> The following can be used to reproduce the issues using a local minikube K8S cluster:
> [https://gist.github.com/EnricoMi/e9daa1176bce4c1211af3f3c5848112a]



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