[ 
https://issues.apache.org/jira/browse/SPARK-24135?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16462145#comment-16462145
 ] 

Anirudh Ramanathan commented on SPARK-24135:
--------------------------------------------

cc/ [~mridulm80] [~irashid] for thoughts on whether this behavior would be 
intuitive to an existing Spark user.

> [K8s] Executors that fail to start up because of init-container errors are 
> not retried and limit the executor pool size
> -----------------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-24135
>                 URL: https://issues.apache.org/jira/browse/SPARK-24135
>             Project: Spark
>          Issue Type: Bug
>          Components: Kubernetes
>    Affects Versions: 2.3.0
>            Reporter: Matt Cheah
>            Priority: Major
>
> In KubernetesClusterSchedulerBackend, we detect if executors disconnect after 
> having been started or if executors hit the {{ERROR}} or {{DELETED}} states. 
> When executors fail in these ways, they are removed from the pending 
> executors pool and the driver should retry requesting these executors.
> However, the driver does not handle a different class of error: when the pod 
> enters the {{Init:Error}} state. This state comes up when the executor fails 
> to launch because one of its init-containers fails. Spark itself doesn't 
> attach any init-containers to the executors. However, custom web hooks can 
> run on the cluster and attach init-containers to the executor pods. 
> Additionally, pod presets can specify init containers to run on these pods. 
> Therefore Spark should be handling the {{Init:Error}} cases regardless if 
> Spark itself is aware of init-containers or not.
> This class of error is particularly bad because when we hit this state, the 
> failed executor will never start, but it's still seen as pending by the 
> executor allocator. The executor allocator won't request more rounds of 
> executors because its current batch hasn't been resolved to either running or 
> failed. Therefore we end up with being stuck with the number of executors 
> that successfully started before the faulty one failed to start, potentially 
> creating a fake resource bottleneck.



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

Reply via email to