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Posted to issues@spark.apache.org by "Jackey Lee (Jira)" <ji...@apache.org> on 2019/11/07 05:13:00 UTC
[jira] [Comment Edited] (SPARK-29771) Limit executor max failures
before failing the application
[ https://issues.apache.org/jira/browse/SPARK-29771?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16968933#comment-16968933 ]
Jackey Lee edited comment on SPARK-29771 at 11/7/19 5:12 AM:
-------------------------------------------------------------
This patch is mainly used in the scenario where the executor started failed. The executor runtime failure, which is caused by task errors is controlled by spark.executor.maxFailures.
Another Example, add `--conf spark.executor.extraJavaOptions=-Xmse` after spark-submit, which can also appear executor crazy retry.
was (Author: jackey lee):
This patch is mainly used in the scenario where the executor started failed. The executor runtime failurem, which is caused by task errors is controlled by spark.executor.maxFailures.
Another Example, add `--conf spark.executor.extraJavaOptions=-Xmse` after spark-submit, which can also appear executor crazy retry.
> Limit executor max failures before failing the application
> ----------------------------------------------------------
>
> Key: SPARK-29771
> URL: https://issues.apache.org/jira/browse/SPARK-29771
> Project: Spark
> Issue Type: Improvement
> Components: Kubernetes
> Affects Versions: 3.0.0
> Reporter: Jackey Lee
> Priority: Major
>
> At present, K8S scheduling does not limit the number of failures of the executors, which may cause executor retried continuously without failing.
> A simple example, we add a resource limit on default namespace. After the driver is started, if the quota is full, the executor will retry the creation continuously, resulting in a large amount of pod information accumulation. When many applications encounter such situations, they will affect the K8S cluster.
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