[
https://issues.apache.org/jira/browse/SPARK-3913?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14169760#comment-14169760
]
Apache Spark commented on SPARK-3913:
-------------------------------------
User 'chesterxgchen' has created a pull request for this issue:
https://github.com/apache/spark/pull/2786
> Spark Yarn Client API change to expose Yarn Resource Capacity, Yarn
> Application Listener and killApplication() API
> ------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-3913
> URL: https://issues.apache.org/jira/browse/SPARK-3913
> Project: Spark
> Issue Type: Improvement
> Components: YARN
> Reporter: Chester
>
> When working with Spark with Yarn deployment mode, we have two issues:
> 1) We don't know how much yarn max capacity ( memory and cores) before we
> specify the number of executor and memories for spark drivers and executors.
> We we set a big number, the job can potentially exceeds the limit and got
> killed.
> It would be better we let the application know that the yarn resource
> capacity a head of time and the spark config can adjusted dynamically.
>
> 2) Once job started, we would like to have some feedbacks from yarn
> application. Currently, the spark client basically block the call and returns
> when the job is finished or failed or killed.
> If the job runs for few hours, we have no idea how far it has gone, the
> progress and resource usage, tracking URL etc.
> 3) Once the job is started, you basically can't stop it. The Yarn Client API
> stop doesn't to work in most cases from our experience. But Yarn API does
> work is killApplication(appId).
> So we need to expose this killApplication() API to Spark Yarn Client as
> well.
>
> I will create one Pull Request and try to address these problems.
>
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
