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https://issues.apache.org/jira/browse/SPARK-4730?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14233596#comment-14233596
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Apache Spark commented on SPARK-4730:
-------------------------------------

User 'andrewor14' has created a pull request for this issue:
https://github.com/apache/spark/pull/3590

> Warn against deprecated YARN settings
> -------------------------------------
>
>                 Key: SPARK-4730
>                 URL: https://issues.apache.org/jira/browse/SPARK-4730
>             Project: Spark
>          Issue Type: Bug
>          Components: YARN
>    Affects Versions: 1.2.0
>            Reporter: Andrew Or
>            Assignee: Andrew Or
>
> Yarn currently reads from SPARK_MASTER_MEMORY and SPARK_WORKER_MEMORY. If you 
> have these settings leftover from a standalone cluster setup and you try to 
> run Spark on Yarn on the same cluster, then your executors suddenly get the 
> amount of memory specified through SPARK_WORKER_MEMORY.
> This behavior is due in large part to backward compatibility. However, we 
> should log a warning against the use of these variables at the very least.



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