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https://issues.apache.org/jira/browse/SPARK-19090?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16157932#comment-16157932
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Carlos Vicenti edited comment on SPARK-19090 at 9/8/17 10:19 AM:
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I have found the same issue while using Hive On Spark (on Yarn) and
spark.dynamicAllocation.enabled set to true
{noformat}
SET spark.executor.cores=4;
SET spark.executor.memory=21G;
SET spark.yarn.executor.memoryOverhead=3813;
{noformat}
>From the application logs:
{noformat}
17/09/08 00:30:34 INFO yarn.YarnAllocator: Will request 1 executor containers,
each with 6 cores and 25317 MB memory including 3813 MB overhead
{noformat}
As mentioned above. This does not happen if I set
spark.dynamicAllocation.enabled to false.
I'm using v1.6
was (Author: cvicenti):
I have found the same issue while using Hive On Spark (on Yarn) and
spark.dynamicAllocation.enabled set to true
{noformat}
SET spark.executor.cores=4;
SET spark.executor.memory=21G;
SET spark.yarn.executor.memoryOverhead=3813;
{noformat}
>From the application logs:
{noformat}
17/09/08 00:30:34 INFO yarn.YarnAllocator: Will request 1 executor containers,
each with 6 cores and 25317 MB memory including 3813 MB overhead
{noformat}
As mentioned above. This does not happen if I set
spark.dynamicAllocation.enabled to false
> Dynamic Resource Allocation not respecting spark.executor.cores
> ---------------------------------------------------------------
>
> Key: SPARK-19090
> URL: https://issues.apache.org/jira/browse/SPARK-19090
> Project: Spark
> Issue Type: Bug
> Affects Versions: 1.5.2, 1.6.1, 2.0.1
> Reporter: nirav patel
>
> When enabling dynamic scheduling with yarn I see that all executors are using
> only 1 core even if I specify "spark.executor.cores" to 6. If dynamic
> scheduling is disabled then each executors will have 6 cores. i.e. it
> respects "spark.executor.cores". I have tested this against spark 1.5 . I
> think it will be the same behavior with 2.x as well.
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