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https://issues.apache.org/jira/browse/SPARK-19090?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15813962#comment-15813962
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nirav patel commented on SPARK-19090:
-------------------------------------
Oh right, I have that set exclusively. I corrected my comment. I verified that
dynamic allocation was enabled by checking following in driver logs:
2017-01-04 12:04:11,362 INFO [spark-dynamic-executor-allocation]
org.apache.spark.ExecutorAllocationManager: Requesting 4 new executors because
tasks are backlogged (new desired total will be 6)
If it was not enabled then it should have actually create 6 executors with 5
cores.
here's the snippet of code I have:
if(sparkConfig.dynamicAllocation){
sparkConf.set("spark.dynamicAllocation.enabled", "true")
sparkConf.set("spark.dynamicAllocation.executorIdleTimeout", "600s")
sparkConf.set("spark.dynamicAllocation.initialExecutors",
sparkConfig.executorInstances)
sparkConf.set("spark.dynamicAllocation.minExecutors",
String.valueOf((Integer.valueOf(sparkConfig.executorInstances) - 3)))
sparkConf.set("spark.dynamicAllocation.sustainedSchedulerBacklogTimeout",
"300s")
sparkConf.set("spark.dynamicAllocation.schedulerBacklogTimeout", "120")
} else {
sparkConf.set("spark.executor.instances",
sparkConfig.executorInstances)
}
sparkConf.set("spark.executor.cores",
sparkConfig.executorCores)
> 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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