[jira] [Updated] (SPARK-11005) Spark 1.5 Shuffle performance - (sort-based shuffle)

["Sandeep Pal (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-11005?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sandeep Pal updated SPARK-11005:
--------------------------------
    Summary: Spark 1.5 Shuffle performance - (sort-based shuffle)  (was: Spark 1.5 Shuffle performance)

> Spark 1.5 Shuffle performance - (sort-based shuffle)
> ----------------------------------------------------
>
>                 Key: SPARK-11005
>                 URL: https://issues.apache.org/jira/browse/SPARK-11005
>             Project: Spark
>          Issue Type: Question
>          Components: Shuffle, SQL
>    Affects Versions: 1.5.0
>         Environment: 6 node cluster with 1 master and 5 worker nodes.
> Memory > 100 GB each
> Cores = 72 each
> Input data ~496 GB
>            Reporter: Sandeep Pal
>
> In case of terasort by Spark SQL with 20 total cores(4 cores/ executor), the performance of the map tasks is 14 minutes (around 26s-30s each) where as if I increase the number of cores to 60(12 cores /executor), the performance of map degrades to 30 minutes ( ~2.3 minutes per task). I believe the map tasks are independent of each other in the shuffle. 
> Each map task has 128 MB input (HDFS block size) in both of the above cases. So, what makes the performance degradation with increasing number of cores.
> 	



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