[jira] [Assigned] (SPARK-11583) Make MapStatus use less memory uage

["Kent Yao (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-11583?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Kent Yao reassigned SPARK-11583:
--------------------------------

    Assignee: Kent Yao  (was: Davies Liu)

> Make MapStatus use less memory uage
> -----------------------------------
>
>                 Key: SPARK-11583
>                 URL: https://issues.apache.org/jira/browse/SPARK-11583
>             Project: Spark
>          Issue Type: Improvement
>          Components: Scheduler, Spark Core
>            Reporter: Kent Yao 2
>            Assignee: Kent Yao
>            Priority: Major
>             Fix For: 1.6.0
>
>
> In the resolved issue https://issues.apache.org/jira/browse/SPARK-11271, as I said, using BitSet can save ≈20% memory usage compared to RoaringBitMap. 
> For a spark job contains quite a lot of tasks, 20% seems a drop in the ocean. 
> Essentially, BitSet uses long[]. For example a BitSet[200k] = long[3125].
> So if we use a HashSet[Int] to store reduceId (when non-empty blocks are dense,use reduceId of empty blocks; when sparse, use non-empty ones). 
> For dense cases: if HashSet[Int](numNonEmptyBlocks).size <   BitSet[totalBlockNum], I use MapStatusTrackingNoEmptyBlocks
> For sparse cases: if HashSet[Int](numEmptyBlocks).size <   BitSet[totalBlockNum], I use MapStatusTrackingEmptyBlocks
> sparse case, 299/300 are empty
> sc.makeRDD(1 to 30000, 3000).groupBy(x=>x).top(5)
> dense case,  no block is empty
> sc.makeRDD(1 to 9000000, 3000).groupBy(x=>x).top(5)



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