[jira] [Updated] (SPARK-18925) Reduce memory usage of mapWithState

["Hyukjin Kwon (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-18925?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Hyukjin Kwon updated SPARK-18925:
---------------------------------
    Labels: bulk-closed  (was: )

> Reduce memory usage of mapWithState
> -----------------------------------
>
>                 Key: SPARK-18925
>                 URL: https://issues.apache.org/jira/browse/SPARK-18925
>             Project: Spark
>          Issue Type: Improvement
>          Components: DStreams
>    Affects Versions: 2.0.0, 2.0.1, 2.0.2
>            Reporter: Vladimir Pchelko
>            Priority: Major
>              Labels: bulk-closed
>
> With default settings mapWithState leads to storing up to 10 copies of MapWithStateRDD in memory: 
> (DSream, InternalMapWithStateDStream, DEFAULT_CHECKPOINT_DURATION_MULTIPLIER, rememberDuration, minRememberDuration)
> In my project we quickly get OutOfMemory, because we have to track many millions of events * 2-3KB per event -> about 50 GB per MapWithStateRDD. 
> Using cluster with +500GB memory is unacceptable for our task.
> Reducing CHECKPOINT_DURATION_MULTIPLIER is unacceptable, it slightly 'fixes' memory issue, but leads to new one - we unable process data in real-time - because the checkpointing duration is in several times longer than batchInterval.
> So I investigated the mapWithState process and concluded that for proper functioning of mapWithState, we need the current MapWithStateRDD and the last checkpointed MapWithStateRDD.
> To fix memory issues in my project: I override clearMetadata for InternalMapWithStateDStream and unpersist all oldRDDs:
>   val oldRDDs = generatedRDDs.filter(_._1 <= (time - slideDuration))
> except the last checkpointed
>     val checkpointedKeys = oldRDDs.filter(_._2.isCheckpointed).keys
>     if (checkpointedKeys.nonEmpty) {
>       oldRDDs -= checkpointedKeys.max
>     }
> ... (C/P of DStream clearMetadata)
> Please correct me.



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