[
https://issues.apache.org/jira/browse/BEAM-848?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Aviem Zur reassigned BEAM-848:
------------------------------
Assignee: Aviem Zur (was: Amit Sela)
> A better shuffle after reading from within mapWithState.
> --------------------------------------------------------
>
> Key: BEAM-848
> URL: https://issues.apache.org/jira/browse/BEAM-848
> Project: Beam
> Issue Type: Improvement
> Components: runner-spark
> Reporter: Amit Sela
> Assignee: Aviem Zur
>
> The SparkRunner uses {{mapWithState}} to read and manage CheckpointMarks, and
> this stateful operation will be followed by a shuffle:
> https://github.com/apache/spark/blob/master/streaming/src/main/scala/org/apache/spark/streaming/dstream/MapWithStateDStream.scala#L159
> Since the stateful read maps "splitSource" -> "partition of a list of read
> values", the following shuffle won't benefit in any way (the list of read
> values has not been flatMapped yet). In order to avoid shuffle we need to set
> the input RDD ({{SourceRDD.Unbounded}}) partitioner to be a default
> {{HashPartitioner}} since {{mapWithState}} would use the same partitioner and
> will skip shuffle if the partitioners match.
> It would be wise to shuffle the read values _after_ flatmap.
> I will break this into two tasks:
> # Set default-partitioner to the input RDD.
> # Shuffle (using Coders) the input.
--
This message was sent by Atlassian JIRA
(v6.3.15#6346)
