[jira] [Commented] (BEAM-1444) Flatten of Bounded and Unbounded repeats the union with the RDD for each micro-batch.

["Kenneth Knowles (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/BEAM-1444?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17546262#comment-17546262 ] 

Kenneth Knowles commented on BEAM-1444:
---------------------------------------

This issue has been migrated to https://github.com/apache/beam/issues/18144

> Flatten of Bounded and Unbounded repeats the union with the RDD for each micro-batch. 
> --------------------------------------------------------------------------------------
>
>                 Key: BEAM-1444
>                 URL: https://issues.apache.org/jira/browse/BEAM-1444
>             Project: Beam
>          Issue Type: Bug
>          Components: runner-spark
>            Reporter: Amit Sela
>            Priority: P3
>
> Flatten of BOUNDED and UNBOUNDED PCollections in the Spark runner is implemented by applying {{SparkContext#union(RDD...)}} inside a {{DStream.transform()}} which causes the same RDD to be "unionized" into each micro-batch and so multiplying it's content in the resulting stream (x number of batches).
> Spark does not seem to provide any out-of-the-box implementations for this.
> One approach I tried was to create a stream from Queue (single RDD stream)  but this is not an option since this fails checkpointing.
> Another approach would be to create a custom {{InputDStream}} that does this.
> An important note here is that the challenge here is to find a solution that holds with checkpointing and recovery from failure.  



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