[jira] [Commented] (SPARK-3292) Shuffle Tasks run incessantly even though there's no inputs

["Tathagata Das (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-3292?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14155550#comment-14155550 ] 

Tathagata Das commented on SPARK-3292:
--------------------------------------

I mentioned this in the PR but I am adding it here as well.  Not returning an RDD can mess up a lot of the logic and semantics. For example if there is a transform() followed by updateStateByKey(), the result will be unpredictable. updateStateByKey expects the previous batch to have a state RDD. If it does not find any state RDD it will assume that this the start of the streamign computation and effectively initialize again, forgetting the previous states from 2 batches ago. So this change is incorrect.

Regarding the original problem of creating too many empty files, you can filter that out by doing explicitly saving yourself.

    dstream.foreachRDD { case (rdd, time) => 
        if (rdd.take(1).size == 1) {
           rdd.saveAsHadoopFile(....)
       }
    }

> Shuffle Tasks run incessantly even though there's no inputs
> -----------------------------------------------------------
>
>                 Key: SPARK-3292
>                 URL: https://issues.apache.org/jira/browse/SPARK-3292
>             Project: Spark
>          Issue Type: Improvement
>          Components: Streaming
>    Affects Versions: 1.0.2
>            Reporter: guowei
>
> such as repartition groupby join and cogroup
> for example. 
> if i want the shuffle outputs save as hadoop file ,even though  there is no inputs , many emtpy file generate too.
> it's too expensive , 



--
This message was sent by Atlassian JIRA
(v6.3.4#6332)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscribe@spark.apache.org
For additional commands, e-mail: issues-help@spark.apache.org