[jira] [Comment Edited] (SPARK-3098) In some cases, operation zipWithIndex get a wrong results

["Guoqiang Li (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-3098?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14102024#comment-14102024 ] 

Guoqiang Li edited comment on SPARK-3098 at 8/19/14 8:55 AM:
-------------------------------------------------------------

the (id, value) pairs are generated there zipWithIndex.
The reproduce code:
{code}
   val c = sc.parallelize(1 to 7899).flatMap { i =>
      (1 to 10000).toSeq.map(p => i * 6000 + p)
    }.distinct().zipWithIndex()
    val e = c.map(t => (t._1, t._2.toString))
    val d = c.filter(t => t._1 % 100 > 5)
    e.join(d).filter(t => t._2._1 != t._2._2.toString).take(3)
{code}


was (Author: gq):
the (id, value) pairs are generated there zipWithIndex.
Reproduce the code:
{code}
   val c = sc.parallelize(1 to 7899).flatMap { i =>
      (1 to 10000).toSeq.map(p => i * 6000 + p)
    }.distinct().zipWithIndex()
    val e = c.map(t => (t._1, t._2.toString))
    val d = c.filter(t => t._1 % 100 > 5)
    e.join(d).filter(t => t._2._1 != t._2._2.toString).take(3)
{code}

>  In some cases, operation zipWithIndex get a wrong results
> ----------------------------------------------------------
>
>                 Key: SPARK-3098
>                 URL: https://issues.apache.org/jira/browse/SPARK-3098
>             Project: Spark
>          Issue Type: Bug
>          Components: Spark Core
>    Affects Versions: 1.0.1
>            Reporter: Guoqiang Li
>            Priority: Critical
>
> I do not know how to reproduce the bug.
> This is the case. When I was in operating 10 billion data by groupByKey. the results error:
> {noformat}
> (4696501, 370568)
> (4696501, 376672)
> (4696501, 374880)
> .....
> (4696502, 350264)
> (4696502, 358458)
> (4696502, 398502)
> ......
> {noformat} 
> => 
> {noformat}
> (4696501,ArrayBuffer(350264, 358458, 398502 ........)), (4696502,ArrayBuffer(376621, ......))
> {noformat}
> code :
> {code}
>     val dealOuts = clickPreferences(sc, dealOutPath, periodTime)
>     val dealOrders = orderPreferences(sc, dealOrderPath, periodTime)
>     val favorites = favoritePreferences(sc, favoritePath, periodTime)
>     val allBehaviors = (dealOrders ++ favorites ++ dealOuts)
>     val peferences= allBehaviors.groupByKey().map { ... } 
> {code}
> spark-defaults.conf:
> {code}
> spark.default.parallelism    280
> {code}



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