[jira] [Commented] (SPARK-8893) Require positive partition counts in RDD.repartition

["Apache Spark (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-8893?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14618402#comment-14618402 ] 

Apache Spark commented on SPARK-8893:
-------------------------------------

User 'darabos' has created a pull request for this issue:
https://github.com/apache/spark/pull/7285

> Require positive partition counts in RDD.repartition
> ----------------------------------------------------
>
>                 Key: SPARK-8893
>                 URL: https://issues.apache.org/jira/browse/SPARK-8893
>             Project: Spark
>          Issue Type: Improvement
>    Affects Versions: 1.4.0
>            Reporter: Daniel Darabos
>            Priority: Trivial
>
> What does {{sc.parallelize(1 to 3).repartition(p).collect}} return? I would expect {{Array(1, 2, 3)}} regardless of {{p}}. But if {{p}} < 1, it returns {{Array()}}. I think instead it should throw an {{IllegalArgumentException}}.
> I think the case is pretty clear for {{p}} < 0. But the behavior for {{p}} = 0 is also error prone. In fact that's how I found this strange behavior. I used {{rdd.repartition(a/b)}} with positive {{a}} and {{b}}, but {{a/b}} was rounded down to zero and the results surprised me. I'd prefer an exception instead of unexpected (corrupt) results.
> I'm happy to send a pull request for this.



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