You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@spark.apache.org by "Apache Spark (JIRA)" <ji...@apache.org> on 2016/01/07 05:04:39 UTC

[jira] [Assigned] (SPARK-12662) Add a local sort operator to DataFrame used by randomSplit

     [ https://issues.apache.org/jira/browse/SPARK-12662?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Apache Spark reassigned SPARK-12662:
------------------------------------

    Assignee: Apache Spark  (was: Sameer Agarwal)

> Add a local sort operator to DataFrame used by randomSplit
> ----------------------------------------------------------
>
>                 Key: SPARK-12662
>                 URL: https://issues.apache.org/jira/browse/SPARK-12662
>             Project: Spark
>          Issue Type: Bug
>          Components: Documentation, SQL
>            Reporter: Yin Huai
>            Assignee: Apache Spark
>
> With {{./bin/spark-shell --master=local-cluster[2,1,2014]}}, the following code will provide overlapped rows for two DFs returned by the randomSplit. 
> {code}
> sqlContext.sql("drop table if exists test")
> val x = sc.parallelize(1 to 210)
> case class R(ID : Int)
> sqlContext.createDataFrame(x.map {R(_)}).write.format("json").saveAsTable("bugsc1597")
> var df = sql("select distinct ID from test")
> var Array(a, b) = df.randomSplit(Array(0.333, 0.667), 1234L)
> a.registerTempTable("a")
> b.registerTempTable("b")
> val intersectDF = a.intersect(b)
> intersectDF.show
> {code}
> The reason is that {{sql("select distinct ID from test")} does not guarantee the ordering rows in a partition. It will be good to add a local sort operator to make row ordering within a partition deterministic.



--
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