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https://issues.apache.org/jira/browse/SPARK-12662?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15086770#comment-15086770
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Apache Spark commented on SPARK-12662:
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User 'sameeragarwal' has created a pull request for this issue:
https://github.com/apache/spark/pull/10626
> 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: Sameer Agarwal
>
> 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.
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