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https://issues.apache.org/jira/browse/SPARK-12662?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15085764#comment-15085764
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Yin Huai commented on SPARK-12662:
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btw, with local sort operator, we can make row ordering in a partition
deterministic. However, if the partition that a row belongs to is not
deterministic (e.g. the DF shuffles data randomly), the returned DFs of
randomSplit still have this issue. Let's also add doc to the randomSplit to let
users know that random shuffle should not be used for the input DF of
randomSplit.
> 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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