[jira] [Updated] (SPARK-12662) Add document to randomSplit to explain the sampling depends on the ordering of the rows in a partition

["Yin Huai (JIRA)" <ji...@apache.org>]

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

Yin Huai updated SPARK-12662:
-----------------------------
    Assignee: Sameer Agarwal

> Add document to randomSplit to explain the sampling depends on the ordering of the rows in a partition
> ------------------------------------------------------------------------------------------------------
>
>                 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 more document to the api doc to explain it. To make intersectDF contain 0 row, the df needs to have fixed row ordering within a partition.



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