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Date: Tue, 16 Feb 2016 07:11:18 +0000 (UTC)
From: "Xiao Li (JIRA)" <jira@apache.org>
To: issues@spark.apache.org
Message-ID: <JIRA.12939406.1455600973000.57802.1455606678072@Atlassian.JIRA>
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 <JIRA.12939406.1455600973598@arcas>
Subject: [jira] [Commented] (SPARK-13333) DataFrame filter + randn +
 unionAll has bad interaction
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    [ https://issues.apache.org/jira/browse/SPARK-13333?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15148182#comment-15148182 ] 

Xiao Li commented on SPARK-13333:
---------------------------------

This is a known issue. The same issue exists in CTE with non-deterministic expression. 

For example, the following query could return a wrong result. 

{code}
With q as (select * from testData limit 10) select * from q as q1 inner join q as q2 where q1.key = q2.key
{code}

We need to materialize it before doing self unionall/join/intersect like operations. 

> DataFrame filter + randn + unionAll has bad interaction
> -------------------------------------------------------
>
>                 Key: SPARK-13333
>                 URL: https://issues.apache.org/jira/browse/SPARK-13333
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 1.4.2, 1.6.1, 2.0.0
>            Reporter: Joseph K. Bradley
>
> Buggy workflow
> * Create a DataFrame df0
> * Filter df0
> * Add a randn column
> * Create a copy of the DataFrame
> * unionAll the two DataFrames
> This fails, where randn produces the same results on the original DataFrame and the copy before unionAll but fails to do so after unionAll.  Removing the filter fixes the problem.
> The bug can be reproduced on master:
> {code}
> import org.apache.spark.sql.functions.randn
> val df0 = sqlContext.createDataFrame(Seq(0, 1).map(Tuple1(_))).toDF("id")
> // Removing the following filter() call makes this give the expected result.
> val df1 = df0.filter(col("id") === 0).withColumn("b", randn(12345))
> println("DF1")
> df1.show()
> val df2 = df1.select("id", "b")
> println("DF2")
> df2.show()  // same as df1.show(), as expected
> val df3 = df1.unionAll(df2)
> println("DF3")
> df3.show()  // NOT two copies of df1, which is unexpected
> {code}


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