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From "Adrian Wang (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-13393) Column mismatch issue in left_outer join using Spark DataFrame
Date Wed, 09 Mar 2016 07:29:41 GMT

    [ https://issues.apache.org/jira/browse/SPARK-13393?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15186661#comment-15186661
] 

Adrian Wang commented on SPARK-13393:
-------------------------------------

How do you resolve it? Both sides are `df`, so we can resolve df("key") to single side, which
leads to a Cartesian join (4 output rows); or we can resolve to both sides (2 output rows).
We are not able to tell what the user meant to.

> Column mismatch issue in left_outer join using Spark DataFrame
> --------------------------------------------------------------
>
>                 Key: SPARK-13393
>                 URL: https://issues.apache.org/jira/browse/SPARK-13393
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 1.5.0
>            Reporter: Varadharajan
>
> Consider the below snippet:
> {code:title=test.scala|borderStyle=solid}
> case class Person(id: Int, name: String)
> val df = sc.parallelize(List(
>   Person(1, "varadha"),
>   Person(2, "nagaraj")
> )).toDF
> val varadha = df.filter("id = 1")
> val errorDF = df.join(varadha, df("id") === varadha("id"), "left_outer").select(df("id"),
varadha("id") as "varadha_id")
> val nagaraj = df.filter("id = 2").select(df("id") as "n_id")
> val correctDF = df.join(nagaraj, df("id") === nagaraj("n_id"), "left_outer").select(df("id"),
nagaraj("n_id") as "nagaraj_id")
> {code}
> The `errorDF` dataframe, after the left join is messed up and shows as below:
> | id|varadha_id|
> |  1|         1|
> |  2|         2 (*This should've been null*)| 
> whereas correctDF has the correct output after the left join:
> | id|nagaraj_id|
> |  1|      null|
> |  2|         2|



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