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https://issues.apache.org/jira/browse/SPARK-12556?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Aravind B resolved SPARK-12556.
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Resolution: Duplicate
> Pyspark dataframe unionAll call accepts incorrect input
> -------------------------------------------------------
>
> Key: SPARK-12556
> URL: https://issues.apache.org/jira/browse/SPARK-12556
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 1.4.1
> Reporter: Aravind B
>
> I actually encountered this problem with two dataframes that have 8 and 10
> columns each. The below is a made up example that reproduces what I observed
> going wrong.
> Consider the two dataframes:
> df1:
> +-------+----------+
> |id | count|
> +-------+----------+
> +-------+----------+
> df2:
> +-------+---------+----------+
> |id |new_count| count|
> +-------+---------+----------+
> | 1| 4| 6|
> | 1| 5| 6|
> | 3| 6| 6|
> | 2| 7| 6|
> +-------+---------+----------+
> The call:
> df3 = df1.unionAll(df2)
> returns successfully with df3 containing 2 cloumns. However, some columns now
> have swapped values (with other columns). Based on my previous experience I
> would say that df3's count column will actually be the new_count column.
> I believe that this call should never complete successfully in the first
> place and should throw an exception instead.
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