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https://issues.apache.org/jira/browse/SPARK-17908?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15572330#comment-15572330
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Sean Owen commented on SPARK-17908:
-----------------------------------

Yes what's your code? This says one DF has just 'columns' as column. 

> Column names Corrupted in pysaprk dataframe groupBy
> ---------------------------------------------------
>
>                 Key: SPARK-17908
>                 URL: https://issues.apache.org/jira/browse/SPARK-17908
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 1.6.0, 1.6.1, 1.6.2, 2.0.0, 2.0.1
>            Reporter: Harish
>            Priority: Minor
>
> I have DF say df
> df1= df.groupBy('key1', 'key2', 
> 'key3').agg(func.count(func.col('val')).alias('total'))
> df3 =df.join(df1, ['key1', 'key2', 'key3'])\
>              .withcolumn('newcol', func.col('val')/func.col('total'))
> I am getting key2 is not present in df1, which is not truw becuase df1.show 
> () is having the data with the key2.
> Then i added this code  before join-- df1 = df1.columnRenamed('key2', 'key2') 
> renamed with same name. Then it works.
> Stack trace will say column missing, but it is npt.



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