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https://issues.apache.org/jira/browse/SPARK-17908?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15572189#comment-15572189
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Sean Owen commented on SPARK-17908:
-----------------------------------
Can you provide the error and a self-contained reproduction? I can't reproduce
that on similar code but there's probably something different in what you're
actually doing.
> 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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