Github user dusenberrymw commented on the pull request:
https://github.com/apache/spark/pull/6585#issuecomment-108517651
Okay, I've updated the `DataFrame.drop` with `Column` references function
to use `logicalPlan.output` instead of `schema` to avoid ambiguities for
DataFrames with columns that have the same name. I also added unit tests in
Scala and Python specifically for testing this.
Now, if two DataFrames that share column names are joined together
resulting in a DataFrame "joinedDf" with duplicate column names, the correct
and appropriate column can be removed from the joined DataFrame by passing in
the associated `Column` from the original DataFrame to `joinedDf.drop`.
@ogirardot @cloud-fan @rxin
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