Hello dev@, I had a quick question about the unionByName function. This function currently seems to accept a parameter- "allowMissingColumns"- that allows some tolerance to merging datasets with different schemas [e.g. here <https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/Dataset.scala#L2170>]; but the implementation is currently a bit restrictive, i.e., with the second parameter being a boolean, it is only possible to make unionByName add all columns from both dataframes at the moment. We have other use cases that would be useful to have natively in spark- for example, to take only column names that are in both dataframes (and I'm assuming that other users will have different merge strategies in mind also). Are there any plans for making a second parameter to unionByName a string (denoting a column merging 'mode' parameter)? If not, would the community be in favour of a PR that implements something like this?
Kind Regards, Daniel
