Level: Intermediate (I think?) Scenario: Feature Request Hello dev@,
(First time posting on this mailing list; apologies in advance if this should have been routed elsewhere or is missing any information). Un-pivoting data is supported on numerous SQL engines & in Pandas (with the 'melt' function), but it isn't directly available in spark. It's easy enough to derive this functionality using the 'stack' function or a combination of struct, array, and explode (e.g. such as the reproduction of the melt function in pandas-on-pyspark here <https://github.com/apache/spark/blob/c92bd5cafe62ca5226176446735171cc877e805a/python/pyspark/pandas/frame.py#L9651>), but I was wondering whether a more native solution had been considered? It would make end-user code more lightweight at the very least; and I wonder whether it could be made more efficient than using the stack function/struct-array-explode method. I'm happy to try and make a PR if this is something that might be useful within spark. No worries if this is not something that you think should be supported; the methods above work and are well documented on StackOverflow. I was personally just caught out by this, and thought it would be useful to raise. I did see a thread in the Pony archive about this issue, but it looks like it didn't go anywhere. Does anyone else have context on this <https://lists.apache.org/list?dev@spark.apache.org:lte=60M:unpivot>? Kind Regards, -- *Daniel Davies*
