Github user viirya commented on the issue:
https://github.com/apache/spark/pull/16724
> Just realized df.repartition($"userId").sortWithinPartitions("userId",
"timestamp") will produce a result set as we expected, can we optimize this
case?
I may not understand you correctly. The result sets should be partitioned
by "userId" and sorted by "timestamp". But in each partition, the rows with the
same "userId" are not continuous.
But we want the rows with the same "userId" are continuous in each
partition and their `timestamp` values are sorted.
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