Github user pwendell commented on the pull request:
https://github.com/apache/spark/pull/8931#issuecomment-146288685
The reason I like accumulated memory is that it's something that should be
roughly constant over multiple runs of a workload so people can get a sense of
how much data they are buffering during execution. The max and median will
depend a lot on how tasks are scheduled, etc, so they don't give someone a
great idea of how they can change their query or data to get memory under
control. It's just how in hadoop you can see the total input size for a job.
These totals are often really helpful.
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