Github user pwendell commented on the pull request:
https://github.com/apache/spark/pull/5403#issuecomment-90736418
Yeah so my feeling on this one is I'm sure it's really useful for
benchmarks where you can size things so that data is in memory, but I'd be
really hesitant to expose this to the average Spark user. For instance, you
could have some increase in the input size of your data and then suddenly, for
no reason, your production job now fails with an out-of-memory exception. That
seems like it could easily cause bad user experience for people so I just
wondered if this could be maintained as a third party package.
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