Github user staple commented on the pull request:
https://github.com/apache/spark/pull/2362#issuecomment-55682979
For the PR code, it looks like on each training iteration there are
messages about not being able to cache partitions rdd_4_5 - rdd_4_27
For the master code, it looks like on each training iteration there are
messages about not being able to cache partitions rdd_3_13, rdd_3_15 - rdd_3_27
It looks to me like a greater proportion of the data can be cached in
master, and the set of cached partitions seems consistent across all training
iterations.
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