Github user viirya commented on the pull request:
https://github.com/apache/spark/pull/5572#issuecomment-105334419
> The more important thing to cache is probably rdd2. rdd2.iterator is
called once per element in .rdd1.iterator, which is why you end up with soooo
many remote fetches in the current implementation. By caching rdd1 locally, you
only save doing remote fetches for however many threads you have in one
executor. (And I'm not 100% sure that is even true as implemented in the PR
currently, I have a feeling all threads will simultaneously try to fetch and
insert into the local cache.) Most probably elementsPerPartition >>
threadsPerExecutor.
Because `CacheManager` has a lock for fetching partition, I think we should
not see the situation that all threads will simultaneously try to fetch and
insert into the local cache.
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