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From tbertelsen <>
Subject [GitHub] spark pull request: [SPARK-6307][Core] Speed up RDD.cartesian by c...
Date Tue, 26 May 2015 07:15:44 GMT
Github user tbertelsen commented on the pull request:
    > I think rdd2 will be cached at most W times, which is the number of nodes. Because
BlockManager is running per node, not per executor, right?
    You are right, my mistake.
    > 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
    Great, then we don't have to think about any race conditions.
    > I am not sure why coalescing can have a lot help. Once we coalesce rdd2 to small
number of partitions, we still need to fetch them all for each element in rdd1, right?
    You are right if we don't change anything, i.e., don't even implement idea one. The advantage
is when we only implement idea 1 but not idea two. In this case we will fetch each partition
in RDD2 once for each partition in RDD1 (and vice versa).So fewer partitions means fewer repeated
fetches, but we still need enough partitions to exploit the parallelism.

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