I've heard "Spark is not just MapReduce" mentioned during Spark talks, but it
seems like every method that Spark has is really doing something like (Map
-> Reduce) or (Map -> Map -> Map -> Reduce) etc behind the scenes, with the
performance benefit of keeping RDDs in memory between stages.

Am I wrong about that?  Is Spark doing anything more efficiently than a
series of Maps followed by a Reduce in memory?  What methods does Spark have
that can't easily be mapped (with somewhat similar efficiency) to Map and
Reduce in memory?



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