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From Koert Kuipers <ko...@tresata.com>
Subject Re: What does "Spark is not just MapReduce" mean? Isn't every Spark job a form of MapReduce?
Date Sun, 28 Jun 2015 20:44:15 GMT
spark is partitioner aware, so it can exploit a situation where 2 datasets
are partitioned the same way (for example by doing a map-side join on
them). map-red does not expose this.

On Sun, Jun 28, 2015 at 12:13 PM, YaoPau <jonrgregg@gmail.com> wrote:

> 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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