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From Andrew Ash <and...@andrewash.com>
Subject Re: Implementing rdd.scanLeft()
Date Thu, 05 Jun 2014 19:24:38 GMT
I that something that documentation on the method can solve?


On Thu, Jun 5, 2014 at 10:47 AM, Reynold Xin <rxin@databricks.com> wrote:

> I think the main concern is this would require scanning the data twice, and
> maybe the user should be aware of it ...
>
>
> On Thu, Jun 5, 2014 at 10:29 AM, Andrew Ash <andrew@andrewash.com> wrote:
>
> > I have a use case that would greatly benefit from RDDs having a
> .scanLeft()
> > method.  Are the project developers interested in adding this to the
> public
> > API?
> >
> >
> > Looking through past message traffic, this has come up a few times.  The
> > recommendation from the list before has been to implement a parallel
> prefix
> > scan.
> >
> > http://comments.gmane.org/gmane.comp.lang.scala.spark.user/1880
> > https://groups.google.com/forum/#!topic/spark-users/ts-FdB50ltY
> >
> > The algorithm Reynold sketched in the first link leads to this working
> > implementation:
> >
> > val vector = sc.parallelize(1 to 20, 3)
> >
> > val sums = 0 +: vector.mapPartitionsWithIndex{ case(partition, iter) =>
> > Iterator(iter.sum) }.collect.scanLeft(0)(_+_).drop(1)
> >
> > val prefixScan = vector.mapPartitionsWithIndex { case(partition, iter) =>
> >   val base = sums(partition)
> >   println(partition, base)
> >   iter.scanLeft(base)(_+_).drop(1)
> > }.collect
> >
> >
> > I'd love to have that replaced with this:
> >
> > val vector = sc.parallelize(1 to 20, 3)
> > val cumSum: RDD[Int] = vector.scanLeft(0)(_+_)
> >
> >
> > Any thoughts on whether this contribution would be accepted?  What
> pitfalls
> > exist that I should be thinking about?
> >
> > Thanks!
> > Andrew
> >
>

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