GitHub user rxin opened a pull request:
https://github.com/apache/spark/pull/229
Use Guava's top k implementation rather than our BoundedPriorityQueue based
implementation
Also updated the documentation for top and takeOrdered.
On my simple test of sorting 100 million (Int, Int) tuples using Spark,
Guava's top k implementation (in Ordering) is much faster than the
BoundedPriorityQueue implementation for roughly sorted input (10 - 20X faster),
and still faster for purely random input (2 - 5X).
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/rxin/spark takeOrdered
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/229.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #229
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commit a1da19d69d3f6eecf6c57ef0e32267fe5bd02096
Author: Reynold Xin <r...@apache.org>
Date: 2014-03-25T21:49:15Z
Use Guava's top k implementation rather than our BoundedPriorityQueue based
implementation. Also updated the documentation for top and takeOrdered.
Guava's top k implementation (in Ordering) is much faster than the
BoundedPriorityQueue implementation for roughly sorted input (10 - 20X faster),
and still faster for purely random input (2 - 5X).
commit 723c29403b3662bb4866669cdf8411a8cf24597b
Author: Reynold Xin <r...@apache.org>
Date: 2014-03-25T21:56:54Z
Doc update.
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