[GitHub] spark pull request #18904: [SPARK-21624]optimzie RF communicaiton cost

2018-01-15 Thread mpjlu
Github user mpjlu closed the pull request at:

https://github.com/apache/spark/pull/18904


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[GitHub] spark pull request #18904: [SPARK-21624]optimzie RF communicaiton cost

2017-08-10 Thread mpjlu
GitHub user mpjlu opened a pull request:

https://github.com/apache/spark/pull/18904

[SPARK-21624]optimzie RF communicaiton cost

## What changes were proposed in this pull request?

The implementation of RF is bound by either the cost of statistics 
computation on workers or by communicating the sufficient statistics.
This PR will focus on optimizing communication cost.
The statistics are stored in allStats:
`  private var allStats: Array[Double] = new Array[Double](allStatsSize)`
In real use case, the size of allStats is very large, and it can be very 
sparse, especially on the nodes that near the leave of the tree. 
It is better to change allStats from Array to SparseVector before shufffle.
My tests show the communication is down by about **50% to 90%** with this 
PR. 
Test cases: 
1000 features * 200Bins* 2 label, 
1000 features * 50Bins * 2label
1 features * 200Bins * 2 label
featureSubsetStrategy: auto, 0.2, 0.1
All test cases with the config: spark.shuffle.compress=true.

## How was this patch tested?
The exist UT



You can merge this pull request into a Git repository by running:

$ git pull https://github.com/mpjlu/spark optRFcomm

Alternatively you can review and apply these changes as the patch at:

https://github.com/apache/spark/pull/18904.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 #18904


commit 35d1f244f918bd8ea7fe7fdf10796a64e7a62fc9
Author: Peng Meng 
Date:   2017-08-10T07:19:59Z

optimzie RF communicaiton cost




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