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https://issues.apache.org/jira/browse/SPARK-21624?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16143996#comment-16143996
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Apache Spark commented on SPARK-21624:
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User 'mpjlu' has created a pull request for this issue:
https://github.com/apache/spark/pull/18904
> Optimize communication cost of RF/GBT/DT
> ----------------------------------------
>
> Key: SPARK-21624
> URL: https://issues.apache.org/jira/browse/SPARK-21624
> Project: Spark
> Issue Type: Improvement
> Components: ML, MLlib
> Affects Versions: 2.3.0
> Reporter: Peng Meng
>
> {quote}The implementation of RF is bound by either the cost of statistics
> computation on workers or by communicating the sufficient statistics.{quote}
> The statistics are stored in allStats:
> {code:java}
> /**
> * Flat array of elements.
> * Index for start of stats for a (feature, bin) is:
> * index = featureOffsets(featureIndex) + binIndex * statsSize
> */
> private var allStats: Array[Double] = new Array[Double](allStatsSize)
> {code}
> The size of allStats maybe very large, and it can be very sparse, especially
> on the nodes that near the leave of the tree.
> I have changed allStats from Array to SparseVector, my tests show the
> communication is down by about 50%.
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