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From mengxr <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-3366][MLLIB]Compute best splits distrib...
Date Tue, 30 Sep 2014 18:12:29 GMT
Github user mengxr commented on a diff in the pull request:

    https://github.com/apache/spark/pull/2595#discussion_r18235839
  
    --- Diff: mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala ---
    @@ -518,30 +516,58 @@ object DecisionTree extends Serializable with Logging {
           agg
         }
     
    -    // Calculate bin aggregates.
    -    timer.start("aggregation")
    -    val binAggregates: DTStatsAggregator = {
    -      val initAgg = if (metadata.subsamplingFeatures) {
    -        new DTStatsAggregatorSubsampledFeatures(metadata, treeToNodeToIndexInfo)
    -      } else {
    -        new DTStatsAggregatorFixedFeatures(metadata, numNodes)
    -      }
    -      input.treeAggregate(initAgg)(binSeqOp, DTStatsAggregator.binCombOp)
    -    }
    -    timer.stop("aggregation")
    -
         // Calculate best splits for all nodes in the group
         timer.start("chooseSplits")
     
    +    // In each parition, iterate all instances and compute aggregate stats for each node,
    +    // yield an (nodeIndex, nodeAggregateStats) pair for each node.
    +    // After a `reduceByKey` operation,
    +    // stats of a node will be shuffled to a particular partition and be combined together,
    +    // then best splits for nodes are found there.
    +    // Finally, only best Splits for nodes are collected to driver to construct decision
tree.
    +    val nodeToBestSplits: Map[Int, (Split, InformationGainStats, Predict)] =
    +      input.mapPartitions(points => {
    +        // Construct a nodeStatsAggregators array to hold node aggregate stats,
    +        // each node will have a nodeStatsAggregator
    +        val numNodes = nodeToFeatures.keys.size
    +        val nodeStatsAggregators = new Array[NodeStatsAggregator](numNodes)
    --- End diff --
    
    use `Array.tabulate`


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