Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/2868#discussion_r19178115
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/tree/DecisionTree.scala ---
@@ -553,7 +589,26 @@ object DecisionTree extends Serializable with Logging {
// Finally, only best Splits for nodes are collected to driver to
construct decision tree.
val nodeToFeatures = getNodeToFeatures(treeToNodeToIndexInfo)
val nodeToFeaturesBc = input.sparkContext.broadcast(nodeToFeatures)
- val nodeToBestSplits =
+
+ val partitionAggregates = if (useNodeIdCache) {
+ input.zip(nodeIdCache.get.cur).mapPartitions { points =>
+ // Construct a nodeStatsAggregators array to hold node aggregate
stats,
+ // each node will have a nodeStatsAggregator
+ val nodeStatsAggregators = Array.tabulate(numNodes) { nodeIndex =>
+ val featuresForNode = nodeToFeaturesBc.value.flatMap {
nodeToFeatures =>
+ Some(nodeToFeatures(nodeIndex))
+ }
+ new DTStatsAggregator(metadata, featuresForNode)
+ }
+
+ // iterator all instances in current partition and update
aggregate stats
+ points.foreach(binSeqOpWithNodeIdCache(nodeStatsAggregators, _))
--- End diff --
(from above) You can just test ```useNodeIdCache``` at this line. That
should reduce code duplication.
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