Github user sethah commented on a diff in the pull request:
https://github.com/apache/spark/pull/10231#discussion_r47165377
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tree/impl/RandomForest.scala ---
@@ -842,60 +842,63 @@ private[ml] object RandomForest extends Logging {
1.0
}
logDebug("fraction of data used for calculating quantiles = " +
fraction)
- input.sample(withReplacement = false, fraction, new
XORShiftRandom(seed).nextInt()).collect()
+ input.sample(withReplacement = false, fraction, new
XORShiftRandom(seed).nextInt())
} else {
- new Array[LabeledPoint](0)
+ input.sparkContext.emptyRDD[LabeledPoint]
}
- val splits = new Array[Array[Split]](numFeatures)
-
- // Find all splits.
- // Iterate over all features.
- var featureIndex = 0
- while (featureIndex < numFeatures) {
- if (metadata.isContinuous(featureIndex)) {
- val featureSamples = sampledInput.map(_.features(featureIndex))
- val featureSplits = findSplitsForContinuousFeature(featureSamples,
metadata, featureIndex)
+ findSplitsBinsBySorting(sampledInput, metadata, continuousFeatures)
+ }
- val numSplits = featureSplits.length
- logDebug(s"featureIndex = $featureIndex, numSplits = $numSplits")
- splits(featureIndex) = new Array[Split](numSplits)
+ private def findSplitsBinsBySorting(
+ input: RDD[LabeledPoint],
+ metadata: DecisionTreeMetadata,
+ continuousFeatures: IndexedSeq[Int]): Array[Array[Split]] = {
+
+ val continuousSplits = {
+ // reduce the parallelism for split computations when there are less
+ // continuous features than input partitions. this prevents tasks
from
+ // being spun up that will definitely do no work.
+ val numPartitions = math.min(continuousFeatures.length,
input.partitions.length)
+
+ input
+ .flatMap(point => continuousFeatures.map(idx => (idx,
point.features(idx))))
+ .groupByKey(numPartitions)
+ .map { case (idx, samples) =>
+ val thresholds = findSplitsForContinuousFeature(samples.toArray,
metadata, idx)
+ val splits: Array[Split] = thresholds.map(thresh => new
ContinuousSplit(idx, thresh))
--- End diff --
Fixed.
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