Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/2868#discussion_r19173742
--- Diff:
mllib/src/main/scala/org/apache/spark/mllib/tree/impl/NodeIdCache.scala ---
@@ -0,0 +1,171 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package org.apache.spark.mllib.tree.impl
+
+import scala.collection.mutable
+
+import org.apache.spark.rdd.RDD
+import org.apache.spark.annotation.DeveloperApi
+import org.apache.spark.mllib.tree.configuration.FeatureType._
+import spire.implicits._
+import org.apache.spark.storage.StorageLevel
+import org.apache.spark.mllib.tree.model.{Bin, Split}
+
+/**
+ * :: DeveloperApi ::
+ * This is used by the node id cache to find the child id that a data
point would belong to.
+ * @param split Split information.
+ * @param leftChildIndex Left child index.
+ * @param rightChildIndex Right child index.
+ */
+@DeveloperApi
+private[tree] case class NodeIndexUpdater(
+ split: Split,
+ leftChildIndex: Int,
+ rightChildIndex: Int) {
+ /**
+ * Determine a child node index based on the feature value and the split.
+ * @param binnedFeatures Binned feature values.
+ * @param bins Bin information to convert the bin indices to approximate
feature values.
+ * @return Child node index to update to.
+ */
+ def updateNodeIndex(binnedFeatures: Array[Int], bins:
Array[Array[Bin]]): Int = {
+ if (split.featureType == Continuous) {
+ val featureIndex = split.feature
+ val binIndex = binnedFeatures(featureIndex)
+ val featureValueUpperBound =
bins(featureIndex)(binIndex).highSplit.threshold
+ if (featureValueUpperBound <= split.threshold) {
+ leftChildIndex
+ } else {
+ rightChildIndex
+ }
+ } else {
+ if
(split.categories.contains(binnedFeatures(split.feature).toDouble)) {
+ leftChildIndex
+ } else {
+ rightChildIndex
+ }
+ }
+ }
+}
+
+/**
+ * A given TreePoint would belong to a particular node per tree.
+ * This is used to keep track of which node for a particular tree that a
TreePoint belongs to.
+ * A separate RDD of Array[Int] needs to be maintained and updated at each
iteration.
+ * @param data The RDD of training rows.
+ * @param cur The initial values in the cache
+ * (should be an Array of all 1's (meaning the root nodes)).
+ * @param checkpointDir The checkpoint directory where
+ * the checkpointed files will be stored.
+ * @param checkpointInterval The checkpointing interval
+ * (how often should the cache be checkpointed.).
+ */
+@DeveloperApi
+private[tree] class NodeIdCache(
+ val data: RDD[BaggedPoint[TreePoint]],
+ var cur: RDD[Array[Int]],
+ val checkpointDir: Option[String],
+ val checkpointInterval: Int) {
+
+ // To keep track of the past checkpointed RDDs.
+ val checkpointQueue = mutable.Queue[RDD[Array[Int]]]()
+ var rddUpdateCount = 0
+ if (checkpointDir != None) {
+ cur.sparkContext.setCheckpointDir(checkpointDir.get)
+ }
+
+ /**
+ * Update the node index values in the cache.
+ * This updates the RDD and its lineage.
+ * TODO: Passing bin information to executors seems unnecessary and
costly.
+ * @param nodeIdUpdaters A map of node index updaters.
+ * The key is the indices of nodes that we want to
update.
+ * @param bins Bin information needed to find child node indices.
+ */
+ def updateNodeIndices(
+ nodeIdUpdaters: Array[Map[Int, NodeIndexUpdater]],
+ bins: Array[Array[Bin]]): Unit = {
+ val updatedRDD = data.zip(cur).map {
+ dataPoint => {
+ cfor(0)(_ < nodeIdUpdaters.length, _ + 1)(
--- End diff --
I second that, especially if it eliminates the dependence on spire (since
spire is not used elsewhere in Spark).
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