Github user thvasilo commented on a diff in the pull request:
https://github.com/apache/flink/pull/710#discussion_r32943140
--- Diff:
flink-staging/flink-ml/src/main/scala/org/apache/flink/ml/tree/Tree.scala ---
@@ -0,0 +1,327 @@
+/*
+ * 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.flink.ml.tree
+
+import java.util
+
+import org.apache.flink.ml.math.{ContinuousHistogram, OnlineHistogram,
Vector}
+
+import scala.collection.mutable
+
+/** Tree structure. This is kind of maintained in an unconventional way.
+ * We provide direct access to all nodes
+ * The obvious assumption is that child of i are 2*i and 2*i+1, while
parent of i is i/2
+ *
+ */
+class Tree(
+ val treeID: Int,
+ val nodes: mutable.HashMap[Int, Node],
+ val config: TreeConfiguration
+ ) extends Serializable {
+
+ override def toString: String = {
+ var ret = s"Tree ID=$treeID\nConfiguration:\n$config \nTree
Structure:\n"
+ for (i <- 1 to Math.pow(2, 20).toInt) {
+ if (nodes.get(i).nonEmpty) {
+ ret = ret + nodes.get(i).get.toString + "\n"
+ }
+ }
+ ret
+ }
+
+ /** Determines which node of the tree this vector will go to
+ * If predict at any node is -1 and it has a split, we'll go down
recursively
+ *
+ */
+ def filter(vector: Vector): (Int, Double) = {
+ var node: Node = nodes.get(1).get
+ while (node.predict.round.toInt == -1 && node.split.nonEmpty) {
+ if (node.split.get.getSplitDirection(vector)) {
+ node = nodes.get(2 * node.id).get
+ }
+ else {
+ node = nodes.get(2 * node.id + 1).get
+ }
+ }
+ (node.id, node.predict)
+ }
+
+ /** Splits the tree based on the histograms provided.
+ * Returns an array of node ids which were split in the process
+ *
+ */
+ def split(histogram: util.List[(Int, Int, Double, OnlineHistogram)]):
Array[Int] = {
+ val h = new mutable.HashMap[(Int, Int, Double), OnlineHistogram]()
+ for (i <- 0 to histogram.size() - 1) {
+ val ele = histogram.get(i)
+ h.put((ele._1, ele._2, ele._3), ele._4)
+ }
+ val (splits, activeNodes) = calculateSplits(h)
+
+
+ // first, every unlabeled leaf node must have sent something.
+ // If not, its sibling will be stuck forever
+ val finalNodes = new mutable.HashMap[Int, Int]()
+ activeNodes.keysIterator.foreach(
+ x => {
+ // since this node received instances, it's sibling also must have
done so
+ // for the root node, which happens only at level zero, there is
no sibling. So just add it
+ if (x != 1) {
+ val y = 2 * (x / 2) + 1 - x % 2
+ if (activeNodes.get(y).isEmpty) {
+ finalNodes.put(x, 1)
+ } else {
+ finalNodes.put(x, -1)
+ }
+ } else {
+ finalNodes.put(x, -1)
+ }
+ }
+ )
+ evaluateNodes(finalNodes, splits, h)
+ }
+
+ private def evaluateNodes(
--- End diff --
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