Github user squito commented on a diff in the pull request:
https://github.com/apache/spark/pull/16867#discussion_r106833868
--- Diff:
core/src/main/scala/org/apache/spark/util/collection/MedianHeap.scala ---
@@ -0,0 +1,95 @@
+/*
+ * 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.util.collection
+
+import scala.collection.mutable.PriorityQueue
+
+/**
+ * MedianHeap is designed to be used to quickly track the median of a
group of numbers
+ * that may contain duplicates. Inserting a new number has O(log n) time
complexity and
+ * determining the median has O(1) time complexity.
+ * The basic idea is to maintain two heaps: a smallerHalf and a
largerHalf. The smallerHalf
+ * stores the smaller half of all numbers while the largerHalf stores the
larger half.
+ * The sizes of two heaps need to be balanced each time when a new number
is inserted so
+ * that their sizes will not be different by more than 1. Therefore each
time when
+ * findMedian() is called we check if two heaps have the same size. If
they do, we should
+ * return the average of the two top values of heaps. Otherwise we return
the top of the
+ * heap which has one more element.
+ */
+
+private[spark] class MedianHeap(implicit val ord: Ordering[Double]) {
+
+ // Stores all the numbers less than the current median in a smallerHalf,
+ // i.e median is the maximum, at the root
+ private[this] var smallerHalf = PriorityQueue.empty[Double](ord)
+
+ // Stores all the numbers greater than the current median in a
largerHalf,
+ // i.e median is the minimum, at the root
+ private[this] var largerHalf = PriorityQueue.empty[Double](ord.reverse)
+
+ // Returns if there is no element in MedianHeap.
+ def isEmpty(): Boolean = {
+ smallerHalf.isEmpty && largerHalf.isEmpty
+ }
+
+ // Size of MedianHeap.
+ def size(): Int = {
+ smallerHalf.size + largerHalf.size
+ }
+
+ // Insert a new number into MedianHeap.
+ def insert(x: Double): Unit = {
+ // If both heaps are empty, we arbitrarily insert it into a heap,
let's say, the largerHalf.
+ if (isEmpty) {
+ largerHalf.enqueue(x)
+ } else {
+ // If the number is larger than current median, it should be
inserted into largerHalf,
+ // otherwise smallerHalf.
+ if (x > median) {
+ largerHalf.enqueue(x)
+ } else {
+ smallerHalf.enqueue(x)
+ }
+ }
+ rebalance()
+ }
+
+ // Re-balance the heaps.
+ private[this] def rebalance(): Unit = {
+ if (largerHalf.size - smallerHalf.size > 1) {
+ smallerHalf.enqueue(largerHalf.dequeue())
+ }
+ if (smallerHalf.size - largerHalf.size > 1) {
+ largerHalf.enqueue(smallerHalf.dequeue)
+ }
+ }
+
+ // Returns the median of the numbers.
+ def median: Double = {
--- End diff --
minor: I find comments which basically just restate the method name to be
pretty pointless. I'd only include them if they add something else, eg.
preconditions, or complexity, etc. Mostly I'd say they're not necessary for
any of the methods here.
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