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GitHub Repository: PojavLauncherTeam/mobile
Path: blob/master/test/jdk/java/util/Arrays/SortingLongBenchmarkTestJMH.java
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/*
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* Copyright 2015 Goldman Sachs.
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* Copyright (c) 2015, Oracle and/or its affiliates. All rights reserved.
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* DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER.
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*
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* This code is free software; you can redistribute it and/or modify it
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* under the terms of the GNU General Public License version 2 only, as
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* published by the Free Software Foundation.
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*
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* This code is distributed in the hope that it will be useful, but WITHOUT
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* ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
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* FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
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* version 2 for more details (a copy is included in the LICENSE file that
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* accompanied this code).
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*
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* You should have received a copy of the GNU General Public License version
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* 2 along with this work; if not, write to the Free Software Foundation,
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* Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
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*
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* Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA
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* or visit www.oracle.com if you need additional information or have any
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* questions.
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*/
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import org.openjdk.jmh.annotations.Benchmark;
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import org.openjdk.jmh.annotations.BenchmarkMode;
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import org.openjdk.jmh.annotations.Measurement;
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import org.openjdk.jmh.annotations.Mode;
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import org.openjdk.jmh.annotations.OutputTimeUnit;
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import org.openjdk.jmh.annotations.Param;
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import org.openjdk.jmh.annotations.Scope;
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import org.openjdk.jmh.annotations.Setup;
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import org.openjdk.jmh.annotations.State;
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import org.openjdk.jmh.annotations.Warmup;
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import java.util.ArrayList;
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import java.util.Arrays;
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import java.util.HashSet;
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import java.util.List;
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import java.util.Random;
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import java.util.Set;
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import java.util.concurrent.TimeUnit;
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@State(Scope.Thread)
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@BenchmarkMode(Mode.Throughput)
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@OutputTimeUnit(TimeUnit.SECONDS)
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public class SortingLongBenchmarkTestJMH {
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private static final int QUICKSORT_THRESHOLD = 286;
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private static final int MAX_RUN_COUNT = 67;
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private static final int INSERTION_SORT_THRESHOLD = 47;
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public static final int MAX_VALUE = 1_000_000;
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@Param({"pairFlipZeroPairFlip", "descendingAscending", "zeroHi", "hiZeroLow", "hiFlatLow", "identical",
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"randomDups", "randomNoDups", "sortedReversedSorted", "pairFlip", "endLessThan"})
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public String listType;
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private long[] array;
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private static final int LIST_SIZE = 10_000_000;
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public static final int NUMBER_OF_ITERATIONS = 10;
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@Setup
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public void setUp() {
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Random random = new Random(123456789012345L);
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this.array = new long[LIST_SIZE];
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int threeQuarters = (int) (LIST_SIZE * 0.75);
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if ("zeroHi".equals(this.listType)) {
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for (int i = 0; i < threeQuarters; i++) {
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this.array[i] = 0;
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}
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int k = 1;
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for (int i = threeQuarters; i < LIST_SIZE; i++) {
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this.array[i] = k;
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k++;
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}
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}
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else if ("hiFlatLow".equals(this.listType)) {
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int oneThird = LIST_SIZE / 3;
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for (int i = 0; i < oneThird; i++) {
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this.array[i] = i;
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}
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int twoThirds = oneThird * 2;
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int constant = oneThird - 1;
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for (int i = oneThird; i < twoThirds; i++) {
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this.array[i] = constant;
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}
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for (int i = twoThirds; i < LIST_SIZE; i++) {
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this.array[i] = constant - i + twoThirds;
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}
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}
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else if ("hiZeroLow".equals(this.listType)) {
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int oneThird = LIST_SIZE / 3;
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for (int i = 0; i < oneThird; i++) {
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this.array[i] = i;
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}
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int twoThirds = oneThird * 2;
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for (int i = oneThird; i < twoThirds; i++) {
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this.array[i] = 0;
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}
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for (int i = twoThirds; i < LIST_SIZE; i++) {
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this.array[i] = oneThird - i + twoThirds;
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}
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}
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else if ("identical".equals(this.listType)) {
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for (int i = 0; i < LIST_SIZE; i++) {
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this.array[i] = 0;
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}
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}
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else if ("randomDups".equals(this.listType)) {
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for (int i = 0; i < LIST_SIZE; i++) {
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this.array[i] = random.nextInt(1000);
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}
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}
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else if ("randomNoDups".equals(this.listType)) {
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Set<Integer> set = new HashSet<>();
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while (set.size() < LIST_SIZE + 1) {
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set.add(random.nextInt());
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}
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List<Integer> list = new ArrayList<>(LIST_SIZE);
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list.addAll(set);
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for (int i = 0; i < LIST_SIZE; i++) {
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this.array[i] = list.get(i);
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}
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}
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else if ("sortedReversedSorted".equals(this.listType)) {
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for (int i = 0; i < LIST_SIZE / 2; i++) {
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this.array[i] = i;
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}
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int num = 0;
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for (int i = LIST_SIZE / 2; i < LIST_SIZE; i++) {
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this.array[i] = LIST_SIZE - num;
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num++;
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}
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}
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else if ("pairFlip".equals(this.listType)) {
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for (int i = 0; i < LIST_SIZE; i++) {
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this.array[i] = i;
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}
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for (int i = 0; i < LIST_SIZE; i += 2) {
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long temp = this.array[i];
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this.array[i] = this.array[i + 1];
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this.array[i + 1] = temp;
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}
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}
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else if ("endLessThan".equals(this.listType)) {
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for (int i = 0; i < LIST_SIZE - 1; i++) {
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this.array[i] = 3;
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}
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this.array[LIST_SIZE - 1] = 1;
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}
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else if ("pairFlipZeroPairFlip".equals(this.listType)) {
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//pairflip
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for (int i = 0; i < 64; i++) {
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this.array[i] = i;
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}
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for (int i = 0; i < 64; i += 2) {
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long temp = this.array[i];
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this.array[i] = this.array[i + 1];
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this.array[i + 1] = temp;
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}
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//zero
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for (int i = 64; i < this.array.length - 64; i++) {
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this.array[i] = 0;
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}
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//pairflip
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for (int i = this.array.length - 64; i < this.array.length; i++) {
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this.array[i] = i;
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}
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for (int i = this.array.length - 64; i < this.array.length; i += 2) {
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long temp = this.array[i];
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this.array[i] = this.array[i + 1];
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this.array[i + 1] = temp;
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}
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}
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else if ("pairFlipOneHundredPairFlip".equals(this.listType)) {
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//10, 5
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for (int i = 0; i < 64; i++) {
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if (i % 2 == 0) {
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this.array[i] = 10;
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}
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else {
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this.array[i] = 5;
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}
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}
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//100
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for (int i = 64; i < this.array.length - 64; i++) {
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this.array[i] = 100;
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}
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//10, 5
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for (int i = this.array.length - 64; i < this.array.length; i++) {
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if (i % 2 == 0) {
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this.array[i] = 10;
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}
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else {
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this.array[i] = 5;
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}
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}
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}
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}
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@Warmup(iterations = 20)
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@Measurement(iterations = 10)
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@Benchmark
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public void sortNewWay() {
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for (int i = 0; i < NUMBER_OF_ITERATIONS; i++) {
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SortingLongTestJMH.sort(this.array, 0, this.array.length - 1, null, 0, 0);
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}
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}
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@Warmup(iterations = 20)
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@Measurement(iterations = 10)
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@Benchmark
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public void sortOldWay() {
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for (int i = 0; i < NUMBER_OF_ITERATIONS; i++) {
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Arrays.sort(this.array);
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}
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}
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/**
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* Sorts the specified range of the array using the given
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* workspace array slice if possible for merging
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*
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* @param a the array to be sorted
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* @param left the index of the first element, inclusive, to be sorted
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* @param right the index of the last element, inclusive, to be sorted
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* @param work a workspace array (slice)
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* @param workBase origin of usable space in work array
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* @param workLen usable size of work array
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*/
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static void sort(long[] a, int left, int right,
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long[] work, int workBase, int workLen) {
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// Use Quicksort on small arrays
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if (right - left < QUICKSORT_THRESHOLD) {
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SortingLongTestJMH.sort(a, left, right, true);
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return;
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}
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/*
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* Index run[i] is the start of i-th run
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* (ascending or descending sequence).
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*/
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int[] run = new int[MAX_RUN_COUNT + 1];
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int count = 0;
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run[0] = left;
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// Check if the array is nearly sorted
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for (int k = left; k < right; run[count] = k) {
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while (k < right && a[k] == a[k + 1])
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k++;
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if (k == right) break;
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if (a[k] < a[k + 1]) { // ascending
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while (++k <= right && a[k - 1] <= a[k]) ;
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}
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else if (a[k] > a[k + 1]) { // descending
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while (++k <= right && a[k - 1] >= a[k]) ;
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for (int lo = run[count] - 1, hi = k; ++lo < --hi; ) {
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long t = a[lo];
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a[lo] = a[hi];
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a[hi] = t;
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}
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}
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if (run[count] > left && a[run[count]] >= a[run[count] - 1]) {
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count--;
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}
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/*
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* The array is not highly structured,
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* use Quicksort instead of merge sort.
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*/
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if (++count == MAX_RUN_COUNT) {
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sort(a, left, right, true);
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return;
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}
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}
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// Check special cases
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// Implementation note: variable "right" is increased by 1.
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if (run[count] == right++) {
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run[++count] = right;
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}
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if (count <= 1) { // The array is already sorted
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return;
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}
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// Determine alternation base for merge
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byte odd = 0;
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for (int n = 1; (n <<= 1) < count; odd ^= 1) {
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}
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// Use or create temporary array b for merging
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long[] b; // temp array; alternates with a
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int ao, bo; // array offsets from 'left'
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int blen = right - left; // space needed for b
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if (work == null || workLen < blen || workBase + blen > work.length) {
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work = new long[blen];
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workBase = 0;
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}
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if (odd == 0) {
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System.arraycopy(a, left, work, workBase, blen);
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b = a;
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bo = 0;
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a = work;
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ao = workBase - left;
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}
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else {
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b = work;
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ao = 0;
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bo = workBase - left;
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}
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// Merging
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for (int last; count > 1; count = last) {
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for (int k = (last = 0) + 2; k <= count; k += 2) {
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int hi = run[k], mi = run[k - 1];
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for (int i = run[k - 2], p = i, q = mi; i < hi; ++i) {
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if (q >= hi || p < mi && a[p + ao] <= a[q + ao]) {
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b[i + bo] = a[p++ + ao];
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}
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else {
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b[i + bo] = a[q++ + ao];
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}
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}
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run[++last] = hi;
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}
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if ((count & 1) != 0) {
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for (int i = right, lo = run[count - 1]; --i >= lo;
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b[i + bo] = a[i + ao]
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) {
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}
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run[++last] = right;
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}
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long[] t = a;
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a = b;
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b = t;
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int o = ao;
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ao = bo;
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bo = o;
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}
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}
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/**
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* Sorts the specified range of the array by Dual-Pivot Quicksort.
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*
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* @param a the array to be sorted
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* @param left the index of the first element, inclusive, to be sorted
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* @param right the index of the last element, inclusive, to be sorted
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* @param leftmost indicates if this part is the leftmost in the range
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*/
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private static void sort(long[] a, int left, int right, boolean leftmost) {
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int length = right - left + 1;
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// Use insertion sort on tiny arrays
353
if (length < INSERTION_SORT_THRESHOLD) {
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if (leftmost) {
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/*
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* Traditional (without sentinel) insertion sort,
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* optimized for server VM, is used in case of
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* the leftmost part.
359
*/
360
for (int i = left, j = i; i < right; j = ++i) {
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long ai = a[i + 1];
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while (ai < a[j]) {
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a[j + 1] = a[j];
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if (j-- == left) {
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break;
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}
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}
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a[j + 1] = ai;
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}
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}
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else {
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/*
373
* Skip the longest ascending sequence.
374
*/
375
do {
376
if (left >= right) {
377
return;
378
}
379
}
380
while (a[++left] >= a[left - 1]);
381
382
/*
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* Every element from adjoining part plays the role
384
* of sentinel, therefore this allows us to avoid the
385
* left range check on each iteration. Moreover, we use
386
* the more optimized algorithm, so called pair insertion
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* sort, which is faster (in the context of Quicksort)
388
* than traditional implementation of insertion sort.
389
*/
390
for (int k = left; ++left <= right; k = ++left) {
391
long a1 = a[k], a2 = a[left];
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393
if (a1 < a2) {
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a2 = a1;
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a1 = a[left];
396
}
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while (a1 < a[--k]) {
398
a[k + 2] = a[k];
399
}
400
a[++k + 1] = a1;
401
402
while (a2 < a[--k]) {
403
a[k + 1] = a[k];
404
}
405
a[k + 1] = a2;
406
}
407
long last = a[right];
408
409
while (last < a[--right]) {
410
a[right + 1] = a[right];
411
}
412
a[right + 1] = last;
413
}
414
return;
415
}
416
417
// Inexpensive approximation of length / 7
418
int seventh = (length >> 3) + (length >> 6) + 1;
419
420
/*
421
* Sort five evenly spaced elements around (and including) the
422
* center element in the range. These elements will be used for
423
* pivot selection as described below. The choice for spacing
424
* these elements was empirically determined to work well on
425
* a wide variety of inputs.
426
*/
427
int e3 = (left + right) >>> 1; // The midpoint
428
int e2 = e3 - seventh;
429
int e1 = e2 - seventh;
430
int e4 = e3 + seventh;
431
int e5 = e4 + seventh;
432
433
// Sort these elements using insertion sort
434
if (a[e2] < a[e1]) {
435
long t = a[e2];
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a[e2] = a[e1];
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a[e1] = t;
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}
439
440
if (a[e3] < a[e2]) {
441
long t = a[e3];
442
a[e3] = a[e2];
443
a[e2] = t;
444
if (t < a[e1]) {
445
a[e2] = a[e1];
446
a[e1] = t;
447
}
448
}
449
if (a[e4] < a[e3]) {
450
long t = a[e4];
451
a[e4] = a[e3];
452
a[e3] = t;
453
if (t < a[e2]) {
454
a[e3] = a[e2];
455
a[e2] = t;
456
if (t < a[e1]) {
457
a[e2] = a[e1];
458
a[e1] = t;
459
}
460
}
461
}
462
if (a[e5] < a[e4]) {
463
long t = a[e5];
464
a[e5] = a[e4];
465
a[e4] = t;
466
if (t < a[e3]) {
467
a[e4] = a[e3];
468
a[e3] = t;
469
if (t < a[e2]) {
470
a[e3] = a[e2];
471
a[e2] = t;
472
if (t < a[e1]) {
473
a[e2] = a[e1];
474
a[e1] = t;
475
}
476
}
477
}
478
}
479
480
// Pointers
481
int less = left; // The index of the first element of center part
482
int great = right; // The index before the first element of right part
483
484
if (a[e1] != a[e2] && a[e2] != a[e3] && a[e3] != a[e4] && a[e4] != a[e5]) {
485
/*
486
* Use the second and fourth of the five sorted elements as pivots.
487
* These values are inexpensive approximations of the first and
488
* second terciles of the array. Note that pivot1 <= pivot2.
489
*/
490
long pivot1 = a[e2];
491
long pivot2 = a[e4];
492
493
/*
494
* The first and the last elements to be sorted are moved to the
495
* locations formerly occupied by the pivots. When partitioning
496
* is complete, the pivots are swapped back into their final
497
* positions, and excluded from subsequent sorting.
498
*/
499
a[e2] = a[left];
500
a[e4] = a[right];
501
502
/*
503
* Skip elements, which are less or greater than pivot values.
504
*/
505
while (a[++less] < pivot1) {
506
}
507
while (a[--great] > pivot2) {
508
}
509
510
/*
511
* Partitioning:
512
*
513
* left part center part right part
514
* +--------------------------------------------------------------+
515
* | < pivot1 | pivot1 <= && <= pivot2 | ? | > pivot2 |
516
* +--------------------------------------------------------------+
517
* ^ ^ ^
518
* | | |
519
* less k great
520
*
521
* Invariants:
522
*
523
* all in (left, less) < pivot1
524
* pivot1 <= all in [less, k) <= pivot2
525
* all in (great, right) > pivot2
526
*
527
* Pointer k is the first index of ?-part.
528
*/
529
outer:
530
for (int k = less - 1; ++k <= great; ) {
531
long ak = a[k];
532
if (ak < pivot1) { // Move a[k] to left part
533
a[k] = a[less];
534
/*
535
* Here and below we use "a[i] = b; i++;" instead
536
* of "a[i++] = b;" due to performance issue.
537
*/
538
a[less] = ak;
539
++less;
540
}
541
else if (ak > pivot2) { // Move a[k] to right part
542
while (a[great] > pivot2) {
543
if (great-- == k) {
544
break outer;
545
}
546
}
547
if (a[great] < pivot1) { // a[great] <= pivot2
548
a[k] = a[less];
549
a[less] = a[great];
550
++less;
551
}
552
else { // pivot1 <= a[great] <= pivot2
553
a[k] = a[great];
554
}
555
/*
556
* Here and below we use "a[i] = b; i--;" instead
557
* of "a[i--] = b;" due to performance issue.
558
*/
559
a[great] = ak;
560
--great;
561
}
562
}
563
564
// Swap pivots into their final positions
565
a[left] = a[less - 1];
566
a[less - 1] = pivot1;
567
a[right] = a[great + 1];
568
a[great + 1] = pivot2;
569
570
// Sort left and right parts recursively, excluding known pivots
571
SortingLongTestJMH.sort(a, left, less - 2, leftmost);
572
SortingLongTestJMH.sort(a, great + 2, right, false);
573
574
/*
575
* If center part is too large (comprises > 4/7 of the array),
576
* swap internal pivot values to ends.
577
*/
578
if (less < e1 && e5 < great) {
579
/*
580
* Skip elements, which are equal to pivot values.
581
*/
582
while (a[less] == pivot1) {
583
++less;
584
}
585
586
while (a[great] == pivot2) {
587
--great;
588
}
589
590
/*
591
* Partitioning:
592
*
593
* left part center part right part
594
* +----------------------------------------------------------+
595
* | == pivot1 | pivot1 < && < pivot2 | ? | == pivot2 |
596
* +----------------------------------------------------------+
597
* ^ ^ ^
598
* | | |
599
* less k great
600
*
601
* Invariants:
602
*
603
* all in (*, less) == pivot1
604
* pivot1 < all in [less, k) < pivot2
605
* all in (great, *) == pivot2
606
*
607
* Pointer k is the first index of ?-part.
608
*/
609
outer:
610
for (int k = less - 1; ++k <= great; ) {
611
long ak = a[k];
612
if (ak == pivot1) { // Move a[k] to left part
613
a[k] = a[less];
614
a[less] = ak;
615
++less;
616
}
617
else if (ak == pivot2) { // Move a[k] to right part
618
while (a[great] == pivot2) {
619
if (great-- == k) {
620
break outer;
621
}
622
}
623
if (a[great] == pivot1) { // a[great] < pivot2
624
a[k] = a[less];
625
/*
626
* Even though a[great] equals to pivot1, the
627
* assignment a[less] = pivot1 may be incorrect,
628
* if a[great] and pivot1 are floating-point zeros
629
* of different signs. Therefore in float and
630
* double sorting methods we have to use more
631
* accurate assignment a[less] = a[great].
632
*/
633
a[less] = pivot1;
634
++less;
635
}
636
else { // pivot1 < a[great] < pivot2
637
a[k] = a[great];
638
}
639
a[great] = ak;
640
--great;
641
}
642
}
643
}
644
645
// Sort center part recursively
646
SortingLongTestJMH.sort(a, less, great, false);
647
}
648
else { // Partitioning with one pivot
649
/*
650
* Use the third of the five sorted elements as pivot.
651
* This value is inexpensive approximation of the median.
652
*/
653
long pivot = a[e3];
654
655
/*
656
* Partitioning degenerates to the traditional 3-way
657
* (or "Dutch National Flag") schema:
658
*
659
* left part center part right part
660
* +-------------------------------------------------+
661
* | < pivot | == pivot | ? | > pivot |
662
* +-------------------------------------------------+
663
* ^ ^ ^
664
* | | |
665
* less k great
666
*
667
* Invariants:
668
*
669
* all in (left, less) < pivot
670
* all in [less, k) == pivot
671
* all in (great, right) > pivot
672
*
673
* Pointer k is the first index of ?-part.
674
*/
675
for (int k = less; k <= great; ++k) {
676
if (a[k] == pivot) {
677
continue;
678
}
679
long ak = a[k];
680
if (ak < pivot) { // Move a[k] to left part
681
a[k] = a[less];
682
a[less] = ak;
683
++less;
684
}
685
else { // a[k] > pivot - Move a[k] to right part
686
while (a[great] > pivot) {
687
--great;
688
}
689
if (a[great] < pivot) { // a[great] <= pivot
690
a[k] = a[less];
691
a[less] = a[great];
692
++less;
693
}
694
else { // a[great] == pivot
695
/*
696
* Even though a[great] equals to pivot, the
697
* assignment a[k] = pivot may be incorrect,
698
* if a[great] and pivot are floating-point
699
* zeros of different signs. Therefore in float
700
* and double sorting methods we have to use
701
* more accurate assignment a[k] = a[great].
702
*/
703
a[k] = pivot;
704
}
705
a[great] = ak;
706
--great;
707
}
708
}
709
710
/*
711
* Sort left and right parts recursively.
712
* All elements from center part are equal
713
* and, therefore, already sorted.
714
*/
715
SortingLongTestJMH.sort(a, left, less - 1, leftmost);
716
SortingLongTestJMH.sort(a, great + 1, right, false);
717
}
718
}
719
720
private static void swap(long[] arr, int i, int j) {
721
long tmp = arr[i];
722
arr[i] = arr[j];
723
arr[j] = tmp;
724
}
725
}
726
727