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JonasKunzJonasKunz
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Fix tests, implement benchmarks
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‎benchmarks/src/main/java/org/elasticsearch/benchmark/exponentialhistogram/ExponentialHistogramGenerationBench.java‎

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@State(Scope.Thread)
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public class ExponentialHistogramGenerationBench {
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@Param({ "100", "500", "1000", "5000" })
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@Param({ "100", "500", "1000", "5000" , "10000", "20000"})
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int bucketCount;
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@Param({ "NORMAL", "GAUSSIAN" })

‎benchmarks/src/main/java/org/elasticsearch/benchmark/exponentialhistogram/ExponentialHistogramMergeBench.java‎

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/*
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* Copyright Elasticsearch B.V. and/or licensed to Elasticsearch B.V. under one
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* or more contributor license agreements. Licensed under the "Elastic License
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* 2.0", the "GNU Affero General Public License v3.0 only", and the "Server Side
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* Public License v 1"; you may not use this file except in compliance with, at
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* your election, the "Elastic License 2.0", the "GNU Affero General Public
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* License v3.0 only", or the "Server Side Public License, v 1".
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*/
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package org.elasticsearch.benchmark.exponentialhistogram;
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import org.elasticsearch.exponentialhistogram.ExponentialHistogram;
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import org.elasticsearch.exponentialhistogram.ExponentialHistogramGenerator;
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import org.elasticsearch.exponentialhistogram.ExponentialHistogramMerger;
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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.Fork;
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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.Threads;
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import org.openjdk.jmh.annotations.Warmup;
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import java.util.List;
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import java.util.Random;
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import java.util.concurrent.ThreadLocalRandom;
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import java.util.concurrent.TimeUnit;
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@BenchmarkMode(Mode.AverageTime)
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@OutputTimeUnit(TimeUnit.NANOSECONDS)
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@Warmup(iterations = 3, time = 3, timeUnit = TimeUnit.SECONDS)
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@Measurement(iterations = 5, time = 2, timeUnit = TimeUnit.SECONDS)
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@Fork(1)
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@Threads(1)
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@State(Scope.Thread)
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public class ExponentialHistogramMergeBench {
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@Param({ "1000", "5000" })
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int bucketCount;
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@Param({ "0.01", "0.1", "0.25", "0.5", "1.0", "2.0" })
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double mergedHistoSizeFactor;
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Random random;
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ExponentialHistogramMerger histoMerger;
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ExponentialHistogram[] toMerge = new ExponentialHistogram[10_000];
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@Setup
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public void setUp() {
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random = ThreadLocalRandom.current();
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histoMerger = new ExponentialHistogramMerger(bucketCount);
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ExponentialHistogramGenerator initial = new ExponentialHistogramGenerator(bucketCount);
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for (int j = 0; j < bucketCount; j++) {
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initial.add(Math.pow(1.001, j));
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}
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ExponentialHistogram initialHisto = initial.get();
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int cnt = getBucketCount(initialHisto);
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if (cnt < bucketCount) {
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throw new IllegalArgumentException("Expected bucket count to be " + bucketCount + ", but was " + cnt);
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}
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histoMerger.add(initialHisto);
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int dataPointSize = (int) Math.round(bucketCount * mergedHistoSizeFactor);
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for (int i = 0; i < toMerge.length; i++) {
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ExponentialHistogramGenerator generator = new ExponentialHistogramGenerator(dataPointSize);
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int bucketIndex = 0;
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for (int j = 0; j < dataPointSize; j++) {
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bucketIndex += 1 + random.nextInt(bucketCount) % (Math.max(1, bucketCount / dataPointSize));
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generator.add(Math.pow(1.001, bucketIndex));
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}
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toMerge[i] = generator.get();
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cnt = getBucketCount(toMerge[i]);
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if (cnt < dataPointSize) {
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throw new IllegalArgumentException("Expected bucket count to be " + dataPointSize + ", but was " + cnt);
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}
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}
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}
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private static int getBucketCount(ExponentialHistogram histo) {
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int cnt = 0;
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for (ExponentialHistogram.BucketIterator it : List.of(histo.negativeBuckets(), histo.positiveBuckets())) {
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while (it.hasNext()) {
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cnt++;
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it.advance();
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}
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}
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return cnt;
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}
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@State(Scope.Thread)
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public static class ThreadState {
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int index = 0;
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}
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@Benchmark
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@BenchmarkMode(Mode.AverageTime)
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@OutputTimeUnit(TimeUnit.MICROSECONDS)
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public void add(ThreadState state) {
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if (state.index >= toMerge.length) {
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state.index = 0;
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}
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histoMerger.add(toMerge[state.index++]);
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}
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}

libs/exponential-histogram/src/test/java/org/elasticsearch/exponentialhistogram/DownscaleStatsTest.java renamed to libs/exponential-histogram/src/test/java/org/elasticsearch/exponentialhistogram/DownscaleStatsTests.java

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import static org.hamcrest.MatcherAssert.assertThat;
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import static org.hamcrest.Matchers.equalTo;
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public class DownscaleStatsTest extends ESTestCase {
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public class DownscaleStatsTests extends ESTestCase {
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public void testExponential() {
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long[] values = IntStream.range(0, 100).mapToLong(i -> (long) Math.min(Integer.MAX_VALUE, Math.pow(1.1, i))).distinct().toArray();

libs/exponential-histogram/src/test/java/org/elasticsearch/exponentialhistogram/ExponentialHistogramMergerTest.java renamed to libs/exponential-histogram/src/test/java/org/elasticsearch/exponentialhistogram/ExponentialHistogramMergerTests.java

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import java.util.stream.Collectors;
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import java.util.stream.IntStream;
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import static org.elasticsearch.exponentialhistogram.FixedSizeExponentialHistogramTest.printMidpoints;
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import static org.elasticsearch.exponentialhistogram.FixedSizeExponentialHistogramTests.printMidpoints;
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import static org.hamcrest.Matchers.equalTo;
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public class ExponentialHistogramMergerTest extends ESTestCase {
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public class ExponentialHistogramMergerTests extends ESTestCase {
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public void testZeroThresholdCollapsesOverlappingBuckets() {
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FixedSizeExponentialHistogram first = new FixedSizeExponentialHistogram(100);

libs/exponential-histogram/src/test/java/org/elasticsearch/exponentialhistogram/ExponentialHistogramUtilsTest.java renamed to libs/exponential-histogram/src/test/java/org/elasticsearch/exponentialhistogram/ExponentialHistogramUtilsTests.java

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import static org.hamcrest.Matchers.equalTo;
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import static org.hamcrest.Matchers.lessThanOrEqualTo;
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public class ExponentialHistogramUtilsTest extends ESTestCase {
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public class ExponentialHistogramUtilsTests extends ESTestCase {
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public void testMaxValue() {
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assertThat(getMaximumScaleIncrease(Long.MAX_VALUE), equalTo(0));

libs/exponential-histogram/src/test/java/org/elasticsearch/exponentialhistogram/FixedSizeExponentialHistogramTest.java renamed to libs/exponential-histogram/src/test/java/org/elasticsearch/exponentialhistogram/FixedSizeExponentialHistogramTests.java

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import java.util.stream.IntStream;
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public class FixedSizeExponentialHistogramTest extends ESTestCase {
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public class FixedSizeExponentialHistogramTests extends ESTestCase {
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public void testPrintBuckets() {
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ExponentialHistogram first = ExponentialHistogramGenerator.createFor(0.01234, 42, 56789);

libs/exponential-histogram/src/test/java/org/elasticsearch/exponentialhistogram/PercentileAccuracyTest.java renamed to libs/exponential-histogram/src/test/java/org/elasticsearch/exponentialhistogram/PercentileAccuracyTests.java

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import static org.hamcrest.Matchers.closeTo;
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import static org.hamcrest.Matchers.lessThan;
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public class PercentileAccuracyTest extends ESTestCase {
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public class PercentileAccuracyTests extends ESTestCase {
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public static final double[] PERCENTILES_TO_TEST = { 0, 0.01, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95, 0.99, 1.0 };
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@@ -254,7 +254,7 @@ private double getMaximumRelativeError(double[] values, int bucketCount) {
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// only positive values
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double gammaSquare = Math.pow(largestPositive / smallestPositive, 2.0 / (bucketCount));
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return (gammaSquare - 1) / (gammaSquare + 1);
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} else if (largestAbsNegative == 0) {
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} else if (smallestAbsNegative == 0) {
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// only negative values
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double gammaSquare = Math.pow(largestAbsNegative / smallestAbsNegative, 2.0 / (bucketCount));
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return (gammaSquare - 1) / (gammaSquare + 1);

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