content: /*
   * 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.kafka.jmh.metrics;
  
  import org.apache.kafka.coordinator.common.runtime.HdrHistogram;
  import org.apache.kafka.server.metrics.KafkaYammerMetrics;
  
  import com.yammer.metrics.core.Histogram;
  import com.yammer.metrics.core.MetricName;
  
  import org.openjdk.jmh.annotations.Benchmark;
  import org.openjdk.jmh.annotations.BenchmarkMode;
  import org.openjdk.jmh.annotations.Fork;
  import org.openjdk.jmh.annotations.Group;
  import org.openjdk.jmh.annotations.GroupThreads;
  import org.openjdk.jmh.annotations.Level;
  import org.openjdk.jmh.annotations.Measurement;
  import org.openjdk.jmh.annotations.Mode;
  import org.openjdk.jmh.annotations.OutputTimeUnit;
  import org.openjdk.jmh.annotations.Scope;
  import org.openjdk.jmh.annotations.Setup;
  import org.openjdk.jmh.annotations.State;
  import org.openjdk.jmh.annotations.Threads;
  import org.openjdk.jmh.annotations.Warmup;
  
  import java.util.concurrent.ThreadLocalRandom;
  import java.util.concurrent.TimeUnit;
  
  @State(Scope.Benchmark)
  @Fork(value = 1)
  @Threads(10)
  @Warmup(iterations = 5)
  @Measurement(iterations = 5)
  @BenchmarkMode(Mode.AverageTime)
  @OutputTimeUnit(TimeUnit.NANOSECONDS)
  public class HistogramBenchmark {
  
      /*
       * This benchmark compares the performance of the most commonly used in the Kafka codebase
       * Yammer histogram and the new HdrHistogram. It does it by focusing on the write path in a
       * multiple writers, multiple readers scenario.
       *
       * The benchmark relies on JMH Groups which allows us to distribute the number of worker threads
       * to the different benchmark methods.
       */
  
      private static final long MAX_VALUE = TimeUnit.MINUTES.toMillis(1L);
  
      private Histogram yammerHistogram;
      private HdrHistogram hdrHistogram;
  
      @Setup(Level.Trial)
      public void setUp() {
          yammerHistogram = KafkaYammerMetrics.defaultRegistry().newHistogram(new MetricName("a", "", ""), true);
          hdrHistogram = new HdrHistogram(MAX_VALUE, 3);
      }
  
      /*
       * The write benchmark methods below are the core of the benchmark. They use ThreadLocalRandom
       * to generate values to record. This is much faster than the actual histogram recording, so
       * the benchmark results are representative of the histogram implementation.
       */
  
      @Benchmark
      @Group("runner")
      @GroupThreads(3)
      public void writeYammerHistogram() {
          yammerHistogram.update(ThreadLocalRandom.current().nextLong(MAX_VALUE));
      }
  
      @Benchmark
      @Group("runner")
      @GroupThreads(3)
      public void writeHdrHistogram() {
          hdrHistogram.record(ThreadLocalRandom.current().nextLong(MAX_VALUE));
      }
  
      /*
       * The read benchmark methods below are not real benchmark methods!
       * They are there only to simulate the concurrent exercise of the read and the write paths in
       * the histogram implementations (with the read path exercised significantly less often). The
       * measurements for these benchmark methods should be ignored as although not optimized away
       * (that's why the methods have a return value), they practically measure the cost of a
       * System.currentTimeMillis() call.
       */
  
      @Benchmark
      @Group("runner")
      @GroupThreads(2)
      public double readYammerHistogram() {
          long now = System.currentTimeMillis();
          if (now % 199 == 0) {
              return yammerHistogram.getSnapshot().get999thPercentile();
          }
          return now;
      }
  
      @Benchmark
      @Group("runner")
      @GroupThreads(2)
      public double readHdrHistogram() {
          long now = System.currentTimeMillis();
          if (now % 199 == 0) {
              return hdrHistogram.measurePercentile(now, 99.9);
          }
          return now;
      }
  }
  