code: /*
   * Copyright (c) 2016-present, RxJava Contributors.
   *
   * Licensed 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 io.reactivex.rxjava3.parallel;
  
  import java.util.Arrays;
  import java.util.concurrent.TimeUnit;
  
  import org.openjdk.jmh.annotations.*;
  import org.openjdk.jmh.infra.Blackhole;
  import org.reactivestreams.Publisher;
  
  import io.reactivex.rxjava3.core.*;
  import io.reactivex.rxjava3.flowables.GroupedFlowable;
  import io.reactivex.rxjava3.functions.Function;
  import io.reactivex.rxjava3.schedulers.Schedulers;
  
  @BenchmarkMode(Mode.Throughput)
  @Warmup(iterations = 5)
  @Measurement(iterations = 5, time = 1, timeUnit = TimeUnit.SECONDS)
  @Fork(value = 1, jvmArgsAppend = { "-XX:MaxInlineLevel=20" })
  @OutputTimeUnit(TimeUnit.SECONDS)
  @State(Scope.Thread)
  public class ParallelPerf implements Function<Integer, Integer> {
  
      @Param({"10000"})
      public int count;
  
      @Param({"1", "10", "100", "1000", "10000"})
      public int compute;
  
      @Param({"1", "2", "3", "4"})
      public int parallelism;
  
      Flowable<Integer> flatMap;
  
      Flowable<Integer> groupBy;
  
      Flowable<Integer> parallel;
  
      @Override
      public Integer apply(Integer t) {
          Blackhole.consumeCPU(compute);
          return t;
      }
  
      @Setup
      public void setup() {
  
          final int cpu = parallelism;
  
          Integer[] ints = new Integer[count];
          Arrays.fill(ints, 777);
  
          Flowable<Integer> source = Flowable.fromArray(ints);
  
          flatMap = source.flatMap(new Function<Integer, Publisher<Integer>>() {
              @Override
              public Publisher<Integer> apply(Integer v) {
                  return Flowable.just(v).subscribeOn(Schedulers.computation())
                          .map(ParallelPerf.this);
              }
          }, cpu);
  
          groupBy = source.groupBy(new Function<Integer, Integer>() {
              int i;
              @Override
              public Integer apply(Integer v) {
                  return (i++) % cpu;
              }
          })
          .flatMap(new Function<GroupedFlowable<Integer, Integer>, Publisher<Integer>>() {
              @Override
              public Publisher<Integer> apply(GroupedFlowable<Integer, Integer> g) {
                  return g.observeOn(Schedulers.computation()).map(ParallelPerf.this);
              }
          });
  
          parallel = source.parallel(cpu).runOn(Schedulers.computation()).map(this).sequential();
      }
  
      void subscribe(Flowable<Integer> f, Blackhole bh) {
          PerfAsyncConsumer consumer = new PerfAsyncConsumer(bh);
          f.subscribe(consumer);
          consumer.await(count);
      }
  
      @Benchmark
      public void flatMap(Blackhole bh) {
          subscribe(flatMap, bh);
      }
  
      @Benchmark
      public void groupBy(Blackhole bh) {
          subscribe(groupBy, bh);
      }
  
      @Benchmark
      public void parallel(Blackhole bh) {
          subscribe(parallel, bh);
      }
  }
  