java8中parallelStream性能测试及结果分析

测试1

@BenchmarkMode(Mode.AverageTime)
@OutputTimeUnit(TimeUnit.NANOSECONDS)
@Warmup(iterations = 5, time = 3, timeUnit = TimeUnit.SECONDS)
@Measurement(iterations = 20, time = 3, timeUnit = TimeUnit.SECONDS)
@Fork(1)
@State(Scope.Benchmark)
public class StreamBenchTest {
  List data = new ArrayList<>();
  @Setup
  public void init() {
    // prepare
    for(int i=0;i<100;i++){
      data.add(UUID.randomUUID().toString());
    }
  }
  @TearDown
  public void destory() {
    // destory
  }
  @Benchmark
  public void benchStream(){
    data.stream().forEach(e -> {
      e.getBytes();
      try {
        Thread.sleep(10);
      } catch (InterruptedException e1) {
        e1.printStackTrace();
      }
    });
  }
  @Benchmark
  public void benchParallelStream(){
    data.parallelStream().forEach(e -> {
      e.getBytes();
      try {
        Thread.sleep(10);
      } catch (InterruptedException e1) {
        e1.printStackTrace();
      }
    });
  }
  public static void main(String[] args) throws RunnerException {
    Options opt = new OptionsBuilder()
        .include(".*" +StreamBenchTest.class.getSimpleName()+ ".*")
        .forks(1)
        .build();
    new Runner(opt).run();
  }
}

parallelStream线程数

默认是Runtime.getRuntime().availableProcessors() - 1，这里为7

运行结果

# Run complete. Total time: 00:02:44
Benchmark              Mode Cnt      Score     Error Units
StreamBenchTest.benchParallelStream avgt  20  155868805.437 ± 1509175.840 ns/op
StreamBenchTest.benchStream     avgt  20 1147570372.950 ± 6138494.414 ns/op

测试2

将数据data改为30，同时sleep改为100

Benchmark              Mode Cnt      Score     Error Units
StreamBenchTest.benchParallelStream avgt  20  414230854.631 ± 725294.455 ns/op
StreamBenchTest.benchStream     avgt  20 3107250608.500 ± 4805037.628 ns/op

可以发现sleep越长，parallelStream优势越明显。

小结

parallelStream在阻塞场景下优势更明显，其线程池个数默认为
Runtime.getRuntime().availableProcessors() - 1，如果需修改则需设置-Djava.util.concurrent.ForkJoinPool.common.parallelism=8

以上就是本次讲述知识点的全部内容，感谢你对脚本之家的支持。