Question

此代码对3种不同的方法进行了基准测试，以计算double[]的元素的倒数之和。

一个for循环
Java 8流
colt数学库

使用简单的for循环比使用流的计算快约400倍的原因是什么？（或者在基准测试代码中需要改进什么？还是使用流计算此结果的更快方法？）

代码：

import java.util.Arrays;
import java.util.List;
import java.util.Map;
import java.util.concurrent.TimeUnit;
import java.util.stream.Collectors;
import java.util.stream.IntStream;
import cern.colt.list.DoubleArrayList;
import cern.jet.stat.Descriptive;
import org.openjdk.jmh.annotations.*;

@State(Scope.Thread)
public class MyBenchmark {

    public static double[] array;

    static {
        int num_of_elements = 100;
        array = new double[num_of_elements];
        for (int i = 0; i < num_of_elements; i++) {
            array[i] = i+1;
        }
    }

    @Benchmark
    @BenchmarkMode(Mode.AverageTime)
    @OutputTimeUnit(TimeUnit.NANOSECONDS)
    public void testInversionSumForLoop(){
        double result = 0;
        for (int i = 0; i < array.length; i++) {
            result += 1.0/array[i];
        }
    }

    @Benchmark
    @BenchmarkMode(Mode.AverageTime)
    @OutputTimeUnit(TimeUnit.NANOSECONDS)
    public void testInversionSumUsingStreams(){
        double result = 0;
        result = Arrays.stream(array).map(d -> 1/d).sum();
    }

    @Benchmark
    @BenchmarkMode(Mode.AverageTime)
    @OutputTimeUnit(TimeUnit.NANOSECONDS)
    public void testInversionSumUsingCernColt(){
        double result = Descriptive.sumOfInversions(new DoubleArrayList(array), 0, array.length-1);
    }
}

结果：

/**
 * Results
 * Benchmark                                  Mode  Cnt    Score    Error  Units
 * MyBenchmark.testInversionSumForLoop        avgt  200    1.647 ±  0.155  ns/op
 * MyBenchmark.testInversionSumUsingCernColt  avgt  200  603.254 ± 22.199  ns/op
 * MyBenchmark.testInversionSumUsingStreams   avgt  200  645.895 ± 20.833  ns/o
 */

更新：这些结果表明Blackhome.consume或return是避免jvm优化的必要条件。

/**
 * Updated results after adding Blackhole.consume
 * Benchmark                                  Mode  Cnt    Score    Error  Units
 * MyBenchmark.testInversionSumForLoop        avgt  200  525.498 ± 10.458  ns/op
 * MyBenchmark.testInversionSumUsingCernColt  avgt  200  517.930 ±  2.080  ns/op
 * MyBenchmark.testInversionSumUsingStreams   avgt  200  582.103 ±  3.261  ns/op
 */

oracle jdk版本“ 1.8.0_181”，达尔文内核版本17.7.0

Answer 1

在您的示例中，JVM最有可能完全优化循环，因为在计算之后永远不会读取result值。您应该使用Blackhole来消耗result，如下所示：

@State(Scope.Thread)
@Warmup(iterations = 10, time = 200, timeUnit = MILLISECONDS)
@Measurement(iterations = 20, time = 500, timeUnit = MILLISECONDS)
@BenchmarkMode(Mode.AverageTime)
@OutputTimeUnit(TimeUnit.NANOSECONDS)
public class MyBenchmark {

  static double[] array;

  static {
    int num_of_elements = 100;
    array = new double[num_of_elements];
    for (int i = 0; i < num_of_elements; i++) {
      array[i] = i + 1;
    }
  }

  double result = 0;

  @Benchmark
  public void baseline(Blackhole blackhole) {
    result = 1;
    result = result / 1.0;
    blackhole.consume(result);
  }

  @Benchmark
  public void testInversionSumForLoop(Blackhole blackhole) {
    for (int i = 0; i < array.length; i++) {
      result += 1.0 / array[i];
    }
    blackhole.consume(result);
  }

  @Benchmark
  public void testInversionSumUsingStreams(Blackhole blackhole) {
    result = Arrays.stream(array).map(d -> 1 / d).sum();
    blackhole.consume(result);
  }

}

此新基准测试显示出预期的4倍差异。循环从JVM中的a number of optimizations中受益，并且不像流那样涉及新对象的创建。

Benchmark                                 Mode  Cnt    Score   Error  Units
MyBenchmark.baseline                      avgt  100    2.437 ±  0.139  ns/op
MyBenchmark.testInversionSumForLoop       avgt  100  135.512 ± 13.080  ns/op
MyBenchmark.testInversionSumUsingStreams  avgt  100  506.479 ±  4.209  ns/o

我试图添加一个基线，以显示对我的机器进行一次操作的成本是多少。基线ns/ops与您的循环ns/ops类似，IMO确认您的循环已被优化。

我希望有人告诉我，在此基准测试场景中什么是好的基准。

我的环境：

openjdk version "11.0.1" 2018-10-16
OpenJDK Runtime Environment 18.9 (build 11.0.1+13)
OpenJDK 64-Bit Server VM 18.9 (build 11.0.1+13, mixed mode)

Intel(R) Core(TM) i7-7700HQ CPU @ 2.80GHz
Linux 4.15.0-43-generic #46-Ubuntu SMP Thu Dec 6 14:45:28 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux

为什么使用for循环的倒数总和比流快约400倍？

1 个答案: