多线程的应用 - 提升效率

环境搭建

基本介绍

基准测试工具选择，使用了比较靠谱的 JMH，它会执行程序预热，执行多次测试并平均
cpu 核数限制，有两种思路

1. 使用虚拟机，分配合适的核
2. 使用 msconfig，分配合适的核，需要重启比较麻烦
   并行计算方式的选择

创建项目

点击 Add , 添加 groupId : org.openjdk.jmh , 然后添加 ArtifactId : jmh-java-benchmark-archetype

也可以通过maven命令创建

mvn archetype:generate -DinteractiveMode=false -DarchetypeGroupId=org.openjdk.jmh -
DarchetypeArtifactId=jmh-java-benchmark-archetype 

-DgroupId=cn.knightzz
-DartifactId=apply-efficiency
-Dversion=1.0

创建完成以后记得去pom文件中将java编译版本<javac.target>1.8</javac.target>从1.6修为1.8

  <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <jmh.version>1.0</jmh.version>
        <javac.target>1.8</javac.target>
        <uberjar.name>benchmarks</uberjar.name>
    </properties>

编写测试代码

package cn.knightzz.benchmark;

import java.util.Arrays;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.FutureTask;
import org.openjdk.jmh.annotations.Benchmark;
import org.openjdk.jmh.annotations.BenchmarkMode;
import org.openjdk.jmh.annotations.Fork;
import org.openjdk.jmh.annotations.Measurement;
import org.openjdk.jmh.annotations.Mode;
import org.openjdk.jmh.annotations.Warmup;

/** * @author 王天赐 * @title: MyBenchmark * @projectName hm-juc-codes * @description: 测试多线程提高执行效率 * @website <a href="http://knightzz.cn/">http://knightzz.cn/</a> * @github <a href="https://github.com/knightzz1998">https://github.com/knightzz1998</a> * @create: 2022-06-19 15:59 */
@Fork(1)
@BenchmarkMode(Mode.AverageTime) // 统计程序平均耗时
@Warmup(iterations=3) // 程序热身次数
@Measurement(iterations=5) // 测试次数
@SuppressWarnings("all")
public class MyBenchmark {
    

    static int[] ARRAY = new int[1000_000_00];

    static {
    
        // 将数组里面填充1
        Arrays.fill(ARRAY, 1);
    }

    @Benchmark
    public int c() throws ExecutionException, InterruptedException {
    

        int[] array = ARRAY;

        FutureTask<Integer> t1 = new FutureTask<>(() -> {
    
            int sum = 0;
            for (int i = 0; i < 250_000_00; i++) {
    
                sum += array[0+i];
            }
            return sum;
        });

        FutureTask<Integer> t2 = new FutureTask<>(() -> {
    
            int sum = 0;
            for (int i = 0; i < 250_000_00; i++) {
    
                sum += array[250_000_00 + i];
            }
            return sum;
        });


        FutureTask<Integer> t3 = new FutureTask<>(() -> {
    
            int sum = 0;
            for (int i = 0; i < 250_000_00; i++) {
    
                sum += array[500_000_00 + i];
            }
            return sum;
        });

        FutureTask<Integer> t4 = new FutureTask<>(() -> {
    
            int sum = 0;
            for (int i = 0; i < 250_000_00; i++) {
    
                sum += array[750_000_00 + i];
            }
            return sum;
        });

        new Thread(t1).start();
        new Thread(t2).start();
        new Thread(t3).start();
        new Thread(t4).start();

        return t1.get() + t2.get() + t3.get() + t4.get();
    }

    @Benchmark
    public int d() {
    
        int[] array = ARRAY;
        int sum = 0;
        for (int i = 0; i < 1000_000_00; i++) {
    
            sum += array[0 + i];
        }
        return sum;
    }

}

使用 maven package 打成 jar包

然后命令台进入target目录下 , 执行 java -jar -Xmx2G benchmarks.jar

$ java -jar -Xmx2G benchmarks.jar
# VM invoker: C:\dev\Java\jre\bin\java.exe
# VM options: -Xmx2G
# Warmup: 3 iterations, 1 s each
# Measurement: 5 iterations, 1 s each
# Threads: 1 thread, will synchronize iterations
# Benchmark mode: Average time, time/op
# Benchmark: cn.knightzz.benchmark.MyBenchmark.c

# Run progress: 0.00% complete, ETA 00:00:16
# Fork: 1 of 1
# Warmup Iteration 1: 0.019 s/op
# Warmup Iteration 2: 0.020 s/op
# Warmup Iteration 3: 0.019 s/op
Iteration   1: 0.023 s/op
Iteration   2: 0.020 s/op
Iteration   3: 0.020 s/op
Iteration   4: 0.026 s/op
Iteration   5: 0.022 s/op


Result: 0.022 ±(99.9%) 0.009 s/op [Average]
  Statistics: (min, avg, max) = (0.020, 0.022, 0.026), stdev = 0.002
  Confidence interval (99.9%): [0.013, 0.031]


# VM invoker: C:\dev\Java\jre\bin\java.exe
# VM options: -Xmx2G
# Warmup: 3 iterations, 1 s each
Iteration   4: 0.038 s/op
Iteration   5: 0.039 s/op


Result: 0.039 ±(99.9%) 0.002 s/op [Average]
  Statistics: (min, avg, max) = (0.038, 0.039, 0.039), stdev = 0.000
  Confidence interval (99.9%): [0.037, 0.041]


# Run complete. Total time: 00:00:20

Benchmark              Mode  Samples  Score  Score error  Units
c.k.b.MyBenchmark.c    avgt        5  0.022        0.009   s/op
c.k.b.MyBenchmark.d    avgt        5  0.039        0.002   s/op

执行结果如上面所示 : 可以看到效率差了很多, 多线程的执行 耗费 0.022 s , 而单线程耗费 0.039 s (单位是秒)