JMH和Disruptor

时光怂恿深爱的人放手 提交于 2020-08-07 21:25:59

官网

http://openjdk.java.net/projects/code-tools/jmh/

创建JMH测试

  1. 创建Maven项目,添加依赖

    <?xml version="1.0" encoding="UTF-8"?>
    <project xmlns="http://maven.apache.org/POM/4.0.0"
             xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
             xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
        <modelVersion>4.0.0</modelVersion>
    
        <properties>
            <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
            <encoding>UTF-8</encoding>
            <java.version>1.8</java.version>
            <maven.compiler.source>1.8</maven.compiler.source>
            <maven.compiler.target>1.8</maven.compiler.target>
        </properties>
    
        <groupId>mashibing.com</groupId>
        <artifactId>HelloJMH2</artifactId>
        <version>1.0-SNAPSHOT</version>
    
    
        <dependencies>
            <!-- https://mvnrepository.com/artifact/org.openjdk.jmh/jmh-core -->
            <dependency>
                <groupId>org.openjdk.jmh</groupId>
                <artifactId>jmh-core</artifactId>
                <version>1.21</version>
            </dependency>
    
            <!-- https://mvnrepository.com/artifact/org.openjdk.jmh/jmh-generator-annprocess -->
            <dependency>
                <groupId>org.openjdk.jmh</groupId>
                <artifactId>jmh-generator-annprocess</artifactId>
                <version>1.21</version>
                <scope>test</scope>
            </dependency>
        </dependencies>
    
    
    </project>
  2. idea安装JMH插件 JMH plugin v1.0.3

  3. 由于用到了注解,打开运行程序注解配置

    compiler -> Annotation Processors -> Enable Annotation Processing

  4. 定义需要测试类PS (ParallelStream)

    package com.mashibing.jmh;
    
    import java.util.ArrayList;
    import java.util.List;
    import java.util.Random;
    
    public class PS {
    
    	static List<Integer> nums = new ArrayList<>();
    	static {
    		Random r = new Random();
    		for (int i = 0; i < 10000; i++) nums.add(1000000 + r.nextInt(1000000));
    	}
    
    	static void foreach() {
    		nums.forEach(v->isPrime(v));
    	}
    
    	static void parallel() {
    		nums.parallelStream().forEach(PS::isPrime);
    	}
    	
    	static boolean isPrime(int num) {
    		for(int i=2; i<=num/2; i++) {
    			if(num % i == 0) return false;
    		}
    		return true;
    	}
    }
  5. 写单元测试

    这个测试类一定要在test package下面

    package com.mashibing.jmh;
    
    import org.openjdk.jmh.annotations.Benchmark;
    
    import static org.junit.jupiter.api.Assertions.*;
    
    public class PSTest {
        @Benchmark
        public void testForEach() {
            PS.foreach();
        }
    }
  6. 运行测试类,如果遇到下面的错误:

    ERROR: org.openjdk.jmh.runner.RunnerException: ERROR: Exception while trying to acquire the JMH lock (C:WINDOWS/jmh.lock): C:WINDOWSjmh.lock (拒绝访问。), exiting. Use -Djmh.ignoreLock=true to forcefully continue.
    	at org.openjdk.jmh.runner.Runner.run(Runner.java:216)
    	at org.openjdk.jmh.Main.main(Main.java:71)

    这个错误是因为JMH运行需要访问系统的TMP目录,解决办法是:

    打开RunConfiguration -> Environment Variables -> include system environment viables

  7. 阅读测试报告

JMH中的基本概念

  1. Warmup 预热,由于JVM中对于特定代码会存在优化(本地化),预热对于测试结果很重要

  2. Mesurement 总共执行多少次测试

  3. Timeout

  4. Threads 线程数,由fork指定

  5. Benchmark mode 基准测试的模式

  6. Benchmark 测试哪一段代码

Next

官方样例: http://hg.openjdk.java.net/code-tools/jmh/file/tip/jmh-samples/src/main/java/org/openjdk/jmh/samples/

 

 

 

Disruptor

作者:马士兵 http://www.mashibing.com

最近更新:2019年10月22日

介绍

主页:http://lmax-exchange.github.io/disruptor/

源码:https://github.com/LMAX-Exchange/disruptor

GettingStarted: https://github.com/LMAX-Exchange/disruptor/wiki/Getting-Started

api: http://lmax-exchange.github.io/disruptor/docs/index.html

maven: https://mvnrepository.com/artifact/com.lmax/disruptor

Disruptor的特点

对比ConcurrentLinkedQueue : 链表实现

JDK中没有ConcurrentArrayQueue

Disruptor是数组实现的

无锁,高并发,使用环形Buffer,直接覆盖(不用清除)旧的数据,降低GC频率

实现了基于事件的生产者消费者模式(观察者模式)

RingBuffer

环形队列

RingBuffer的序号,指向下一个可用的元素

采用数组实现,没有首尾指针

对比ConcurrentLinkedQueue,用数组实现的速度更快

假如长度为8,当添加到第12个元素的时候在哪个序号上呢?用12%8决定

当Buffer被填满的时候到底是覆盖还是等待,由Producer决定

长度设为2的n次幂,利于二进制计算,例如:12%8 = 12 & (8 - 1) pos = num & (size -1)

Disruptor开发步骤

  1. 定义Event - 队列中需要处理的元素

  2. 定义Event工厂,用于填充队列

    这里牵扯到效率问题:disruptor初始化的时候,会调用Event工厂,对ringBuffer进行内存的提前分配

    GC产频率会降低

  3. 定义EventHandler(消费者),处理容器中的元素

事件发布模板

long sequence = ringBuffer.next();  // Grab the next sequence
try {
    LongEvent event = ringBuffer.get(sequence); // Get the entry in the Disruptor
    // for the sequence
    event.set(8888L);  // Fill with data
} finally {
    ringBuffer.publish(sequence);
}

使用EventTranslator发布事件

//===============================================================
        EventTranslator<LongEvent> translator1 = new EventTranslator<LongEvent>() {
            @Override
            public void translateTo(LongEvent event, long sequence) {
                event.set(8888L);
            }
        };

        ringBuffer.publishEvent(translator1);

        //===============================================================
        EventTranslatorOneArg<LongEvent, Long> translator2 = new EventTranslatorOneArg<LongEvent, Long>() {
            @Override
            public void translateTo(LongEvent event, long sequence, Long l) {
                event.set(l);
            }
        };

        ringBuffer.publishEvent(translator2, 7777L);

        //===============================================================
        EventTranslatorTwoArg<LongEvent, Long, Long> translator3 = new EventTranslatorTwoArg<LongEvent, Long, Long>() {
            @Override
            public void translateTo(LongEvent event, long sequence, Long l1, Long l2) {
                event.set(l1 + l2);
            }
        };

        ringBuffer.publishEvent(translator3, 10000L, 10000L);

        //===============================================================
        EventTranslatorThreeArg<LongEvent, Long, Long, Long> translator4 = new EventTranslatorThreeArg<LongEvent, Long, Long, Long>() {
            @Override
            public void translateTo(LongEvent event, long sequence, Long l1, Long l2, Long l3) {
                event.set(l1 + l2 + l3);
            }
        };

        ringBuffer.publishEvent(translator4, 10000L, 10000L, 1000L);

        //===============================================================
        EventTranslatorVararg<LongEvent> translator5 = new EventTranslatorVararg<LongEvent>() {

            @Override
            public void translateTo(LongEvent event, long sequence, Object... objects) {
                long result = 0;
                for(Object o : objects) {
                    long l = (Long)o;
                    result += l;
                }
                event.set(result);
            }
        };

        ringBuffer.publishEvent(translator5, 10000L, 10000L, 10000L, 10000L);

使用Lamda表达式

package com.mashibing.disruptor;

import com.lmax.disruptor.RingBuffer;
import com.lmax.disruptor.dsl.Disruptor;
import com.lmax.disruptor.util.DaemonThreadFactory;

public class Main03
{
    public static void main(String[] args) throws Exception
    {
        // Specify the size of the ring buffer, must be power of 2.
        int bufferSize = 1024;

        // Construct the Disruptor
        Disruptor<LongEvent> disruptor = new Disruptor<>(LongEvent::new, bufferSize, DaemonThreadFactory.INSTANCE);

        // Connect the handler
        disruptor.handleEventsWith((event, sequence, endOfBatch) -> System.out.println("Event: " + event));

        // Start the Disruptor, starts all threads running
        disruptor.start();

        // Get the ring buffer from the Disruptor to be used for publishing.
        RingBuffer<LongEvent> ringBuffer = disruptor.getRingBuffer();


        ringBuffer.publishEvent((event, sequence) -> event.set(10000L));

        System.in.read();
    }
}

ProducerType生产者线程模式

ProducerType有两种模式 Producer.MULTI和Producer.SINGLE

默认是MULTI,表示在多线程模式下产生sequence

如果确认是单线程生产者,那么可以指定SINGLE,效率会提升

如果是多个生产者(多线程),但模式指定为SINGLE,会出什么问题呢?

等待策略

1,(常用)BlockingWaitStrategy:通过线程阻塞的方式,等待生产者唤醒,被唤醒后,再循环检查依赖的sequence是否已经消费。

2,BusySpinWaitStrategy:线程一直自旋等待,可能比较耗cpu

3,LiteBlockingWaitStrategy:线程阻塞等待生产者唤醒,与BlockingWaitStrategy相比,区别在signalNeeded.getAndSet,如果两个线程同时访问一个访问waitfor,一个访问signalAll时,可以减少lock加锁次数.

4,LiteTimeoutBlockingWaitStrategy:与LiteBlockingWaitStrategy相比,设置了阻塞时间,超过时间后抛异常。

5,PhasedBackoffWaitStrategy:根据时间参数和传入的等待策略来决定使用哪种等待策略

6,TimeoutBlockingWaitStrategy:相对于BlockingWaitStrategy来说,设置了等待时间,超过后抛异常

7,(常用)YieldingWaitStrategy:尝试100次,然后Thread.yield()让出cpu

  1. (常用)SleepingWaitStrategy : sleep

消费者异常处理

默认:disruptor.setDefaultExceptionHandler()

覆盖:disruptor.handleExceptionFor().with()

依赖处理

 

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