JMH Java准测试工具套件
什么是JMH
创建JMH测试
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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> -
idea安装JMH插件 JMH plugin v1.0.3
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由于用到了注解，打开运行程序注解配置
compiler -> Annotation Processors -> Enable Annotation Processing
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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; } } -
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(); } } -
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:\WINDOWS\jmh.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
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阅读测试报告
JMH中的基本概念
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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 -
Mesurement
总共执行多少次测试 -
Timeout
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Threads
线程数，由fork指定 -
Benchmark mode
基准测试的模式 -
Benchmark
测试哪一段代码
Next
Disruptor
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）
对于遍历来讲，链表效率比数组低。JDK中没有ConcurrentArrayQueue，因为每次都要拷贝
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
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定义Event - 队列中需要处理的元素
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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
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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
- （常用）SleepingWaitStrategy : sleep
消费者异常处理
默认：disruptor.setDefaultExceptionHandler()
覆盖：disruptor.handleExceptionFor().with()