Disruptor的使用

..................2015年的第一天...................

本文代码托管在 https://github.com/hupengcool/disruptor-starter

Intruduction

关于吹牛逼的话就不说了。。。Disruptor是Java实现的用于线程间通信的消息组件。其核心是一个Lock-free的Ringbuffer,Disruptor使用CAS而不是Lock。与大部分并发队列使用的Lock相比,CAS显然要快很多。CAS是CPU级别的指令,更加轻量,不需要像Lock一样需要OS的支持,所以每次调用不需要kernel entry,也不需要context switch。当然,使用CAS的代价是Disruptor实现的复杂程度也相对提高了。

Component

Sequence

Sequence是Disruptor最核心的组件,上面已经提到过了。生产者对RingBuffer的互斥访问,生产者与消费者之间的协调以及消费者之间的协调,都是通过Sequence实现。几乎每一个重要的组件都包含Sequence。那么Sequence是什么呢?首先Sequence是一个递增的序号,说白了就是计数器;其次,由于需要在线程间共享,所以Sequence是引用传递,并且是线程安全的;再次,Sequence支持CAS操作;最后,为了提高效率,Sequence通过padding来避免伪共享。

RingBuffer

RingBuffer是存储消息的地方,通过一个名为cursor的Sequence对象指示队列的头,协调多个生产者向RingBuffer中添加消息,并用于在消费者端判断RingBuffer是否为空。巧妙的是,表示队列尾的Sequence并没有在RingBuffer中,而是由消费者维护。这样的好处是多个消费者处理消息的方式更加灵活,可以在一个RingBuffer上实现消息的单播,多播,流水线以及它们的组合。其缺点是在生产者端判断RingBuffer是否已满是需要跟踪更多的信息,为此,在RingBuffer中维护了一个名为gatingSequences的Sequence数组来跟踪相关Seqence。

SequenceBarrier

SequenceBarrier用来在消费者之间以及消费者和RingBuffer之间建立依赖关系。在Disruptor中,依赖关系实际上指的是Sequence的大小关系,消费者A依赖于消费者B指的是消费者A的Sequence一定要小于等于消费者B的Sequence,这种大小关系决定了处理某个消息的先后顺序。因为所有消费者都依赖于RingBuffer,所以消费者的Sequence一定小于等于RingBuffer中名为cursor的Sequence,即消息一定是先被生产者放到Ringbuffer中,然后才能被消费者处理。

SequenceBarrier在初始化的时候会收集需要依赖的组件的Sequence,RingBuffer的cursor会被自动的加入其中。需要依赖其他消费者和/或RingBuffer的消费者在消费下一个消息时,会先等待在SequenceBarrier上,直到所有被依赖的消费者和RingBuffer的Sequence大于等于这个消费者的Sequence。当被依赖的消费者或RingBuffer的Sequence有变化时,会通知SequenceBarrier唤醒等待在它上面的消费者。

WaitStrategy

当消费者等待在SequenceBarrier上时,有许多可选的等待策略,不同的等待策略在延迟和CPU资源的占用上有所不同,可以视应用场景选择:

BusySpinWaitStrategy : 自旋等待,类似Linux Kernel使用的自旋锁。低延迟但同时对CPU资源的占用也多。

BlockingWaitStrategy : 使用锁和条件变量。CPU资源的占用少,延迟大。

SleepingWaitStrategy : 在多次循环尝试不成功后,选择让出CPU,等待下次调度,多次调度后仍不成功,尝试前睡眠一个纳秒级别的时间再尝试。这种策略平衡了延迟和CPU资源占用,但延迟不均匀。

YieldingWaitStrategy : 在多次循环尝试不成功后,选择让出CPU,等待下次调。平衡了延迟和CPU资源占用,但延迟也比较均匀。

PhasedBackoffWaitStrategy : 上面多种策略的综合,CPU资源的占用少,延迟大。

BatchEvenProcessor

在Disruptor中,消费者是以EventProcessor的形式存在的。其中一类消费者是BatchEvenProcessor。每个BatchEvenProcessor有一个Sequence,来记录自己消费RingBuffer中消息的情况。所以,一个消息必然会被每一个BatchEvenProcessor消费。

WorkProcessor

另一类消费者是WorkProcessor。每个WorkProcessor也有一个Sequence,多个WorkProcessor还共享一个Sequence用于互斥的访问RingBuffer。一个消息被一个WorkProcessor消费,就不会被共享一个Sequence的其他WorkProcessor消费。这个被WorkProcessor共享的Sequence相当于尾指针。

WorkerPool

共享同一个Sequence的WorkProcessor可由一个WorkerPool管理,这时,共享的Sequence也由WorkerPool创建。

Use Cases

下面以Disruptor 3.3.0版本为例介绍Disruptor的初级使用,本文并没有用那些比较原始的API,如果想知道上面写的一些api如何使用,可以参考 https://github.com/LMAX-Exchange/disruptor/tree/master/src/perftest/java/com/lmax/disruptor 为了简化使用,框架提供Disruptor类来简化使用,下面主要是使用这个类来演示。
首先定义一个Event:

/**
 * Created by hupeng on 2015/1/1.
 */
public class MyEvent {

    private long value;

    public void setValue(long value) {
        this.value = value;
    }

    @Override
    public String toString() {
        return "MyEvent{" +
                "value=" + value +
                '}';
    }
}

然后提供一个EventFactory,RingBuffer通过这factory来初始化在Event。

import com.lmax.disruptor.EventFactory;

/**
 * Created by hupeng on 2015/1/1.
 */
public class MyEventFactory implements EventFactory<MyEvent> {
    @Override
    public MyEvent newInstance() {
        return new MyEvent();
    }
}

然后写一个Producer类,也就是消息的生产者。

import com.lmax.disruptor.EventTranslatorOneArg;
import com.lmax.disruptor.RingBuffer;

/**
 * Created by hupeng on 2015/1/1.
 */
public class MyEventProducer {

    private RingBuffer<MyEvent> ringBuffer;

    public MyEventProducer(RingBuffer<MyEvent> ringBuffer) {
        this.ringBuffer = ringBuffer;
    }

    private static final EventTranslatorOneArg TRANSLATOR = new EventTranslatorOneArg<MyEvent, Long>() {

        @Override
        public void translateTo(MyEvent event, long sequence, Long value) {
            event.setValue(value);
        }
    };
    
    public void onData(final Long value) {
        ringBuffer.publishEvent(TRANSLATOR,value);
    }
}

然后写一个EventHandler。这个就是我们定义怎么处理消息的地方。

import com.lmax.disruptor.EventHandler;

/**
 * Created by hupeng on 2015/1/1.
 */
public class MyEventHandler implements EventHandler<MyEvent> {
    @Override
    public void onEvent(MyEvent event, long sequence, boolean endOfBatch) throws Exception {
        System.out.println(event);
    }
}

主程序:

import com.lmax.disruptor.IgnoreExceptionHandler;
import com.lmax.disruptor.RingBuffer;
import com.lmax.disruptor.YieldingWaitStrategy;
import com.lmax.disruptor.dsl.Disruptor;
import com.lmax.disruptor.dsl.ProducerType;
import disruptor.starter.support.*;

import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.TimeUnit;
public class MyEventMain {
    public static void main(String[] args) throws InterruptedException {
        ExecutorService executorService = Executors.newFixedThreadPool(2);

        int bufferSize = 1024;

        Disruptor<MyEvent> disruptor = new Disruptor<MyEvent>(new MyEventFactory(),
                bufferSize, executorService, ProducerType.SINGLE, new YieldingWaitStrategy());
        disruptor.handleExceptionsWith(new IgnoreExceptionHandler());

        disruptor.handleEventsWith(new MyEventHandler(),new MyEventHandler());
//        disruptor.handleEventsWith(new MyEventHandler()).then(new MyEventHandler());  //Pipeline
        RingBuffer<MyEvent> ringBuffer = disruptor.start();

        MyEventProducer producer = new MyEventProducer(ringBuffer);
        for (long i = 0; i < 10; i++) {
            producer.onData(i);
            Thread.sleep(1000);// wait for task execute....
        }

        disruptor.shutdown();

        ExecutorsUtils.shutdownAndAwaitTermination(executorService, 60, TimeUnit.SECONDS);
    }
}

在这个例子中输出

MyEvent{value=0}
MyEvent{value=0}
MyEvent{value=1}
MyEvent{value=1}
MyEvent{value=2}
MyEvent{value=2}
MyEvent{value=3}
MyEvent{value=3}
MyEvent{value=4}
MyEvent{value=4}
MyEvent{value=5}
MyEvent{value=5}
MyEvent{value=6}
MyEvent{value=6}
MyEvent{value=7}
MyEvent{value=7}
MyEvent{value=8}
MyEvent{value=8}
MyEvent{value=9}
MyEvent{value=9}

可以看出每个MyEventHandler(implements EventHandler)都会处理同一条消息。另外我们还可以使用类似:

disruptor.handleEventsWith(new MyEventHandler()).then(new MyEventHandler())

这样的方法来定义依赖关系,比如先执行哪个handler再执行哪个handler。其他比如and()详情见api
如果我们想定义多个handler,但是同时只有一个handler处理某一条消息。可以实现WorkHandler来定义handler:

import com.lmax.disruptor.WorkHandler;

/**
 * Created by hupeng on 2015/1/1.
 */
public class MyEventWorkHandler implements WorkHandler<MyEvent> {

    private String workerName;

    public MyEventWorkHandler(String workerName) {
        this.workerName = workerName;
    }

    @Override
    public void onEvent(MyEvent event) throws Exception {
        System.out.println(workerName + " handle event:" + event);
    }
}

这时候我们改一下我们的主程序:

public static void main(String[] args) throws InterruptedException {
        ExecutorService executorService = Executors.newFixedThreadPool(2);

        int bufferSize = 1024;

        Disruptor<MyEvent> disruptor = new Disruptor<MyEvent>(new MyEventFactory(),
                bufferSize, executorService, ProducerType.SINGLE, new YieldingWaitStrategy());
        disruptor.handleExceptionsWith(new IgnoreExceptionHandler());
        disruptor.handleEventsWithWorkerPool(new MyEventWorkHandler("worker-1"),new MyEventWorkHandler("worker-2"));
        RingBuffer<MyEvent> ringBuffer = disruptor.start();

        MyEventProducer producer = new MyEventProducer(ringBuffer);
        for (long i = 0; i < 10; i++) {
            producer.onData(i);
            Thread.sleep(1000);// wait for task execute....
        }

        disruptor.shutdown();

        ExecutorsUtils.shutdownAndAwaitTermination(executorService, 60, TimeUnit.SECONDS);

    }

这时候我们可以看到输出是这样的:

worker-1 handle event:MyEvent{value=0}
worker-2 handle event:MyEvent{value=1}
worker-1 handle event:MyEvent{value=2}
worker-2 handle event:MyEvent{value=3}
worker-1 handle event:MyEvent{value=4}
worker-2 handle event:MyEvent{value=5}
worker-1 handle event:MyEvent{value=6}
worker-2 handle event:MyEvent{value=7}
worker-1 handle event:MyEvent{value=8}
worker-2 handle event:MyEvent{value=9}

一条消息只被一个handler处理。

这里的ExecutorsUtils就是写的一个关闭ExecutorService的方法

import java.util.concurrent.ExecutorService;
import java.util.concurrent.TimeUnit;

public class ExecutorsUtils {

    public static  void shutdownAndAwaitTermination(ExecutorService pool,int timeout,TimeUnit unit) {
        pool.shutdown(); // Disable new tasks from being submitted
        try {
            // Wait a while for existing tasks to terminate
            if (!pool.awaitTermination(timeout/2, unit)) {
                pool.shutdownNow(); // Cancel currently executing tasks
                // Wait a while for tasks to respond to being cancelled
                if (!pool.awaitTermination(timeout/2, unit))
                    System.err.println("Pool did not terminate");
            }
        } catch (InterruptedException ie) {
            // (Re-)Cancel if current thread also interrupted
            pool.shutdownNow();
            // Preserve interrupt status
            Thread.currentThread().interrupt();
        }
    }
}

概念部分来自http://ziyue1987.github.io/pages/2013/09/22/disruptor-use-manual.html ,如果想对这个框架有更一步了解,可以点进去看看,可以参考源代码。

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