Disruptor的使用

转：http://www.cnblogs.com/hupengcool/p/4196965.html

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。ComponentSequenceSequence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。RingBufferRingBuffer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。SequenceBarrierSequenceBarrier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();        }    }}

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