Disruptor笔记(四)-关键类和代码

AggregateEventHandler.java

对EventHandler列表的封装，类似EventHandler List的功能，还实现了生命周期的管理,onStart onShutdown。

 

Sequence.java

Cache line padded sequence counter 补齐Cache line的序列计数器,ringbuffer和BatchEventProcessor使用到此类来计数。

补齐方式：

    publiclong p1, p2, p3, p4, p5, p6, p7;// cache line padding,  padding1    privatevolatilelong cursor = INITIAL_CURSOR_VALUE; 

    publiclong p8, p9, p10, p11, p12, p13, p14;// cache line padding.  padding2

   情形1： object(0~8byte)+ padding1,    

                  cursor+padding2

   情形2： padding1+ cursor,

                  padding2 + object

这样，保证不同Sequence instance在不同的Cache line

 参考资料：http://mechanical-sympathy.blogspot.com/2011/07/false-sharing.html

因为高速缓存是64字节，而Hotspot JVM的对象头是两个部分组成，第一部分是由24字节的hash code和8字节的锁等状态标识组成，第二部分是指向该对象类的引用。数组Array有一个附加的"word"来记录数组长度。每个对象为了性能优化，采用8个byte粒度边界对齐的。为了在packing的时候更高效，对象的field被从定义顺序（基于字节大小）按下列顺序重排：

1.doubles(8) and longs(8)

2.ints(4) and floats(4)

3.shorts(2) and chars(2)

4.booleans(1) and bytes(1)

5.references(4/8)

6.<repeat for sub-class fields>

所以我们补齐cache line：在任意field之间补上7个long(8)

BatchEventProcessor.java 批量从RingBuffer获取event代理給EventHandler处理。

关键代码：

public void run()    {        if (!running.compareAndSet(false, true))        {            throw new IllegalStateException("Thread is already running");        }        sequenceBarrier.clearAlert();         notifyStart();         T event = null;        long nextSequence = sequence.get() + 1L;        while (true)        {            try            {                final long availableSequence = sequenceBarrier.waitFor(nextSequence);                 //批量处理,nextSequence无限增长怎么办？                while (nextSequence <= availableSequence)                {                    event = ringBuffer.get(nextSequence);                    eventHandler.onEvent(event, nextSequence,nextSequence == availableSequence);                    nextSequence++;                }                 sequence.set(nextSequence - 1L);//注意回退1,标示(nextSequence - 1L)的event已经消费完成            }            catch (final AlertException ex)            {               if (!running.get())               {                   break;               }            }            catch (final Throwable ex)            {                exceptionHandler.handleEventException(ex,nextSequence, event);//异常处理类处理异常信息                sequence.set(nextSequence);//跳过异常信息的序列                nextSequence++;            }        }         notifyShutdown();         running.set(false);    }

 

                         

ClaimStrategy.java

Sequencer里面的、用于event publishers申请event序列的策略合同。

有以下3种实现：

SingleThreadedClaimStrategy.java: 针对发布者的策略的单线程实现,只能在单线程做publisher的场景使用。

 

关键方法：

// availableCapacity 需要申请的可用数量// dependentSequences 依赖的序列public boolean hasAvailableCapacity(final int availableCapacity, final Sequence[] dependentSequences)    {        final long wrapPoint = (claimSequence.get() + availableCapacity) - bufferSize;//当前已经作为发布使用的序列（未被消费）+申请数量-        if (wrapPoint > minGatingSequence.get())        {            long minSequence = getMinimumSequence(dependentSequences);//取出依赖序列中的最小的序列（未被消费）            minGatingSequence.set(minSequence);             if (wrapPoint > minSequence)            {                return false;//如果期望的到达的序列位置大于依赖序列中的最小的序列（未被消费），说明尚未消费，所以没有可用序列用于给发布者分配            }        }         return true;    } private void waitForFreeSlotAt(final long sequence, final Sequence[] dependentSequences)    {        final long wrapPoint = sequence - bufferSize;        if (wrapPoint > minGatingSequence.get())        {            long minSequence;            while (wrapPoint > (minSequence = getMinimumSequence(dependentSequences)))            {                LockSupport.parkNanos(1L);//等待1纳秒            }             minGatingSequence.set(minSequence);        }}

 

 

 

MultiThreadedClaimStrategy.java

@Override    public long incrementAndGet(final Sequence[] dependentSequences)    {        final MutableLong minGatingSequence = minGatingSequenceThreadLocal.get();        waitForCapacity(dependentSequences,minGatingSequence);//什么技巧？         final long nextSequence = claimSequence.incrementAndGet();        waitForFreeSlotAt(nextSequence,dependentSequences, minGatingSequence);         return nextSequence;    }     @Override    public long incrementAndGet(final int delta, final Sequence[] dependentSequences)    {        final long nextSequence = claimSequence.addAndGet(delta);        waitForFreeSlotAt(nextSequence,dependentSequences, minGatingSequenceThreadLocal.get());         return nextSequence;}    @Overridepublic void serialisePublishing(final long sequence, final Sequence cursor, final int batchSize)    {        int counter = RETRIES;        while (sequence - cursor.get() > pendingPublication.length())        {            if (--counter == 0)            {                Thread.yield();                counter = RETRIES;            }        }         long expectedSequence = sequence - batchSize;        for (long pendingSequence = expectedSequence + 1;pendingSequence <= sequence; pendingSequence++)        {            pendingPublication.set((int) pendingSequence& pendingMask, pendingSequence);        }         long cursorSequence = cursor.get();        if (cursorSequence >= sequence)        {            return;        }         expectedSequence = Math.max(expectedSequence,cursorSequence);        long nextSequence = expectedSequence + 1;        while (cursor.compareAndSet(expectedSequence, nextSequence))        {            expectedSequence = nextSequence;            nextSequence++;            if (pendingPublication.get((int) nextSequence & pendingMask) != nextSequence)  //这里是什么含义？只有当nextSequence 大于 PendingBufferSize才会出现不相等的情况。            {                break;            }        }    }

 

 

MultiThreadedLowContentionClaimStrategy.java

与MultiThreadedClaimStrategy.java的在于：

@Override    public void serialisePublishing(final long sequence, final Sequence cursor, final int batchSize)    {        final long expectedSequence = sequence - batchSize;        while (expectedSequence != cursor.get())//会不会死循环？        {            // busy spin        }         cursor.set(sequence);    } 

 

EventPublisher.java

时间发布者，主要代码：

 

 

 

 

 

private void translateAndPublish(final EventTranslator<E> translator, final long sequence)    {        try        {            translator.translateTo(ringBuffer.get(sequence),sequence);//需要根据传入的translator来依据sequence转换event后，再发布event.        }        finally        {            ringBuffer.publish(sequence);        }} 

WaitStrategy.java

定制EventProcessor等待cursor这个sequence的策略，有以下4种实现：

/**

 * Blocking strategy that uses a lock andcondition variable for {@linkEventProcessor}s waiting on a barrier.

 *

 * This strategy can be used when throughputand low-latencyare not as important as CPU resource.

 */

BlockingWaitStrategy.java:用到了lock，所以只适合用在throughput和low-latency要求不高的情况下。

 

/**

 * Busy Spin strategy that uses a busy spinloop for {@link com.lmax.disruptor.EventProcessor}s waiting on a barrier.

 *

 * This strategy will use CPU resource to avoidsyscalls which can introduce latency jitter. It is best

 * used when threads can be bound to specificCPU cores.

 */

BusySpinWaitStrategy.java:这种是耗cpu的做法，不做yield()。

 

/**

 * Sleeping strategy that initially spins, thenuses a Thread.yield(), and eventually for the minimum number of nanos

 * the OS and JVM will allow while the {@link com.lmax.disruptor.EventProcessor}s are waiting on a barrier.

 *

 * This strategy is a good compromise betweenperformance and CPU resource. Latency spikes can occur after quiet periods.

 */

SleepingWaitStrategy.java:做一个counter的判断，小于100才yield(),小于0做LockSupport.parkNanos(1L);

/**

 * Yielding strategy that uses a Thread.yield()for {@link com.lmax.disruptor.EventProcessor}s waiting on a barrier

 * after an initially spinning.

 *

 * This strategy is a good compromise betweenperformance and CPU resource without incurring significant latency spikes.

 */

YieldingWaitStrategy.java:counter==0,才做yield()。