标签:dom star 事件处理 dsl count await 适合 必须 --
Disruptor作者,介绍Disruptor能每秒处理600万订单。这是一个可怕的数字。
disruptor之所以那么快,是因为内部采用环形队列和无锁设计。使用cas来进行并发控制。通过获取可用下标来对事件发布和消费
下标通过cas控制(Atomic)
1.Disruptor:用于控制整个消费者-生产者模型的处理器
2.RingBuffer:用于存放数据
3.EventHandler:一个用于处理事件的接口(可以当做生产者,也可以当做消费者)。
4.EventFactory:事件工厂类。
5.WaitStrategy:用于实现事件处理等待RingBuffer游标策略的接口。
6.SequeueBarrier:队列屏障,用于处理访问RingBuffer的序列。
7.用于运行disruptor的线程或者线程池。
1.创建订单和订单事件
package com.liqang.test; import java.math.BigDecimal; /** * 简单模拟一个订单 * @author Administrator * */ public class Order { private int id; private BigDecimal price; private double num; private int pid; public int getId() { return id; } public void setId(int id) { this.id = id; } public BigDecimal getPrice() { return price; } public void setPrice(BigDecimal price) { this.price = price; } public double getNum() { return num; } public void setNum(double num) { this.num = num; } public int getPid() { return pid; } public void setPid(int pid) { this.pid = pid; } }
package com.liqang.test; import java.math.BigDecimal; //订单事件 disruptor容器都是以事件对存在 public class OrderEvent { private Order order; public Order getOrder() { return order; } public void setOrder(Order order) { this.order = order; } }
2.创建disruptor事件工厂
package bhz.base; import com.lmax.disruptor.EventFactory; // 需要让disruptor为我们创建事件,我们同时还声明了一个EventFactory来实例化Event对象。 public class LongEventFactory implements EventFactory { @Override public Object newInstance() { return new LongEvent(); } }
disruptor会调用工厂方法为我们创建事件。并放到对应的事件槽里面
3.创建事件消费者处理类
/** * 事件消费者 * @author Administrator * */ public class OrderEventHandle implements EventHandler<OrderEvent>{ @Override public void onEvent(OrderEvent orderEvent, long arg1, boolean arg2) throws Exception { /** *做相应的业务处理 */ System.out.println(orderEvent.getOrder().getPid()); } }
4.创建事件生产者类
/** * 事件生产者 * * @author Administrator * */ public class OrderEvenProducer { private RingBuffer<OrderEvent> ringBuffer;// disruptor容器 public OrderEvenProducer(RingBuffer<OrderEvent> ringBuffer) { this.ringBuffer = ringBuffer; } public void onData(Order order) { long index = ringBuffer.next();// 首先获取下一个事件槽位置 try { OrderEvent orderEvent = ringBuffer.get(index);// 通过序列获得disruptorFacotry创建好的事件槽 orderEvent.setOrder(order);// 填充好业务数据 } finally { ringBuffer.publish(index);// 发布事件。使用finally保证publish调用 } } }
任务是 根据容器 往容器里面注册数据
/** * 事件生产者 * * @author Administrator * */ public class OrderEvenProducer { private RingBuffer<OrderEvent> ringBuffer;// disruptor容器 public OrderEvenProducer(RingBuffer<OrderEvent> ringBuffer) { this.ringBuffer = ringBuffer; } public void onData(Order order) { long index = ringBuffer.next();// 首先获取下一个事件槽位置 try { OrderEvent orderEvent = ringBuffer.get(index);// 通过序列获得disruptorFacotry创建好的事件槽 orderEvent.setOrder(order);// 填充好业务数据 } finally { ringBuffer.publish(index);// 发布事件。使用finally保证publish调用 } } }
5.测试
package com.liqang.test; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import com.lmax.disruptor.YieldingWaitStrategy; import com.lmax.disruptor.dsl.Disruptor; import com.lmax.disruptor.dsl.ProducerType; import bhz.base.LongEventHandler; public class OrderEventMain { public static void main(String[] args) { /** * 创建线程池 不限制大小 60秒不被使用就会被回收 */ ExecutorService executorService = Executors.newCachedThreadPool(); OrderEventFactory factory = new OrderEventFactory();// 创建事件工厂 // 创建bufferSize ,也就是RingBuffer大小,必须是2的N次方 diruptor减少计算事件槽的时间 int ringBufferSize = 1024 * 1024; // /** * //BlockingWaitStrategy 是最低效的策略,但其对CPU的消耗最小并且在各种不同部署环境中能提供更加一致的性能表现 * WaitStrategy BLOCKING_WAIT = new BlockingWaitStrategy(); * //SleepingWaitStrategy * 的性能表现跟BlockingWaitStrategy差不多,对CPU的消耗也类似,但其对生产者线程的影响最小,适合用于异步日志类似的场景 * WaitStrategy SLEEPING_WAIT = new SleepingWaitStrategy(); * //YieldingWaitStrategy * 的性能是最好的,适合用于低延迟的系统。在要求极高性能且事件处理线数小于CPU逻辑核心数的场景中,推荐使用此策略;例如,CPU开启超线程的特性 * WaitStrategy YIELDING_WAIT = new YieldingWaitStrategy(); */ // 初始化disruptorProducerType.SINGLE 表示是单生产者 Disruptor<OrderEvent> disruptor = new Disruptor<>(factory, ringBufferSize, executorService, ProducerType.SINGLE, new YieldingWaitStrategy()); // 注册消费者事件处理器 disruptor.handleEventsWith(new OrderEventHandle()); // 启动 disruptor.start(); //创建生产者 OrderEvenProducer orderEvenProducer=new OrderEvenProducer(disruptor.getRingBuffer()); //模拟生产10个订单 for (int i = 0; i <10; i++) { Order order=new Order(); order.setId(i); order.setNum(i); order.setPid(i); order.setPid(i); orderEvenProducer.onData(order); } disruptor.shutdown();//关闭 disruptor,方法会堵塞,直至所有的事件都得到处理; executorService.shutdown();//关闭 disruptor 使用的线程池;如果需要的话,必须手动关闭, disruptor 在 shutdown 时不会自动关闭; } }
disruptor3.0提供lambda表达式的方式(需要jdk8)发布事件 改造事件发布者类
package com.liqang.test; import java.nio.ByteBuffer; import com.lmax.disruptor.EventTranslatorOneArg; import com.lmax.disruptor.RingBuffer; import bhz.base.LongEvent; /** * 事件生产者 * * @author Administrator * */ public class OrderEvenProducer { private static final EventTranslatorOneArg<OrderEvent, Order> TRANSLATOR = new EventTranslatorOneArg<OrderEvent, Order>() { @Override public void translateTo(OrderEvent event, long sequeue, Order order) { event.setOrder(order); } }; private final RingBuffer<OrderEvent> ringBuffer; public OrderEvenProducer(RingBuffer<OrderEvent> ringBuffer) { this.ringBuffer = ringBuffer; } public void onData(Order order){ ringBuffer.publishEvent(TRANSLATOR, order); //ringBuffer.publishEvent((event,sequeue,or)->{event.setOrder(order);},order); } }
package com.liqang.test; import java.util.concurrent.Callable; import java.util.concurrent.ExecutionException; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import java.util.concurrent.Future; import com.lmax.disruptor.BatchEventProcessor; import com.lmax.disruptor.EventFactory; import com.lmax.disruptor.RingBuffer; import com.lmax.disruptor.SequenceBarrier; import com.lmax.disruptor.YieldingWaitStrategy; import bhz.generate1.Trade; import bhz.generate1.TradeHandler; public class RingBufferTest { public static void main(String[] args) throws InterruptedException, ExecutionException { int bufferSize=1024*1024; //创建线程池 ExecutorService executorService=Executors.newCachedThreadPool(); //初始化ringbuffer RingBuffer<OrderEvent> ringBuffer=RingBuffer.createSingleProducer(new EventFactory<OrderEvent>() { @Override public OrderEvent newInstance() { // TODO Auto-generated method stub return new OrderEvent(); } }, bufferSize, new YieldingWaitStrategy()); //创建SequenceBarrier SequenceBarrier sequenceBarrier = ringBuffer.newBarrier(); //创建消息处理器 BatchEventProcessor<OrderEvent> transProcessor = new BatchEventProcessor<OrderEvent>( ringBuffer, sequenceBarrier, new OrderEventHandle()); //这一步的目的就是把消费者的位置信息引用注入到生产者 如果只有一个消费者的情况可以省略 ringBuffer.addGatingSequences(transProcessor.getSequence()); //把消息处理器提交到线程池 executorService.submit(transProcessor); //如果存在多个消费者 那重复执行上面3行代码 把TradeHandler换成其它消费者类 Future<?> future= executorService.submit(new Callable<Void>() { @Override public Void call() throws Exception { long seq; for(int i=0;i<10;i++){ seq = ringBuffer.next();//占个坑 --ringBuffer一个可用区块 OrderEvent orderEvent=ringBuffer.get(seq); Order order=new Order(); order.setId(i); order.setNum(i); order.setPid(i); order.setPid(i); orderEvent.setOrder(order); ringBuffer.publish(seq);//发布这个区块的数据使handler(consumer)可见 } return null; } }); future.get();//等待生产者结束 Thread.sleep(1000);//等上1秒,等消费都处理完成 transProcessor.halt();//通知事件(或者说消息)处理器 可以结束了(并不是马上结束!!!) executorService.shutdown();//终止线程 } }
disruptor还可以做很多复杂的业务操作
如 一个事件c1 c2 处理器并行执行 执行完之后交给c3
public class Main { public static void main(String[] args) throws InterruptedException { long beginTime=System.currentTimeMillis(); int bufferSize=1024; ExecutorService executor=Executors.newFixedThreadPool(8); Disruptor<Trade> disruptor = new Disruptor<Trade>(new EventFactory<Trade>() { @Override public Trade newInstance() { return new Trade(); } }, bufferSize, executor, ProducerType.SINGLE, new BusySpinWaitStrategy()); //菱形操作 //使用disruptor创建消费者组C1,C2 EventHandlerGroup<Trade> handlerGroup = disruptor.handleEventsWith(new Handler1(), new Handler2()); //声明在C1,C2完事之后执行JMS消息发送操作 也就是流程走到C3 (测试遇到一个问题就是 要队列被消费完了才会走到3) handlerGroup.then(new Handler3()); disruptor.start();//启动 CountDownLatch latch=new CountDownLatch(1); //生产者准备 executor.submit(new TradePublisher(latch, disruptor)); latch.await();//等待生产者完事. disruptor.shutdown(); executor.shutdown(); System.out.println("总耗时:"+(System.currentTimeMillis()-beginTime)); } }
package bhz.generate2; import java.util.Random; import java.util.concurrent.CountDownLatch; import bhz.generate1.Trade; import com.lmax.disruptor.EventTranslator; import com.lmax.disruptor.dsl.Disruptor; public class TradePublisher implements Runnable { Disruptor<Trade> disruptor; private CountDownLatch latch; private static int LOOP=1000;//模拟百万次交易的发生 public TradePublisher(CountDownLatch latch,Disruptor<Trade> disruptor) { this.disruptor=disruptor; this.latch=latch; } @Override public void run() { for(int i=0;i<LOOP;i++){ disruptor.getRingBuffer().publishEvent((event,sequeue,or)->{event.setId("ff");},new Trade()); } latch.countDown(); } }
顺序执行
c1执行后交给c2处理 c2 处理后交给c3处理
package bhz.generate2; import java.util.concurrent.CountDownLatch; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import bhz.generate1.Trade; import bhz.generate1.TradeHandler; import com.lmax.disruptor.BusySpinWaitStrategy; import com.lmax.disruptor.EventFactory; import com.lmax.disruptor.dsl.Disruptor; import com.lmax.disruptor.dsl.EventHandlerGroup; import com.lmax.disruptor.dsl.ProducerType; public class Main { public static void main(String[] args) throws InterruptedException { long beginTime=System.currentTimeMillis(); int bufferSize=1024; ExecutorService executor=Executors.newFixedThreadPool(8); Disruptor<Trade> disruptor = new Disruptor<Trade>(new EventFactory<Trade>() { @Override public Trade newInstance() { return new Trade(); } }, bufferSize, executor, ProducerType.SINGLE, new BusySpinWaitStrategy()); //顺序操作 disruptor.handleEventsWith(new Handler1()). handleEventsWith(new Handler2()). handleEventsWith(new Handler3()); disruptor.start();//启动 CountDownLatch latch=new CountDownLatch(1); //生产者准备 executor.submit(new TradePublisher(latch, disruptor)); latch.await();//等待生产者完事. disruptor.shutdown(); executor.shutdown(); System.out.println("总耗时:"+(System.currentTimeMillis()-beginTime)); } }
六边形操作
package bhz.generate2; import java.util.concurrent.CountDownLatch; import java.util.concurrent.ExecutorService; import java.util.concurrent.Executors; import bhz.generate1.Trade; import bhz.generate1.TradeHandler; import com.lmax.disruptor.BusySpinWaitStrategy; import com.lmax.disruptor.EventFactory; import com.lmax.disruptor.dsl.Disruptor; import com.lmax.disruptor.dsl.EventHandlerGroup; import com.lmax.disruptor.dsl.ProducerType; public class Main { public static void main(String[] args) throws InterruptedException { long beginTime=System.currentTimeMillis(); int bufferSize=1024; ExecutorService executor=Executors.newFixedThreadPool(8); Disruptor<Trade> disruptor = new Disruptor<Trade>(new EventFactory<Trade>() { @Override public Trade newInstance() { return new Trade(); } }, bufferSize, executor, ProducerType.SINGLE, new BusySpinWaitStrategy()); //六边形操作. Handler1 h1 = new Handler1(); Handler2 h2 = new Handler2(); Handler3 h3 = new Handler3(); Handler4 h4 = new Handler4(); Handler5 h5 = new Handler5(); disruptor.handleEventsWith(h1, h2); disruptor.after(h1).handleEventsWith(h4); disruptor.after(h2).handleEventsWith(h5); disruptor.after(h4, h5).handleEventsWith(h3); disruptor.start();//启动 CountDownLatch latch=new CountDownLatch(1); //生产者准备 executor.submit(new TradePublisher(latch, disruptor)); latch.await();//等待生产者完事. disruptor.shutdown(); executor.shutdown(); System.out.println("总耗时:"+(System.currentTimeMillis()-beginTime)); } }
h1 h2并行执行 h1执行完毕之后h4执行 h2执行完毕之后h5执行最终交给h3汇总执行
标签:dom star 事件处理 dsl count await 适合 必须 --
原文地址:https://www.cnblogs.com/LQBlog/p/8997846.html