EventProcessor与WorkPool用法--可处理多消费者

时间:2023-03-09 23:08:43
EventProcessor与WorkPool用法--可处理多消费者

单一的生产者,消费者有多个,使用WorkerPool来管理多个消费者;

RingBuffer在生产Sequencer中记录一个cursor,追踪生产者生产到的最新位置,通过WorkSequence和sequence记录整个workpool消费的位置和每个WorkProcessor消费到位置,来协调生产和消费程序

1、定义事件

package com.ljq.disruptor;

import java.io.Serializable;

/**
* 交易事件数据
*
* @author Administrator
*
*/
@SuppressWarnings("serial")
public class TradeEvent implements Serializable {
private String id; // 订单ID
private String name;
private double price; // 金额 public TradeEvent() {
} public TradeEvent(String id) {
super();
this.id = id;
} public String getId() {
return id;
} public void setId(String id) {
this.id = id;
} public String getName() {
return name;
} public void setName(String name) {
this.name = name;
} public double getPrice() {
return price;
} public void setPrice(double price) {
this.price = price;
} @Override
public String toString() {
return "Trade [id=" + id + ", name=" + name + ", price=" + price + "]";
} }

2、TradeEvent事件消费者

package com.ljq.disruptor;

import com.lmax.disruptor.EventHandler;
import com.lmax.disruptor.WorkHandler; public class TradeEventHandler implements EventHandler<TradeEvent>, WorkHandler<TradeEvent> {
@Override
public void onEvent(TradeEvent event, long sequence, boolean endOfBatch) throws Exception {
this.onEvent(event);
} /**
* WorkProcessor多线程排队领event然后再执行,不同线程执行不同的event。但是多了个排队领event的过程,这个是为了减少对生产者队列查询的压力
*/
@Override
public void onEvent(TradeEvent event) throws Exception {
// 具体的消费逻辑
System.out.println("consumer:" + Thread.currentThread().getName() + " Event: value=" + event);
}
}

3、EventProcessor消费者-生产者启动类

package com.ljq.disruptor;

import java.util.UUID;
import java.util.concurrent.Callable;
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; public class EventProcessorMain {
public static void main(String[] args) throws Exception {
long beginTime = System.currentTimeMillis(); // 指定 ring buffer字节大小,必需为2的N次方(能将求模运算转为位运算提高效率 ),否则影响性能
int bufferSize = 1024;
//固定线程数
int nThreads = 4; EventFactory<TradeEvent> eventFactory = new EventFactory<TradeEvent>() {
@Override
public TradeEvent newInstance() {
return new TradeEvent(UUID.randomUUID().toString());
}
}; //RingBuffer. createSingleProducer创建一个单生产者的RingBuffer
//第一个参数叫EventFactory,从名字上理解就是“事件工厂”,其实它的职责就是产生数据填充RingBuffer的区块。
//第二个参数是RingBuffer的大小,它必须是2的整数倍,目的是为了将求模运算转为&运算提高效率
//第三个参数是RingBuffer的生产在没有可用区块的时候(可能是消费者太慢了)的等待策略
final RingBuffer<TradeEvent> ringBuffer = RingBuffer.createSingleProducer(eventFactory, bufferSize, new YieldingWaitStrategy()); //SequenceBarrier, 协调消费者与生产者, 消费者链的先后顺序. 阻塞后面的消费者(没有Event可消费时)
SequenceBarrier sequenceBarrier = ringBuffer.newBarrier(); //创建消费者事件处理器, 多线程并发执行,不同线程执行不同的event
BatchEventProcessor<TradeEvent> transProcessor = new BatchEventProcessor<TradeEvent>(ringBuffer, sequenceBarrier, new TradeEventHandler());
//把消费者的消费进度情况注册给RingBuffer结构(生产者),如果只有一个消费者的情况可以省略
ringBuffer.addGatingSequences(transProcessor.getSequence()); //创建一个可重用固定线程数的线程池,以共享的*队列方式来运行这些线程
ExecutorService executors = Executors.newFixedThreadPool(nThreads);
//把消费者提交到线程池,说明EventProcessor实现了callable接口
executors.submit(transProcessor); // 生产者,这里新建线程不是必要的
Future<?> future= executors.submit(new Callable<Void>() {
@Override
public Void call() throws Exception {
long seq;
for (int i = 0; i < 100000; i++) {
seq = ringBuffer.next();
ringBuffer.get(seq).setPrice(i);
ringBuffer.publish(seq);
}
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!!!)
executors.shutdown(); System.out.println(String.format("总共耗时%s毫秒", (System.currentTimeMillis() - beginTime))); }
}

4、WorkerPool消费者-生产者启动类

package com.ljq.disruptor;

import java.util.UUID;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors; import com.lmax.disruptor.EventFactory;
import com.lmax.disruptor.IgnoreExceptionHandler;
import com.lmax.disruptor.RingBuffer;
import com.lmax.disruptor.SequenceBarrier;
import com.lmax.disruptor.WorkerPool; public class WorkPoolMain {
public static void main(String[] args) throws InterruptedException {
// 指定 ring buffer字节大小,必需为2的N次方(能将求模运算转为位运算提高效率 ),否则影响性能
int bufferSize = 1024;
//固定线程数
int nThreads = 4; //RingBuffer. createSingleProducer创建一个单生产者的RingBuffer
RingBuffer<TradeEvent> ringBuffer = RingBuffer.createSingleProducer(new EventFactory<TradeEvent>() {
public TradeEvent newInstance() {
return new TradeEvent(UUID.randomUUID().toString());
}
}, bufferSize); SequenceBarrier sequenceBarrier = ringBuffer.newBarrier(); WorkerPool<TradeEvent> workerPool = new WorkerPool<TradeEvent>(ringBuffer, sequenceBarrier,
new IgnoreExceptionHandler(), new TradeEventHandler()); //创建一个可重用固定线程数的线程池,以共享的*队列方式来运行这些线程
ExecutorService executors = Executors.newFixedThreadPool(nThreads);
workerPool.start(executors); // 生产10个数据
for (int i = 0; i < 80000; i++) {
long seq = ringBuffer.next();
ringBuffer.get(seq).setPrice(i);
ringBuffer.publish(seq);
} Thread.sleep(1000); //等上1秒,等消费都处理完成
workerPool.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!!!)
executors.shutdown();
}
}