Disruptor详解
LMAX是一种新型零售金融交易平台，它能够以很低的延迟产生大量交易。这个系统是建立在JVM平台上，其核心是一个业务逻辑处理器，它能够在一个线程里每秒处理6百万订单。业务逻辑处理器完全是运行在内存中，使用事件源驱动方式。业务逻辑处理器的核心是Disruptor。 Disruptor它是一个开源的并发框架，并获得2011 Duke’s 程序框架创新奖，能够在无锁的情况下实现网络的Queue并发操作。 Disruptor是一个高性能的异步处理框架，或者可以认为是最快的消息框架（轻量的JMS），也可以认为是一个观察者模式的实现，或者事件监听模式的实现。 在Disruptor中，我们想实现hello world 需要如下几步骤： 第一：建立一个Event类 第二：建立一个工厂Event类，用于创建Event类实例对象 第三：需要有一个监听事件类，用于处理数据（Event类） 第四：我们需要进行测试代码编写。实例化Disruptor实例，配置一系列参数。然后我们对Disruptor实例绑定监听事件类，接受并处理数据。 第五：在Disruptor中，真正存储数据的核心叫做RingBuffer，我们通过Disruptor实例拿到它，然后把数据生产出来，把数据加入到RingBuffer的实例对象中即可。 Event类：数据封装类
public class LongEvent {
private Long value;
public Long getValue() {
return value;
}
public void setValue(Long value) {
this.value = value;
}
}工厂Event类：实现EventFactory<>接口的实现类
public class LongEventFactory implements EventFactory<LongEvent>{
@Override
public LongEvent newInstance() {
return new LongEvent();
}
}EventHandler类：数据处理类实现EventHandler<>接口
/**
* 消费者，事件监听
* @author Administrator
*
*/
public class LongEventHandler implements EventHandler<LongEvent>{
@Override
public void onEvent(LongEvent longEvent, long l, boolean b) throws Exception {
//消费，数据处理
System.out.println(longEvent.getValue());
}
}数据生产类：
public class LongEventProducer {
private final RingBuffer<LongEvent> ringBuffer;
public LongEventProducer(RingBuffer<LongEvent> ringBuffer) {
this.ringBuffer=ringBuffer;
}
public void onData(ByteBuffer bb) {
//可以把ringBuffer看做一个事件队列，那么next就是得到下面一个事件槽
long sequence=ringBuffer.next();
try {
//用上面的索引取出一个空的事件用于填充
LongEvent l=ringBuffer.get(sequence);
l.setValue(bb.getLong(
0
));
}catch (Exception e) {
}finally {
ringBuffer.publish(sequence);
}
}
}测试类：
public class LongEventTest {
public static void main(String[] args) {
ExecutorService executor=Executors.newCachedThreadPool();
LongEventFactory eventFactory=new LongEventFactory();
//必须2的N次方
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();
*/
Disruptor<LongEvent> dis=new Disruptor<>(eventFactory, ringBufferSize, executor, ProducerType.SINGLE, new YieldingWaitStrategy());
dis.handleEventsWith(new LongEventHandler());
dis.start();
RingBuffer<LongEvent> ringBuffer=dis.getRingBuffer();
LongEventProducer producer=new LongEventProducer(ringBuffer);
//LongEventProducerWithTranslator producer = new LongEventProducerWithTranslator(ringBuffer);
ByteBuffer bb=ByteBuffer.allocate(
8
);
for (int i =
0
; i <
100
; i++) {
bb.putLong(
0
,i);
producer.onData(bb);
}
dis.shutdown();
executor.shutdown();
}
}
EventProducerWithTranslator实现方式：
public class LongEventProducerWithTranslator {
//一个translator可以看做一个事件初始化器，publicEvent方法会调用它
//填充Event
private static final EventTranslatorOneArg<LongEvent, ByteBuffer> TRANSLATOR=
new EventTranslatorOneArg<LongEvent, ByteBuffer>() {
@Override
public void translateTo(LongEvent event, long sequence, ByteBuffer buffer) {
event.setValue(buffer.getLong(
0
));
}
};
private final RingBuffer<LongEvent> ringBuffer;
public LongEventProducerWithTranslator(RingBuffer<LongEvent> ringBuffer) {
this.ringBuffer=ringBuffer;
}
public void onData(ByteBuffer buffer) {
ringBuffer.publishEvent(TRANSLATOR,buffer);
}
}Disruptor术语说明
RingBuffer: 被看作Disruptor最主要的组件，然而从3.0开始RingBuffer仅仅负责存储和更新在Disruptor中流通的数据。对一些特殊的使用场景能够被用户(使用其他数据结构)完全替代。 Sequence: Disruptor使用Sequence来表示一个特殊组件处理的序号。和Disruptor一样，每个消费者(EventProcessor)都维持着一个Sequence。大部分的并发代码依赖这些Sequence值的运转，因此Sequence支持多种当前为AtomicLong类的特性。 Sequencer: 这是Disruptor真正的核心。实现了这个接口的两种生产者（单生产者和多生产者）均实现了所有的并发算法，为了在生产者和消费者之间进行准确快速的数据传递。 SequenceBarrier: 由Sequencer生成，并且包含了已经发布的Sequence的引用，这些的Sequence源于Sequencer和一些独立的消费者的Sequence。它包含了决定是否有供消费者来消费的Event的逻辑。 WaitStrategy：决定一个消费者将如何等待生产者将Event置入Disruptor。 Event：从生产者到消费者过程中所处理的数据单元。Disruptor中没有代码表示Event，因为它完全是由用户定义的。 EventProcessor：主要事件循环，处理Disruptor中的Event，并且拥有消费者的Sequence。它有一个实现类是BatchEventProcessor，包含了event loop有效的实现，并且将回调到一个EventHandler接口的实现对象。 EventHandler：由用户实现并且代表了Disruptor中的一个消费者的接口。 Producer：由用户实现，它调用RingBuffer来插入事件(Event)，在Disruptor中没有相应的实现代码，由用户实现。 WorkProcessor：确保每个sequence只被一个processor消费，在同一个WorkPool中的处理多个WorkProcessor不会消费同样的sequence。 WorkerPool：一个WorkProcessor池，其中WorkProcessor将消费Sequence，所以任务可以在实现WorkHandler接口的worker吃间移交 LifecycleAware：当BatchEventProcessor启动和停止时，于实现这个接口用于接收通知。
EventProcessor使用： handler消费类：
public class TradeHandler implements EventHandler<Trade>,WorkHandler<Trade>{
@Override
public void onEvent(Trade event) throws Exception {
//生成订单id
event.setId(UUID.randomUUID().toString());
System.out.println(event);
}
@Override
public void onEvent(Trade event, long sequence, boolean endOfBatch) throws Exception {
this.onEvent(event);
}
}Trade数据封装类：
public class Trade {
private String id;//id
private String name;//名称
private double price;//金额
private AtomicInteger count=new AtomicInteger(
0
);
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;
}
public AtomicInteger getCount() {
return count;
}
public void setCount(AtomicInteger count) {
this.count = count;
}
}EventProcessorMain测试类：
public static void main(String[] args) throws InterruptedException, ExecutionException {
int BUFFER_SIZE=
1024
;
int THREAD_NUMBERS=
4
;
/*
* 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的指数倍 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的生产都在没有可用区块的时候(可能是消费者（或者说是事件处理器） 太慢了)的等待策略
*/
final RingBuffer<Trade> ringBuffer=RingBuffer.createSingleProducer(new EventFactory<Trade>() {
@Override
public Trade newInstance() {
return new Trade();
}
}, BUFFER_SIZE,new YieldingWaitStrategy());
//创建一个线程池
ExecutorService executors=Executors.newFixedThreadPool(THREAD_NUMBERS);
//创建SequenceBarrier
SequenceBarrier sequenceBarrier=ringBuffer.newBarrier();
//创建消息处理器
BatchEventProcessor<Trade> transProcessor=new BatchEventProcessor<Trade>(ringBuffer, sequenceBarrier, new TradeHandler());
//这一步的目的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
executors.submit(transProcessor);
//如果存在多个消费者，那么重复执行上面三行代码，把TradeHandler换成其他消费者类
Future<?> future=executors.submit(new Callable<Trade>() {
@Override
public Trade call() throws Exception {
long seq;
for(int i=
0
;i<
10
;i++) {
seq=ringBuffer.next();//占一个坑-----ringBuffer一个可用区块
ringBuffer.get(seq).setPrice(Math.random()*
9999
);//给这个区块放入数据
ringBuffer.publish(seq);//发布这个区块的数据使handler(consumer)可见
}
return null;
}
});
future.get();//等待生成者结束
Thread.sleep(
1000
);//等待一秒，等消费者处理完成
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();//终止线程
}WorkProcessor使用： WorkProcessorMain测试类：
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.EventFactory;
import com.lmax.disruptor.IgnoreExceptionHandler;
import com.lmax.disruptor.RingBuffer;
import com.lmax.disruptor.SequenceBarrier;
import com.lmax.disruptor.WorkHandler;
import com.lmax.disruptor.WorkerPool;
public class WorkProcessorMain {
public static void main(String[] args) throws InterruptedException, ExecutionException {
int BUFFER_SIZE =
1024
;
int THREAD_NUMBERS =
4
;
EventFactory<Trade> eventFactory = new EventFactory<Trade>() {
@Override
public Trade newInstance() {
return new Trade();
}
};
final RingBuffer<Trade> ringBuffer = RingBuffer.createSingleProducer(eventFactory, BUFFER_SIZE);
SequenceBarrier sequenceBarrier = ringBuffer.newBarrier();
ExecutorService executors = Executors.newFixedThreadPool(THREAD_NUMBERS);
WorkHandler<Trade> handler = new TradeHandler();
WorkerPool<Trade> workerPool = new WorkerPool<>(ringBuffer, sequenceBarrier, new IgnoreExceptionHandler(),
handler);
workerPool.start(executors);
// 如果存在多个消费者，那么重复执行上面三行代码，把TradeHandler换成其他消费者类
Future<?> future = executors.submit(new Callable<Trade>() {
@Override
public Trade call() throws Exception {
long seq;
for (int i =
0
; i <
10
; i++) {
seq = ringBuffer.next();// 占一个坑-----ringBuffer一个可用区块
ringBuffer.get(seq).setPrice(Math.random() *
9999
);// 给这个区块放入数据
ringBuffer.publish(seq);// 发布这个区块的数据使handler(consumer)可见
}
return null;
}
});
future.get();// 等待生成者结束
Thread.sleep(
1000
);// 等待一秒，等消费者处理完成
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();// 终止线程
}
}并行计算 - 多边形高端操作
菱形操作
Disruptor可实现串并行同时编码。
在复杂场景下使用RingBuffer（希望P1生产的数据给C1、C2并行执行，最后C1、C2执行结束后C3执行）
- C1和C2并行执行。
六边形操作
C1h和C2并行执行，C4和C5并行执行，并行执行完后执行C3 示例： C1:
import com.lmax.disruptor.EventHandler;
import com.lmax.disruptor.WorkHandler;
import com.moudle.disruptorDemo.generate1.Trade;
public class Handler1 implements EventHandler<Trade>,WorkHandler<Trade>{
@Override
public void onEvent(Trade trade) throws Exception {
System.out.println("handler1 set name:");
trade.setName("h1");
Thread.sleep(
1000
);
}
@Override
public void onEvent(Trade arg0, long arg1, boolean arg2) throws Exception {
this.onEvent(arg0);
}
}C2
import com.lmax.disruptor.EventHandler;
import com.lmax.disruptor.WorkHandler;
import com.moudle.disruptorDemo.generate1.Trade;
public class Handler2 implements EventHandler<Trade>,WorkHandler<Trade>{
@Override
public void onEvent(Trade trade) throws Exception {
System.out.println("handler2 set price:");
trade.setPrice(
17
);
Thread.sleep(
1000
);
}
@Override
public void onEvent(Trade arg0, long arg1, boolean arg2) throws Exception {
this.onEvent(arg0);
}
}C3
import com.lmax.disruptor.EventHandler;
import com.lmax.disruptor.WorkHandler;
import com.moudle.disruptorDemo.generate1.Trade;
public class Handler3 implements EventHandler<Trade>,WorkHandler<Trade>{
@Override
public void onEvent(Trade event) throws Exception {
System.out.println("handler3: name: " + event.getName() + " , price: " + event.getPrice() + "; instance: " + event.toString());
}
@Override
public void onEvent(Trade arg0, long arg1, boolean arg2) throws Exception {
this.onEvent(arg0);
}
}C4
import com.lmax.disruptor.EventHandler;
import com.lmax.disruptor.WorkHandler;
import com.moudle.disruptorDemo.generate1.Trade;
public class Handler4 implements EventHandler<Trade>,WorkHandler<Trade>{
@Override
public void onEvent(Trade trade) throws Exception {
System.out.println("handler4 set addName:");
trade.setName(trade.getName()+"h4");
}
@Override
public void onEvent(Trade arg0, long arg1, boolean arg2) throws Exception {
this.onEvent(arg0);
}
}C5
import com.lmax.disruptor.EventHandler;
import com.lmax.disruptor.WorkHandler;
import com.moudle.disruptorDemo.generate1.Trade;
public class Handler5 implements EventHandler<Trade>,WorkHandler<Trade>{
@Override
public void onEvent(Trade trade) throws Exception {
System.out.println("handler5 set add price:");
trade.setPrice(trade.getPrice()+
3
);
}
@Override
public void onEvent(Trade arg0, long arg1, boolean arg2) throws Exception {
this.onEvent(arg0);
}
}P1(生产者)
import java.util.Random;
import java.util.concurrent.CountDownLatch;
import com.lmax.disruptor.EventTranslator;
import com.lmax.disruptor.dsl.Disruptor;
import com.moudle.disruptorDemo.generate1.Trade;
public class TradePublisher implements Runnable{
Disruptor<Trade> disruptor;
private CountDownLatch latch;
private static int count =
1
;//模拟百万次交易的发生
public TradePublisher(Disruptor<Trade> disruptor,CountDownLatch latch){
this.disruptor=disruptor;
this.latch=latch;
}
@Override
public void run() {
TradeEventTranslator translator=new TradeEventTranslator();
for(int i=
0
;i<count;i++){
disruptor.publishEvent(translator);
}
latch.countDown();
}
}
class TradeEventTranslator implements EventTranslator<Trade>{
private Random random=new Random();
@Override
public void translateTo(Trade trade, long arg1) {
this.generateTrade(trade);
}
private Trade generateTrade(Trade trade){
trade.setPrice(random.nextDouble()*
9999
);
return trade;
}
}Main:
package com.moudle.disruptorDemo.generate2;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
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;
import com.moudle.disruptorDemo.generate1.Trade;
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<>(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
handlerGroup.then(new Handler3());
//輸出結果：
// handler1 set name:
// handler2 set price:
// handler3: name: h1 , price: 17.0; instance: com.moudle.disruptorDemo.generate1.Trade@220a5c4d
/*//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);
//输出结果：
// handler1 set name:
// handler2 set price:
// handler4 set addName:
// handler5 set add price:
// handler3: name: h1h4 , price: 20.0; instance: com.moudle.disruptorDemo.generate1.Trade@5e6d6957
*/
/* //顺序执行
disruptor.handleEventsWith(new Handler1()).
handleEventsWith(new Handler2()).
handleEventsWith(new Handler3());
//输出结果：
// handler1 set name:
// handler2 set price:
// handler3: name: h1 , price: 17.0; instance: com.moudle.disruptorDemo.generate1.Trade@331d6441
*/
disruptor.start();//启动
CountDownLatch latch=new CountDownLatch(
1
);
//生产者准备
executor.submit(new TradePublisher(disruptor, latch));
latch.await();//等待生产完成
disruptor.shutdown();
executor.shutdown();
}
}多生产者多消费者的使用： Order订单类:
package com.moudle.disruptorDemo.multi;
public class Order {
private String id;//id
private String name;//
private double price;//
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;
}
}Producer生产者:
package com.moudle.disruptorDemo.multi;
import com.lmax.disruptor.RingBuffer;
public class Producer {
private final RingBuffer<Order> ringBuffer;
public Producer(RingBuffer<Order> ringBuffer){
this.ringBuffer=ringBuffer;
}
/**
* onData用来发布事件，每调用一次就发布一次事件
* 它的参数会用过事件传递给消费者
*/
public void onData(String data){
//可以把ringBuffer看做一个事件队列，那么next就是得到下面一个事件槽
long sequence=ringBuffer.next();
try {
//用上面的索引取出一个空的事件用于填充（获取该序号对应的事件对象）
Order order=ringBuffer.get(sequence);
//获取要通过事件传递的业务数据
order.setId(data);
} catch (Exception e) {
}finally{
//发布事件
//注意，最后的 ringBuffer.publish 方法必须包含在 finally 中以确保必须得到调用；如果某个请求的 sequence 未被提交，将会堵塞后续的发布操作或者其它的 producer。
ringBuffer.publish(sequence);
}
}
}Consumer消费者：
package com.moudle.disruptorDemo.multi;
import java.util.concurrent.atomic.AtomicInteger;
import com.lmax.disruptor.WorkHandler;
public class Consumer implements WorkHandler<Order>{
private String consumerId;
private static AtomicInteger count=new AtomicInteger(
0
);
public Consumer(String consumerId){
this.consumerId=consumerId;
}
@Override
public void onEvent(Order order) throws Exception {
System.out.println("当前消费者："+this.consumerId+",消费消息："+order);
count.incrementAndGet();
}
public int getCount(){
return count.get();
}
}Main测试类：
package com.moudle.disruptorDemo.multi;
import java.util.UUID;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.Executor;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import com.lmax.disruptor.EventFactory;
import com.lmax.disruptor.ExceptionHandler;
import com.lmax.disruptor.RingBuffer;
import com.lmax.disruptor.SequenceBarrier;
import com.lmax.disruptor.WorkerPool;
import com.lmax.disruptor.YieldingWaitStrategy;
import com.lmax.disruptor.dsl.ExceptionHandlerWrapper;
import com.lmax.disruptor.dsl.ProducerType;
public class Main {
public static void main(String[] args) throws Exception{
// RingBuffer<Order> ringBuffer=RingBuffer.create(
// ProducerType.MULTI, new EventFactory<Order>() {
// @Override
// public Order newInstance() {
// return new Order();
// }
// }, 1024*1024, new YieldingWaitStrategy());
//创建ringBuffer
RingBuffer<Order> ringBuffer=RingBuffer.createMultiProducer(new EventFactory<Order>() {
@Override
public Order newInstance() {
return new Order();
}
},
1024
*
1024
, new YieldingWaitStrategy());
//创建SequenceBarrier
SequenceBarrier barriers=ringBuffer.newBarrier();
//创建3个消费者实例
Consumer[] consumers=new Consumer[
3
];
for (int i =
0
; i < consumers.length; i++) {
consumers[i]=new Consumer("c"+i);
}
WorkerPool<Order> workerPool=new WorkerPool<>(
ringBuffer, barriers, new IntEventExceptionHandler(), consumers);
//这一步的目的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。
//workerPool.getWorkerSequences()获取Sequence集合
ringBuffer.addGatingSequences(workerPool.getWorkerSequences());
//创建线程池
ExecutorService executorService=Executors.newFixedThreadPool(Runtime.getRuntime().availableProcessors());
workerPool.start(executorService);
final CountDownLatch latch=new CountDownLatch(
1
);
for (int i =
0
; i <
100
; i++) {
final Producer producer=new Producer(ringBuffer);
new Thread(new Runnable() {
@Override
public void run() {
try {
//等待生产者100个线程启动
latch.await();
for (int j =
0
; j <
100
; j++) {
//生产数据
producer.onData(UUID.randomUUID().toString());
}
} catch (InterruptedException e) {
e.printStackTrace();
}
}
}).start();
}
//等待两秒，等生产者的100个线程启动
Thread.sleep(
2000
);
System.out.println("---------------开始生产-----------------");
latch.countDown();
Thread.sleep(
5000
);
System.out.println("总数:"+consumers[
0
].getCount());
executorService.shutdown();
}
static class IntEventExceptionHandler implements ExceptionHandler<Order>{
@Override
public void handleEventException(Throwable arg0, long arg1, Order arg2) {
}
@Override
public void handleOnShutdownException(Throwable arg0) {
}
@Override
public void handleOnStartException(Throwable arg0) {
}
}
}参考
- https://programtip.com/zh/art-111663
本文参与 腾讯云自媒体同步曝光计划，分享自作者个人站点/博客。
原始发表：2020/10/11 ，如有侵权请联系 cloudcommunity@tencent.com 删除
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