Disruptor 有哪些典型的使用场景?

开发 前端
通过消费者的灵活组合,Disruptor 的使用场景非常丰富。本文介绍了 Disruptor 的 5 个典型使用场景。在选型的时候,除了使用场景,更多地要考虑到 Disruptor 作为高性能内存队列的这个特点。

大家好,我是君哥。

Disruptor 是一款高性能的内存有界队列,它通过内存预分配、无锁并发、解决伪共享问题、使用 RingBuffer 取代阻塞队列等措施来大幅提升队列性能。

但开发者们往往对它的使用场景不太了解,到底应该在哪些场景使用呢?今天咱们就来聊一聊 Disruptor 的使用场景。

Disruptor 是一个生产-消费模式的队列,这里我们使用官网的示例,生产者发送一个 long 类型的变量,消费者收到消息后把变量打印出来。首先定义消息体:

public class LongEvent {
    private long value;
    public void set(long value)
    {
        this.value = value;
    }

    @Override
    public String toString()
    {
        return "LongEvent{" + "value=" + value + '}';
    }
}

为了让 Disruptor 给消息预先分配内存,定义一个 EventFactory,代码如下:

public class LongEventFactory implements EventFactory<LongEvent>
{
    @Override
    public LongEvent newInstance()
    {
        return new LongEvent();
    }
}

下面定义个消费者 LongEventHandler:

public class LongEventHandler implements EventHandler<LongEvent>
{
    private String consumer;

    public LongEventHandler(String consumer) {
        this.consumer = consumer;
    }

    @Override
    public void onEvent(LongEvent event, long sequence, boolean endOfBatch)
    {
        System.out.println("consumer: " + consumer + ",Event: " + event);
    }
}

1.广播场景

广播场景在我们的开发工作中并不少见,比如系统收到上游系统的一个请求消息,然后把这个消息发送给多个下游系统来处理。Disruptor 支持广播模式。比如消费者生产的消息由三个消费者来消费:

public class Broadcast {
    public static void main(String[] args) throws InterruptedException {
        int bufferSize = 1024;

        Disruptor<LongEvent> disruptor =
                new Disruptor<>(LongEvent::new, bufferSize, DaemonThreadFactory.INSTANCE);

        EventHandler<LongEvent> consumer1 = new LongEventHandler("consumer1");
        EventHandler<LongEvent> consumer2 = new LongEventHandler("consumer2");
        EventHandler<LongEvent> consumer3 = new LongEventHandler("consumer3");

        disruptor.handleEventsWith(consumer1, consumer2, consumer3);
        disruptor.start();

        RingBuffer<LongEvent> ringBuffer = disruptor.getRingBuffer();
        ByteBuffer bb = ByteBuffer.allocate(8);
        for (long l = 0; true; l++)
        {
            bb.putLong(0, l);
            ringBuffer.publishEvent((event, sequence, buffer) -> event.set(buffer.getLong(0)), bb);
            Thread.sleep(1000);
        }
    }
}

2.日志收集

再来看一个日志收集的例子。这里我们假设一个场景,业务系统集群有 3 个节点,每个节点打印的业务日志发送到 Disruptor,Disruptor 下游有 3 个消费者负责日志收集。

这里我们需要重新定义一个日志收集处理类,代码如下:

public class LogCollectHandler implements WorkHandler<LongEvent> {
    public LogCollectHandler(String consumer) {
        this.consumer = consumer;
    }

    private String consumer;


    @Override
    public void onEvent(LongEvent event)
    {
        System.out.println("consumer: " + consumer + ",Event: " + event);
    }
}

下面这个代码是绑定消费者的代码:

public static void main(String[] args) throws InterruptedException {
 int bufferSize = 1024;

 Disruptor<LongEvent> disruptor =
   new Disruptor<>(LongEvent::new, bufferSize, DaemonThreadFactory.INSTANCE);

 WorkHandler<LongEvent> consumer1 = new LogCollectHandler("consumer1");
 WorkHandler<LongEvent> consumer2 = new LogCollectHandler("consumer2");
 WorkHandler<LongEvent> consumer3 = new LogCollectHandler("consumer3");

 disruptor.handleEventsWithWorkerPool(consumer1, consumer2, consumer3);
 disruptor.start();
}

需要注意的是,上面使用的是 Disruptor 的 handleEventsWithWorkerPool 方法,使用的消费者不是 EventHandler,而是 WorkHandler。消费者组里面的消费者如果是 WorkHandler,那消费者之间就是有竞争的,比如一个 Event 已经被 consumer1 消费过,那就不再会被其他消费者消费了。消费者组里面的消费者如果是 EventHandler,那消费者之间是没有竞争的,所有消息都会消费。

3.责任链

责任链这种设计模式我们都比较熟悉了,同一个对象的处理有多个不同的逻辑,每个逻辑作为一个节点组成责任链,比如收到一条告警消息,处理节点分为:给开发人员发送邮件、给运维人员发送短信、给业务人员发送 OA 消息。

Disruptor 支持链式处理消息,看下面的示例代码:

public static void main(String[] args) throws InterruptedException {
 int bufferSize = 1024;

 Disruptor<LongEvent> disruptor =
   new Disruptor<>(LongEvent::new, bufferSize, DaemonThreadFactory.INSTANCE);

 EventHandler<LongEvent> consumer1 = new LongEventHandler("consumer1");
 EventHandler<LongEvent> consumer2 = new LongEventHandler("consumer2");
 EventHandler<LongEvent> consumer3 = new LongEventHandler("consumer3");

 disruptor.handleEventsWith(consumer1).then(consumer2).then(consumer3);
 disruptor.start();
}

Disruptor 也支持多个并行责任链,下图是 2 条责任链的场景:

这里给出一个示例代码:

public static void main(String[] args) throws InterruptedException {
 int bufferSize = 1024;

 Disruptor<LongEvent> disruptor =
   new Disruptor<>(LongEvent::new, bufferSize, DaemonThreadFactory.INSTANCE);

 EventHandler<LongEvent> consumer1 = new LongEventHandler("consumer1");
 EventHandler<LongEvent> consumer2 = new LongEventHandler("consumer2");
 EventHandler<LongEvent> consumer3 = new LongEventHandler("consumer3");
 EventHandler<LongEvent> consumer4 = new LongEventHandler("consumer4");
 EventHandler<LongEvent> consumer5 = new LongEventHandler("consumer5");
 EventHandler<LongEvent> consumer6 = new LongEventHandler("consumer6");

 disruptor.handleEventsWith(consumer1).then(consumer2).then(consumer3);
 disruptor.handleEventsWith(consumer4).then(consumer5).then(consumer6);
 disruptor.start();
}

4.多任务协作

一个经典的例子,我们在泡咖啡之前,需要烧水、洗被子、磨咖啡粉,这三个步骤可以并行,但是需要等着三步都完成之后,才可以泡咖啡。

当然,这个例子可以用 Java 中的 CompletableFuture 来实现,代码如下:

public static void main(String[] args){
    ExecutorService executor = ...;
    CompletableFuture future1 = CompletableFuture.runAsync(() -> {
        try {
            washCup();
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
    }, executor);

    CompletableFuture future2 = CompletableFuture.runAsync(() -> {
        try {
            hotWater();
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
    }, executor);

    CompletableFuture future3 = CompletableFuture.runAsync(() -> {
        try {
            grindCoffee();
        } catch (InterruptedException e) {
            e.printStackTrace();
        }
    }, executor);

    CompletableFuture.allOf(future1, future2, future3).thenAccept(
            r -> {
                System.out.println("泡咖啡");
            }
    );
    System.out.println("我是主线程");
}

同样,使用 Disruptor 也可以实现这个场景,看下面代码:

public static void main(String[] args) throws InterruptedException {
 int bufferSize = 1024;

 Disruptor<LongEvent> disruptor =
   new Disruptor<>(LongEvent::new, bufferSize, DaemonThreadFactory.INSTANCE);

 EventHandler<LongEvent> consumer1 = new LongEventHandler("consumer1");
 EventHandler<LongEvent> consumer2 = new LongEventHandler("consumer2");
 EventHandler<LongEvent> consumer3 = new LongEventHandler("consumer3");
 EventHandler<LongEvent> consumer4 = new LongEventHandler("consumer4");

 disruptor.handleEventsWith(consumer1, consumer2, consumer3).then(consumer4);
 disruptor.start();
}

5.多消费者组

类比主流消息队列的场景,Disruptor 也可以实现多消费者组的场景,组间并行消费互不影响,组内消费者竞争消息,如下图:

示例代码如下:

public static void main(String[] args) throws InterruptedException {
 int bufferSize = 1024;

 Disruptor<LongEvent> disruptor =
   new Disruptor<>(LongEvent::new, bufferSize, DaemonThreadFactory.INSTANCE);

 WorkHandler<LongEvent> consumer1 = new LogWorkHandler("consumer1");
 WorkHandler<LongEvent> consumer2 = new LogWorkHandler("consumer2");
 WorkHandler<LongEvent> consumer3 = new LogWorkHandler("consumer3");
 WorkHandler<LongEvent> consumer4 = new LogWorkHandler("consumer4");
 WorkHandler<LongEvent> consumer5 = new LogWorkHandler("consumer5");
 WorkHandler<LongEvent> consumer6 = new LogWorkHandler("consumer6");

 disruptor.handleEventsWithWorkerPool(consumer1, consumer2, consumer3);
 disruptor.handleEventsWithWorkerPool(consumer4, consumer5, consumer6);
 disruptor.start();
}

6.总结

通过消费者的灵活组合,Disruptor 的使用场景非常丰富。本文介绍了 Disruptor 的 5 个典型使用场景。在选型的时候,除了使用场景,更多地要考虑到 Disruptor 作为高性能内存队列的这个特点。

责任编辑:姜华 来源: 君哥聊技术
相关推荐

2023-04-03 11:01:26

低代码平台场景

2022-10-17 00:27:20

二叉树数组索引

2021-03-16 06:47:47

Python

2020-11-20 10:53:46

边缘计算

2015-08-04 15:21:17

SDN公有云软件定义网络

2020-02-25 22:08:02

ZooKeeper典型应用场景

2023-01-30 11:27:57

人工智能高性能计算CPU

2022-07-24 21:56:38

元宇宙

2020-10-16 09:09:20

机器学习银行技术

2023-12-29 10:28:24

SPIJava灵活性

2024-12-30 08:32:36

2015-10-09 10:12:23

ZooKeeper

2024-01-03 10:32:36

2024-05-29 14:34:07

2022-12-08 10:40:06

声明式事务AOP

2023-05-16 07:47:18

RabbitMQ消息队列系统

2013-07-27 20:11:27

2018-03-27 09:10:54

区块链

2021-09-26 05:38:16

云计算云计算环境云应用
点赞
收藏

51CTO技术栈公众号