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《disruptor笔记》系列链接
本篇概览
本篇是《disruptor笔记》的第五篇,前文《disruptor笔记之四:事件消费知识点小结》从理论上梳理分析了独立消费和共同消费,留下了三个任务,今天就来成这些任务,即编码实现以下三个场景:
- 100个订单,短信和邮件系统独立消费
- 100个订单,邮件系统的两个邮件服务器共同消费;
- 100个订单,短信系统独立消费,与此同时,两个邮件服务器共同消费;
源码下载
- 本篇实战中的完整源码可在GitHub下载到,地址和链接信息如下表所示(https://github.com/zq2599/blo...):
名称 | 链接 | 备注 |
---|---|---|
项目主页 | https://github.com/zq2599/blo... | 该项目在GitHub上的主页 |
git仓库地址(https) | https://github.com/zq2599/blo... | 该项目源码的仓库地址,https协议 |
git仓库地址(ssh) | [email protected]:zq2599/blog_demos.git | 该项目源码的仓库地址,ssh协议 |
- 这个git项目中有多个文件夹,本次实战的源码在disruptor-tutorials文件夹下,如下图红框所示:
- disruptor-tutorials是个父工程,里面有多个module,本篇实战的module是consume-mode,如下图红框所示:
编写公共代码
- 为了完成任务,编码实现上面那三个场景,咱们需要先把公共代码写好;
- 首先是在父工程disruptor-tutorials下面新建名为consume-mode的module,其build.gradle内容如下:
plugins {
id 'org.springframework.boot'
}
dependencies {
implementation 'org.projectlombok:lombok'
implementation 'org.springframework.boot:spring-boot-starter'
implementation 'org.springframework.boot:spring-boot-starter-web'
implementation 'com.lmax:disruptor'
testImplementation('org.springframework.boot:spring-boot-starter-test')
}
- springboot启动类:
package com.bolingcavalry;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
@SpringBootApplication
public class ConsumeModeApplication {
public static void main(String[] args) {
SpringApplication.run(ConsumeModeApplication.class, args);
}
}
- 订单事件定义:
package com.bolingcavalry.service;
import lombok.Data;
import lombok.NoArgsConstructor;
import lombok.ToString;
@Data
@ToString
@NoArgsConstructor
public class OrderEvent {
private String value;
}
-
- 订单事件的工程类,定义事件实例如何创建:
package com.bolingcavalry.service;
import com.lmax.disruptor.EventFactory;
public class OrderEventFactory implements EventFactory {
@Override
public OrderEvent newInstance() {
return new OrderEvent();
}
}
- 订单事件生产者类,定义如何将业务信息通过事件发布到环形队列:
package com.bolingcavalry.service;
import com.lmax.disruptor.RingBuffer;
public class OrderEventProducer {
// 存储数据的环形队列
private final RingBuffer ringBuffer;
public OrderEventProducer(RingBuffer ringBuffer) {
this.ringBuffer = ringBuffer;
}
public void onData(String content) {
// ringBuffer是个队列,其next方法返回的是下最后一条记录之后的位置,这是个可用位置
long sequence = ringBuffer.next();
try {
// sequence位置取出的事件是空事件
OrderEvent orderEvent = ringBuffer.get(sequence);
// 空事件添加业务信息
orderEvent.setValue(content);
} finally {
// 发布
ringBuffer.publish(sequence);
}
}
}
- 消费订单事件的短信服务,实现EventHandler接口,所以是用在独立消费的场景:
package com.bolingcavalry.service;
import com.lmax.disruptor.EventHandler;
import lombok.extern.slf4j.Slf4j;
import java.util.function.Consumer;
@Slf4j
public class SmsEventHandler implements EventHandler {
public SmsEventHandler(Consumer> consumer) {
this.consumer = consumer;
}
// 外部可以传入Consumer实现类,每处理一条消息的时候,consumer的accept方法就会被执行一次
private Consumer> consumer;
@Override
public void onEvent(OrderEvent event, long sequence, boolean endOfBatch) throws Exception {
log.info("短信服务 sequence [{}], endOfBatch [{}], event : {}", sequence, endOfBatch, event);
// 这里延时100ms,模拟消费事件的逻辑的耗时
Thread.sleep(100);
// 如果外部传入了consumer,就要执行一次accept方法
if (null!=consumer) {
consumer.accept(null);
}
}
}
- 消费订单事件的邮件服务,实现EventHandler接口,所以是用在独立消费的场景:
package com.bolingcavalry.service;
import com.lmax.disruptor.EventHandler;
import lombok.extern.slf4j.Slf4j;
import java.util.function.Consumer;
@Slf4j
public class MailEventHandler implements EventHandler {
public MailEventHandler(Consumer> consumer) {
this.consumer = consumer;
}
// 外部可以传入Consumer实现类,每处理一条消息的时候,consumer的accept方法就会被执行一次
private Consumer> consumer;
@Override
public void onEvent(OrderEvent event, long sequence, boolean endOfBatch) throws Exception {
log.info("邮件服务 sequence [{}], endOfBatch [{}], event : {}", sequence, endOfBatch, event);
// 这里延时100ms,模拟消费事件的逻辑的耗时
Thread.sleep(100);
// 如果外部传入了consumer,就要执行一次accept方法
if (null!=consumer) {
consumer.accept(null);
}
}
}
- 消费订单事件的邮件服务,实现WorkHandler接口,所以是用在共同消费的场景:
package com.bolingcavalry.service;
import com.lmax.disruptor.WorkHandler;
import lombok.extern.slf4j.Slf4j;
import java.util.function.Consumer;
@Slf4j
public class MailWorkHandler implements WorkHandler {
public MailWorkHandler(Consumer> consumer) {
this.consumer = consumer;
}
// 外部可以传入Consumer实现类,每处理一条消息的时候,consumer的accept方法就会被执行一次
private Consumer> consumer;
@Override
public void onEvent(OrderEvent event) throws Exception {
log.info("共同消费模式的邮件服务 : {}", event);
// 这里延时100ms,模拟消费事件的逻辑的耗时
Thread.sleep(100);
// 如果外部传入了consumer,就要执行一次accept方法
if (null!=consumer) {
consumer.accept(null);
}
}
}
- 最后,将发布和消费事件的逻辑写在一个抽象类里,但是具体如何消费事件并不在此类中实现,而是留给子类,这个抽象类中有几处要注意的地方稍后会提到:
package com.bolingcavalry.service;
import com.lmax.disruptor.dsl.Disruptor;
import lombok.Setter;
import org.springframework.scheduling.concurrent.CustomizableThreadFactory;
import javax.annotation.PostConstruct;
import java.util.concurrent.CountDownLatch;
import java.util.concurrent.atomic.AtomicLong;
import java.util.function.Consumer;
public abstract class ConsumeModeService {
/**
* 独立消费者数量
*/
public static final int INDEPENDENT_CONSUMER_NUM = 2;
/**
* 环形缓冲区大小
*/
protected int BUFFER_SIZE = 16;
protected Disruptor disruptor;
@Setter
private OrderEventProducer producer;
/**
* 统计消息总数
*/
protected final AtomicLong eventCount = new AtomicLong();
/**
* 这是辅助测试用的,
* 测试的时候,完成事件发布后,测试主线程就用这个countDownLatch开始等待,
* 在消费到指定的数量(countDownLatchGate)后,消费线程执行countDownLatch的countDown方法,
* 这样测试主线程就可以结束等待了
*/
private CountDownLatch countDownLatch;
/**
* 这是辅助测试用的,
* 测试的时候,完成事件发布后,测试主线程就用这个countDownLatch开始等待,
* 在消费到指定的数量(countDownLatchGate)后,消费线程执行countDownLatch的countDown方法,
* 这样测试主线程就可以结束等待了
*/
private int countDownLatchGate;
/**
* 准备一个匿名类,传给disruptor的事件处理类,
* 这样每次处理事件时,都会将已经处理事件的总数打印出来
*/
protected Consumer> eventCountPrinter = new Consumer
- 上述代码,有以下几处需要注意:
- init方法是spring bean实例化后要执行的方法,这里面实例化Disruptor,还启动了消费线程,并且实例化了事件生产者,具体的事件消费逻辑,由子类在disruptorOperate方法中实现;
- eventCountPrinter是个匿名类实例,传给事件消费的handler后,每消费一个事件都会执行一次eventCountPrinter.accept方法,这样就把消费事件的总数准确的保存在eventCount变量中了;
- countDownLatch和countDownLatchGate是为了辅助单元测试而准备的,测试的时候,完成事件发布后,测试主线程就用这个countDownLatch开始等待,在消费到指定的数量(countDownLatchGate)后,消费线程执行countDownLatch的countDown方法,这样测试主线程就可以结束等待了
- 至此,公用代码就写完了,可见抽象父类已经做好了大部分事情,咱们的子类可以聚焦事件消费的逻辑编排了,开始挨个实现那三个场景;
100个订单,短信和邮件系统独立消费
- 两个消费者独立消费的逻辑非常简单,就一行代码,调用handleEventsWith方法把所有消费者实例传进去,就完事了:
package com.bolingcavalry.service.impl;
import com.bolingcavalry.service.ConsumeModeService;
import com.bolingcavalry.service.MailEventHandler;
import com.bolingcavalry.service.SmsEventHandler;
import org.springframework.stereotype.Service;
@Service("independentModeService")
public class IndependentModeServiceImpl extends ConsumeModeService {
@Override
protected void disruptorOperate() {
// 调用handleEventsWith,表示创建的多个消费者,每个都是独立消费的
// 这里创建两个消费者,一个是短信的,一个是邮件的
disruptor.handleEventsWith(new SmsEventHandler(eventCountPrinter), new MailEventHandler(eventCountPrinter));
}
}
- 单元测试代码如下,要注意的地方是发布完100事件后,调用countDownLatch.await()方法开始等待,直到消费者线程调用countDownLatch.countDown()方法解除等待,还有就是预期的消费消息总数等于200:
package com.bolingcavalry.service.impl;
import com.bolingcavalry.service.ConsumeModeService;
import lombok.extern.slf4j.Slf4j;
import org.junit.Test;
import org.junit.runner.RunWith;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.beans.factory.annotation.Qualifier;
import org.springframework.boot.test.context.SpringBootTest;
import org.springframework.test.context.junit4.SpringRunner;
import java.util.concurrent.CountDownLatch;
import static org.junit.Assert.assertEquals;
@RunWith(SpringRunner.class)
@SpringBootTest
@Slf4j
public class ConsumeModeServiceTest {
@Autowired
@Qualifier("independentModeService")
ConsumeModeService independentModeService;
/**
* 测试时生产的消息数量
*/
private static final int EVENT_COUNT = 100;
private void testConsumeModeService(ConsumeModeService service, int eventCount, int expectEventCount) throws InterruptedException {
CountDownLatch countDownLatch = new CountDownLatch(1);
// 告诉service,等消费到expectEventCount个消息时,就执行countDownLatch.countDown方法
service.setCountDown(countDownLatch, expectEventCount);
for(int i=0;i
- 单元测试执行结果如下,符合预期:
100个订单,邮件系统的两个邮件服务器共同消费
- 两个消费者共同消费的代码也很简单,调用handleEventsWithWorkerPool方法即可,把共同消费的MailWorkHandler实例作为参数传入:
package com.bolingcavalry.service.impl;
import com.bolingcavalry.service.ConsumeModeService;
import com.bolingcavalry.service.MailWorkHandler;
import org.springframework.stereotype.Service;
@Service("shareModeService")
public class ShareModeServiceImpl extends ConsumeModeService {
@Override
protected void disruptorOperate() {
// mailWorkHandler1模拟一号邮件服务器
MailWorkHandler mailWorkHandler1 = new MailWorkHandler(eventCountPrinter);
// mailWorkHandler2模拟一号邮件服务器
MailWorkHandler mailWorkHandler2 = new MailWorkHandler(eventCountPrinter);
// 调用handleEventsWithWorkerPool,表示创建的多个消费者以共同消费的模式消费
disruptor.handleEventsWithWorkerPool(mailWorkHandler1, mailWorkHandler2);
}
}
- 单元测试是在ConsumeModeServiceTest.java中添加如下代码,注意由于是共同消费,因此预期的消费事件数等于消息数,都是100:
@Autowired
@Qualifier("shareModeService")
ConsumeModeService shareModeService;
@Test
public void testShareModeService() throws InterruptedException {
log.info("start testShareModeService");
testConsumeModeService(shareModeService, EVENT_COUNT, EVENT_COUNT);
}
- 执行单元测试,结果如下图:
100个订单,短信系统独立消费,与此同时,两个邮件服务器共同消费
- 最后一个场景,依旧很简单,handleEventsWith调用一次,再调用一次handleEventsWithWorkerPool即可:
package com.bolingcavalry.service.impl;
import com.bolingcavalry.service.ConsumeModeService;
import com.bolingcavalry.service.MailWorkHandler;
import com.bolingcavalry.service.SmsEventHandler;
import org.springframework.stereotype.Service;
@Service("independentAndShareModeService")
public class IndependentAndShareModeServiceImpl extends ConsumeModeService {
@Override
protected void disruptorOperate() {
// 调用handleEventsWith,表示创建的多个消费者,每个都是独立消费的
// 这里创建一个消费者,短信服务
disruptor.handleEventsWith(new SmsEventHandler(eventCountPrinter));
// mailWorkHandler1模拟一号邮件服务器
MailWorkHandler mailWorkHandler1 = new MailWorkHandler(eventCountPrinter);
// mailWorkHandler2模拟一号邮件服务器
MailWorkHandler mailWorkHandler2 = new MailWorkHandler(eventCountPrinter);
// 调用handleEventsWithWorkerPool,表示创建的多个消费者以共同消费的模式消费
disruptor.handleEventsWithWorkerPool(mailWorkHandler1, mailWorkHandler2);
}
}
- 单元测试是在ConsumeModeServiceTest.java中添加如下代码,预期的消费事件数应该是200,因为整体上是两个独立消费,只不过其中的一个内部有两个消费者共同消费:
@Autowired
@Qualifier("independentAndShareModeService")
ConsumeModeService independentAndShareModeService;
@Test
public void independentAndShareModeService() throws InterruptedException {
log.info("start independentAndShareModeService");
testConsumeModeService(independentAndShareModeService,
EVENT_COUNT,
EVENT_COUNT * ConsumeModeService.INDEPENDENT_CONSUMER_NUM);
}
- 单元测试结果如下,符合预期:
- 至此,独立消费和共同消费的实战就完成了,借助disruptor,三个常见场景都可以轻松完成,如果您正在做这些场景的开发,希望本文能给您一些参考;
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