kafka-顺序消息实现

kafka-顺序消息实现

场景

在购物付款的时候，订单会有不同的订单状态，对应不同的状态事件，比如：待支付，支付成功，支付失败等等，我们会将这些消息推送给消息队列 ，后续的服务会根据订单状态进行不同的业务处理，这就要求订单状态推送就要有状态的保证

解决方案

• 生产者将相同的key的订单状态事件推送到kafka的同一分区
• kafka 消费者接收消息
• 消费者将消息提交给线程池
• 线程池根据接收到的消息，将订单状态事件使用路由策略选择其中一个线程，将具有相同路由key的事件发送到同一个线程的阻塞队列中
• 单个线程不停的从阻塞队列获取订单状态消息消费

代码实现

引入依赖

<parent>
    <groupId>org.springframework.bootgroupId>
    <artifactId>spring-boot-starter-parentartifactId>
    <version>3.2.2version>
    <relativePath/> 
parent>
<groupId>com.examplegroupId>
<artifactId>boot-kafkaartifactId>
<version>0.0.1-SNAPSHOTversion>
<name>boot-kafkaname>
<description>boot-kafkadescription>
<properties>
    <java.version>17java.version>
properties>
<dependencies>
    <dependency>
        <groupId>org.springframework.bootgroupId>
        <artifactId>spring-boot-starter-webartifactId>
    dependency>
    <dependency>
        <groupId>org.springframework.kafkagroupId>
        <artifactId>spring-kafkaartifactId>
    dependency>

    <dependency>
        <groupId>org.projectlombokgroupId>
        <artifactId>lombokartifactId>
        <optional>trueoptional>
    dependency>
    <dependency>
        <groupId>org.springframework.bootgroupId>
        <artifactId>spring-boot-starter-testartifactId>
        <scope>testscope>
    dependency>
    <dependency>
        <groupId>org.springframework.kafkagroupId>
        <artifactId>spring-kafka-testartifactId>
        <scope>testscope>
    dependency>
    <dependency>
        <groupId>com.alibabagroupId>
        <artifactId>fastjsonartifactId>
        <version>2.0.39version>
    dependency>
dependencies>

使用到的DTO

@Data
public class InterOrderDto extends OrderDto implements OrderMessage{

    /**
     * 属于哪个分区
     */
    private String partition;

    @Override
    public String getUniqueNo() {
        return getOrderNo();
    }
}


@Data
public class InterOrderDto extends OrderDto implements OrderMessage{

    /**
     * 属于哪个分区
     */
    private String partition;

    @Override
    public String getUniqueNo() {
        return getOrderNo();
    }
}

public interface OrderMessage {

    /**
     * 线程池路由key
     * @return
     */
    String getUniqueNo();

}

定义topic

这里是 3个分区，2个副本

@Configuration
public class KafkaConfiguration {

    @Bean
    public NewTopic topic(){
        return new NewTopic(Constants.TOPIC_ORDER,3,(short) 2);
    }
}

public interface Constants {

     String TOPIC_ORDER = "order";
}

消费者

消费者：OrderListener

@Component
@Slf4j
public class OrderListener {

    @Autowired
    private OrderThreadPool<OrderWorker, InterOrderDto> orderThreadPool;

    @KafkaListener(topics = Constants.TOPIC_ORDER, groupId = "orderGroup", concurrency = "3")
    public void logListener(ConsumerRecord<String, String> record) {
        log.debug("> receive log event: {}-{}", record.partition(), record.value());
        try {
            OrderDto orderDto = JSON.parseObject(record.value(), OrderDto.class);
            InterOrderDto interOrderDto = new InterOrderDto();
            BeanUtils.copyProperties(orderDto, interOrderDto);
            interOrderDto.setPartition(record.partition() + "");
            orderThreadPool.dispatch(interOrderDto);
        } catch (Exception e) {
            log.error("# kafka log listener error: {}", record.value(), e);
        }
    }

}

线程池： OrderThreadPool

/**
 * @Date: 2024/1/24 10:23
 * 线程池实现
 *
 * @param W: worker
 * @param D: message
 */
@Slf4j
public class OrderThreadPool<W extends SingleThreadWorker<D>, D extends OrderMessage> {
    private List<W> workers;
    private int size;

    public OrderThreadPool(int size, Supplier<W> provider) {
        this.size = size;
        workers = new ArrayList<>(size);
        for (int i = 0; i < size; i++) {
            workers.add(provider.get());
        }
        if (CollectionUtils.isEmpty(workers)) {
            throw new RuntimeException("worker size is 0");
        }
        start();
    }

    /**
     * route message to single thread
     *
     * @param data
     */
    public void dispatch(D data) {
        W w = getUniqueQueue(data.getUniqueNo());
        w.offer(data);
    }

    private W getUniqueQueue(String uniqueNo) {
        int queueNo = uniqueNo.hashCode() % size;
        for (W worker : workers) {
            if (queueNo == worker.getQueueNo()) {
                return worker;
            }
        }
        throw new RuntimeException("worker 路由失败");
    }

    /**
     * start worker, only start once
     */
    private void start() {
        for (W worker : workers) {
            new Thread(worker, "OWorder-" + worker.getQueueNo()).start();
        }
    }

    /**
     * 关闭所有 workder, 等待所有任务执行完
     */
    public void shutdown() {
        for (W worker : workers) {
            worker.shutdown();
        }
    }

}

工作线程：SingleThreadWorker, 内部使用阻塞队列使其串行化

/**
 * @Date: 2024/1/24 10:58
 * single thread with a blocking-queue
 */
@Slf4j
public abstract class SingleThreadWorker<T> implements Runnable {

    private static AtomicInteger cnt = new AtomicInteger(0);
    private BlockingQueue<T> queue;
    private boolean started = true;

    /**
     * worker 唯一id
     */
    @Getter
    private int queueNo;

    public SingleThreadWorker(int size) {
        this.queue = new LinkedBlockingQueue<>(size);
        this.queueNo = cnt.getAndIncrement();
        log.info("init worker {}", this.queueNo);
    }

    /**
     * 提交消息
     *
     * @param data
     */
    public void offer(T data) {
        try {
            queue.put(data);
        } catch (InterruptedException e) {
            log.info("{} offer error: {}", Thread.currentThread().getName(), JSON.toJSONString(data), e);
        }
    }

    @Override
    public void run() {
        log.info("{} worker start take ", Thread.currentThread().getName());
        while (started) {
            try {
                T data = queue.take();
                doConsumer(data);
            } catch (InterruptedException e) {
                log.error("queue take error", e);
            }
        }
    }

    /**
     * do real consume message
     *
     * @param data
     */
    protected abstract void doConsumer(T data);

    /**
     * consume rest of message in the queue when thread-pool shutdown
     */
    public void shutdown() {
        this.started = false;
        ArrayList<T> rest = new ArrayList<>();
        int i = queue.drainTo(rest);
        if (i > 0) {
            log.info("{} has rest in queue {}", Thread.currentThread().getName(), i);
            for (T t : rest) {
                doConsumer(t);
            }
        }
    }


}

工作线程实现：OrderWorker, 这里就单独处理订单事件

/**
 * @Date: 2024/1/24 13:42
 * 具体消费者
 */
@Slf4j
public class OrderWorker extends SingleThreadWorker<InterOrderDto>{
    public OrderWorker(int size) {
        super(size);
    }

    @Override
    protected void doConsumer(InterOrderDto data) {
        log.info("{} consume msg: {}", Thread.currentThread().getName(), JSON.toJSONString(data));

    }
}

生产者

生产者：OrderController, 模拟发送不同的事件类型的订单

@RestController
public class OrderController {

    @Autowired
    private KafkaTemplate<String, String> kafkaTemplate;

    @GetMapping("/send")
    public String send() throws InterruptedException {
        int size = 1000;
        for (int i = 0; i < size; i++) {
            OrderDto orderDto = new InterOrderDto();
            orderDto.setOrderNo(i + "");
            orderDto.setPayStatus(getStatus(0));
            orderDto.setTimestamp(System.currentTimeMillis());
            //相同的key发送到相同的分区
            kafkaTemplate.send(Constants.TOPIC_ORDER, orderDto.getOrderNo(), JSON.toJSONString(orderDto));
            TimeUnit.MILLISECONDS.sleep(10);
            orderDto.setPayStatus(getStatus(1));
            orderDto.setTimestamp(System.currentTimeMillis());
            kafkaTemplate.send(Constants.TOPIC_ORDER, orderDto.getOrderNo(), JSON.toJSONString(orderDto));
            TimeUnit.MILLISECONDS.sleep(10);
            orderDto.setPayStatus(getStatus(2));
            orderDto.setTimestamp(System.currentTimeMillis());
            kafkaTemplate.send(Constants.TOPIC_ORDER, orderDto.getOrderNo(), JSON.toJSONString(orderDto));
        }
        return "success";
    }

    private String getStatus(int status){
        return status == 0 ? "待支付" : status == 1 ? "已支付" : "支付失败";
    }
}

application.properties 配置

# kafka地址
spring.kafka.bootstrap-servers=192.168.x.x:9092
spring.kafka.producer.key-serializer=org.apache.kafka.common.serialization.StringSerializer
spring.kafka.producer.value-serializer=org.apache.kafka.common.serialization.StringSerializer

启动类

@Slf4j
@SpringBootApplication
public class BootKafkaApplication {

    public static void main(String[] args) {
        SpringApplication.run(BootKafkaApplication.class, args);
    }

    /**
     * 配置线程池
     * @return
     */
    @Bean
    public OrderThreadPool<OrderWorker, InterOrderDto> orderThreadPool(){
        OrderThreadPool<OrderWorker, InterOrderDto> threadPool =
            new OrderThreadPool<>(3, () -> new OrderWorker(100));
        Runtime.getRuntime().addShutdownHook(new Thread(() -> {
            log.info("shutdown orderThreadPool");
            //容器关闭时让工作线程中的任务都被消费完
            threadPool.shutdown();
        }));
        return threadPool;
    }

}

测试

访问: http://localhost:8080/send， 结果:

OWorder-0 worker start take 
OWorder-0 consume msg: {"orderNo":"0","partition":"2","payStatus":"待支付","timestamp":1706084482134,"uniqueNo":"0"}
OWorder-0 consume msg: {"orderNo":"0","partition":"2","payStatus":"已支付","timestamp":1706084482271,"uniqueNo":"0"}
OWorder-0 consume msg: {"orderNo":"0","partition":"2","payStatus":"支付失败","timestamp":1706084482282,"uniqueNo":"0"}
OWorder-0 consume msg: {"orderNo":"3","partition":"2","payStatus":"待支付","timestamp":1706084482326,"uniqueNo":"3"}
OWorder-0 consume msg: {"orderNo":"3","partition":"2","payStatus":"已支付","timestamp":1706084482336,"uniqueNo":"3"}
OWorder-0 consume msg: {"orderNo":"3","partition":"2","payStatus":"支付失败","timestamp":1706084482347,"uniqueNo":"3"}
OWorder-0 consume msg: {"orderNo":"6","partition":"1","payStatus":"待支付","timestamp":1706084482391,"uniqueNo":"6"}
OWorder-0 consume msg: {"orderNo":"6","partition":"1","payStatus":"已支付","timestamp":1706084482401,"uniqueNo":"6"}
OWorder-0 consume msg: {"orderNo":"6","partition":"1","payStatus":"支付失败","timestamp":1706084482412,"uniqueNo":"6"}

可以发现，在我们工作线程中，事件消费是有序的

good luck!