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RocketMQ中如何实现并行模式

这篇文章主要介绍了RocketMQ中如何实现并行模式,具有一定借鉴价值,感兴趣的朋友可以参考下,希望大家阅读完这篇文章之后大有收获,下面让小编带着大家一起了解一下。

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DefaultMQPushConsumerImpl.pullMessage中的PullCallback在接收到拉取的message之后,会调用ConsumeMessageService.submitConsumeRequest方法将消息“推”给listener来执行业务处理。RocketMQ支持并行和顺序两种消费模式,本文主要讲解并行模式ConsumeMessageConcurrentlyService的实现。该类包含一下关键属性:

public class ConsumeMessageConcurrentlyService implements ConsumeMessageService {
    // ...
    private final MessageListenerConcurrently messageListener; // 业务处理回掉
    private final BlockingQueue consumeRequestQueue;  // consumerExecutor的并发队列
    private final ThreadPoolExecutor consumeExecutor;
    private final String consumerGroup;

    // ...

    public ConsumeMessageConcurrentlyService(DefaultMQPushConsumerImpl defaultMQPushConsumerImpl,
        MessageListenerConcurrently messageListener) {
        this.defaultMQPushConsumerImpl = defaultMQPushConsumerImpl;
        this.messageListener = messageListener;

        this.defaultMQPushConsumer = this.defaultMQPushConsumerImpl.getDefaultMQPushConsumer();
        this.consumerGroup = this.defaultMQPushConsumer.getConsumerGroup();
        this.consumeRequestQueue = new LinkedBlockingQueue();

        this.consumeExecutor = new ThreadPoolExecutor(
            this.defaultMQPushConsumer.getConsumeThreadMin(),
            this.defaultMQPushConsumer.getConsumeThreadMax(),
            1000 * 60,
            TimeUnit.MILLISECONDS,
            this.consumeRequestQueue,
            new ThreadFactoryImpl("ConsumeMessageThread_"));

        this.scheduledExecutorService = Executors.newSingleThreadScheduledExecutor(new ThreadFactoryImpl("ConsumeMessageScheduledThread_"));
        this.cleanExpireMsgExecutors = Executors.newSingleThreadScheduledExecutor(new ThreadFactoryImpl("CleanExpireMsgScheduledThread_"));
    }

    //...
}

ConsumeMessageConcurrentlyService.submitConsumeRequest会将拉取到的message列表按配置的分批策略做分割,提交执行:

    public void submitConsumeRequest(
        final List msgs,
        final ProcessQueue processQueue,
        final MessageQueue messageQueue,
        final boolean dispatchToConsume) {
        final int consumeBatchSize = this.defaultMQPushConsumer.getConsumeMessageBatchMaxSize(); // 配置的批次大小
        if (msgs.size() <= consumeBatchSize) {
            // 拉取的消息列表长度小于配置的批次大小,一次性提交处理
            ConsumeRequest consumeRequest = new ConsumeRequest(msgs, processQueue, messageQueue);
            try {
                this.consumeExecutor.submit(consumeRequest);
            } catch (RejectedExecutionException e) {
                this.submitConsumeRequestLater(consumeRequest);
            }
        } else {
            // 否则,将message分割后提交
            for (int total = 0; total < msgs.size(); ) {
                List msgThis = new ArrayList(consumeBatchSize);
                for (int i = 0; i < consumeBatchSize; i++, total++) {
                    if (total < msgs.size()) {
                        msgThis.add(msgs.get(total));
                    } else {
                        break;
                    }
                }

                ConsumeRequest consumeRequest = new ConsumeRequest(msgThis, processQueue, messageQueue);
                try {
                    this.consumeExecutor.submit(consumeRequest);
                } catch (RejectedExecutionException e) {
                    for (; total < msgs.size(); total++) {
                        msgThis.add(msgs.get(total));
                    }

                    this.submitConsumeRequestLater(consumeRequest);
                }
            }
        }
    }

实际处理逻辑在ConsumeRequest.run方法中

    // ConsumeRequest    
    public void run() {
            if (this.processQueue.isDropped()) {
                log.info("the message queue not be able to consume, because it's dropped. group={} {}", ConsumeMessageConcurrentlyService.this.consumerGroup, this.messageQueue);
                return;
            }

            MessageListenerConcurrently listener = ConsumeMessageConcurrentlyService.this.messageListener;
            ConsumeConcurrentlyContext context = new ConsumeConcurrentlyContext(messageQueue);
            ConsumeConcurrentlyStatus status = null;
            defaultMQPushConsumerImpl.resetRetryAndNamespace(msgs, defaultMQPushConsumer.getConsumerGroup());

            ConsumeMessageContext consumeMessageContext = null;
            // ....

            long beginTimestamp = System.currentTimeMillis();
            boolean hasException = false;
            ConsumeReturnType returnType = ConsumeReturnType.SUCCESS;
            try {
                if (msgs != null && !msgs.isEmpty()) {
                    for (MessageExt msg : msgs) {
                        MessageAccessor.setConsumeStartTimeStamp(msg, String.valueOf(System.currentTimeMillis()));
                    }
                }
                // 1. 调用listener
                status = listener.consumeMessage(Collections.unmodifiableList(msgs), context);
            } catch (Throwable e) {
                log.warn("consumeMessage exception: {} Group: {} Msgs: {} MQ: {}",
                    RemotingHelper.exceptionSimpleDesc(e),
                    ConsumeMessageConcurrentlyService.this.consumerGroup,
                    msgs,
                    messageQueue);
                hasException = true;
            }
            long consumeRT = System.currentTimeMillis() - beginTimestamp;
            // ...

            if (!processQueue.isDropped()) {
                // 2. 处理业务调用结果
                ConsumeMessageConcurrentlyService.this.processConsumeResult(status, context, this);
            } else {
                // ...
            }
        }
    }

processConsumeResult将处理消费结果:

    public void processConsumeResult(
        final ConsumeConcurrentlyStatus status,
        final ConsumeConcurrentlyContext context,
        final ConsumeRequest consumeRequest
    ) {
        int ackIndex = context.getAckIndex(); // 消费成功的index

        if (consumeRequest.getMsgs().isEmpty())
            return;

        // ...

        // 1. 消费失败msg处理
        switch (this.defaultMQPushConsumer.getMessageModel()) {
            case BROADCASTING:
                for (int i = ackIndex + 1; i < consumeRequest.getMsgs().size(); i++) {
                    // 广播模式,仅打印消费失败的msg
                    MessageExt msg = consumeRequest.getMsgs().get(i);
                    log.warn("BROADCASTING, the message consume failed, drop it, {}", msg.toString());
                }
                break;
            case CLUSTERING:
                // 集群模式,首先尝试将消费失败的msg发回到broker,若失败则在本地尝试reconsume
                List msgBackFailed = new ArrayList(consumeRequest.getMsgs().size());
                for (int i = ackIndex + 1; i < consumeRequest.getMsgs().size(); i++) {
                    MessageExt msg = consumeRequest.getMsgs().get(i);
                    boolean result = this.sendMessageBack(msg, context);
                    if (!result) {
                        msg.setReconsumeTimes(msg.getReconsumeTimes() + 1);
                        msgBackFailed.add(msg);
                    }
                }

                if (!msgBackFailed.isEmpty()) {
                    consumeRequest.getMsgs().removeAll(msgBackFailed);

                    this.submitConsumeRequestLater(msgBackFailed, consumeRequest.getProcessQueue(), consumeRequest.getMessageQueue());
                }
                break;
            default:
                break;
        }

        // 2. 更新offset store
        long offset = consumeRequest.getProcessQueue().removeMessage(consumeRequest.getMsgs());
        if (offset >= 0 && !consumeRequest.getProcessQueue().isDropped()) {
            this.defaultMQPushConsumerImpl.getOffsetStore().updateOffset(consumeRequest.getMessageQueue(), offset, true);
        }
    }

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标题名称:RocketMQ中如何实现并行模式
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