RocketMQ消息消费源码分析(二消息的消费)

首先回到DefaultMQPushConsumerImpl start方法

public synchronized void start() throws MQClientException {
        switch(this.serviceState) {
        case CREATE_JUST:
            this.log.info("the consumer [{}] start beginning. messageModel={}, isUnitMode={}", new Object[]{this.defaultMQPushConsumer.getConsumerGroup(), this.defaultMQPushConsumer.getMessageModel(), this.defaultMQPushConsumer.isUnitMode()});
            this.serviceState = ServiceState.START_FAILED;
            this.checkConfig();
            this.copySubscription();
            if (this.defaultMQPushConsumer.getMessageModel() == MessageModel.CLUSTERING) {
                this.defaultMQPushConsumer.changeInstanceNameToPID();
            }

            this.mQClientFactory = MQClientManager.getInstance().getAndCreateMQClientInstance(this.defaultMQPushConsumer, this.rpcHook);
            this.rebalanceImpl.setConsumerGroup(this.defaultMQPushConsumer.getConsumerGroup());
            this.rebalanceImpl.setMessageModel(this.defaultMQPushConsumer.getMessageModel());
            this.rebalanceImpl.setAllocateMessageQueueStrategy(this.defaultMQPushConsumer.getAllocateMessageQueueStrategy());
            this.rebalanceImpl.setmQClientFactory(this.mQClientFactory);
            this.pullAPIWrapper = new PullAPIWrapper(this.mQClientFactory, this.defaultMQPushConsumer.getConsumerGroup(), this.isUnitMode());
            this.pullAPIWrapper.registerFilterMessageHook(this.filterMessageHookList);
            if (this.defaultMQPushConsumer.getOffsetStore() != null) {
                this.offsetStore = this.defaultMQPushConsumer.getOffsetStore();
            } else {
                switch(this.defaultMQPushConsumer.getMessageModel()) {
                case BROADCASTING:
                    this.offsetStore = new LocalFileOffsetStore(this.mQClientFactory, this.defaultMQPushConsumer.getConsumerGroup());
                    break;
                case CLUSTERING:
                    this.offsetStore = new RemoteBrokerOffsetStore(this.mQClientFactory, this.defaultMQPushConsumer.getConsumerGroup());
                }

                this.defaultMQPushConsumer.setOffsetStore(this.offsetStore);
            }

            this.offsetStore.load();
            if (this.getMessageListenerInner() instanceof MessageListenerOrderly) {
                this.consumeOrderly = true;
                this.consumeMessageService = new ConsumeMessageOrderlyService(this, (MessageListenerOrderly)this.getMessageListenerInner());
            } else if (this.getMessageListenerInner() instanceof MessageListenerConcurrently) {
                this.consumeOrderly = false;
                this.consumeMessageService = new ConsumeMessageConcurrentlyService(this, (MessageListenerConcurrently)this.getMessageListenerInner());
            }

            this.consumeMessageService.start();
            boolean registerOK = this.mQClientFactory.registerConsumer(this.defaultMQPushConsumer.getConsumerGroup(), this);
            if (!registerOK) {
                this.serviceState = ServiceState.CREATE_JUST;
                this.consumeMessageService.shutdown();
                throw new MQClientException("The consumer group[" + this.defaultMQPushConsumer.getConsumerGroup() + "] has been created before, specify another name please." + FAQUrl.suggestTodo("http://rocketmq.apache.org/docs/faq/"), (Throwable)null);
            } else {
                this.mQClientFactory.start();
                this.log.info("the consumer [{}] start OK.", this.defaultMQPushConsumer.getConsumerGroup());
                this.serviceState = ServiceState.RUNNING;
            }
        default:
            this.updateTopicSubscribeInfoWhenSubscriptionChanged();
            this.mQClientFactory.checkClientInBroker();
            this.mQClientFactory.sendHeartbeatToAllBrokerWithLock();
            this.mQClientFactory.rebalanceImmediately();
            return;
        case RUNNING:
        case SHUTDOWN_ALREADY:
        case START_FAILED:
            throw new MQClientException("The PushConsumer service state not OK, maybe started once, " + this.serviceState + FAQUrl.suggestTodo("http://rocketmq.apache.org/docs/faq/"), (Throwable)null);
        }
    }

这里主要分析

this.consumeMessageService = new ConsumeMessageConcurrentlyService(this, (MessageListenerConcurrently)this.getMessageListenerInner());

先看下consumeMessageService的构造函数

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<Runnable>();

        this.consumeExecutor = new ThreadPoolExecutor(
                //线程池的常驻线程数：consumeThreadMin
            this.defaultMQPushConsumer.getConsumeThreadMin(),
            //线程池的最大线程数：consumeThreadMax
            this.defaultMQPushConsumer.getConsumeThreadMax(),
            1000 * 60,
            TimeUnit.MILLISECONDS,
            this.consumeRequestQueue,
            //线程池中的线程名：ConsumeMessageThread_
            new ThreadFactoryImpl("ConsumeMessageThread_"));

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

在这个构造函数中，new了一个名字叫consumeExecutor的线程池，在并发消费的模式下，这个线程池也就是消费消息的方式，我们先回到消息消费的入口处，我们上篇（一）中也提到了在回调函数中

//消费消息服务提交
DefaultMQPushConsumerImpl.this.consumeMessageService.submitConsumeRequest(
                                    pullResult.getMsgFoundList(),
                                    processQueue,
                                    pullRequest.getMessageQueue(),
                                    dispatchToConsume);

把拉取到的消息（默认为32条）提交到consumeMessageService中,进入submitConsumeRequest方法：

final int consumeBatchSize = this.defaultMQPushConsumer.getConsumeMessageBatchMaxSize();
if (msgs.size() <= consumeBatchSize) {
            ConsumeRequest consumeRequest = new ConsumeRequest(msgs, processQueue, messageQueue);
            try {
                //consumeExecutor : 消费端消费线程池
                this.consumeExecutor.submit(consumeRequest);
            } catch (RejectedExecutionException e) {
                this.submitConsumeRequestLater(consumeRequest);
            }
        }

第一步：获取默认的处理大小，一直觉得这个字段的命名有点歧义，这个字段是用来处理消费端每次消费消息的条数，不是从broker端拉取过来的消息的条数
第二步：判断从broker拉取过来的消息是否大于consumeBatchSize，一般consumeBatchSize都设置为1，默认值也是1，下面直接去看else逻辑

for (int total = 0; total < msgs.size(); ) {
    List<MessageExt> msgThis = new ArrayList<MessageExt>(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);
    }
}

把消息按照consumeBatchSize分组，组装成ConsumeRequest对象，提交到consumeExecutor线程池中，我们看下ConsumeRequest的run方法

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;
            }

第一步：判断processQueue的dropped属性，这个属性在负载均衡中会处理，判断需不需要继续消费这个processQueue拉取到的消息

MessageListenerConcurrently listener = ConsumeMessageConcurrentlyService.this.messageListener;
            ConsumeConcurrentlyContext context = new ConsumeConcurrentlyContext(messageQueue);
            ConsumeConcurrentlyStatus status = null;

第二步：拿到业务系统定义的消息监听listener

ConsumeMessageContext consumeMessageContext = null;
            if (ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.hasHook()) {
                consumeMessageContext = new ConsumeMessageContext();
                consumeMessageContext.setConsumerGroup(defaultMQPushConsumer.getConsumerGroup());
                consumeMessageContext.setProps(new HashMap<String, String>());
                consumeMessageContext.setMq(messageQueue);
                consumeMessageContext.setMsgList(msgs);
                consumeMessageContext.setSuccess(false);
                ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.executeHookBefore(consumeMessageContext);
            }

第三步：判断是否有钩子函数，执行before方法

//设置消息的重试主题，并开始消费消息，并返回该批次消息消费结果：
long beginTimestamp = System.currentTimeMillis();
boolean hasException = false;
ConsumeReturnType returnType = ConsumeReturnType.SUCCESS;
try {
    ConsumeMessageConcurrentlyService.this.resetRetryTopic(msgs);
    if (msgs != null && !msgs.isEmpty()) {
        for (MessageExt msg : msgs) {
            MessageAccessor.setConsumeStartTimeStamp(msg, String.valueOf(System.currentTimeMillis()));
        }
    }
    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;
}

第四步：调用resetRetryTopic方法设置消息的重试主题
第五步：执行listener.consumeMessage，业务系统具体去消费消息，如果消费成功那么返回status返回CONSUME_SUCCESS，如果有异常想重试，那么返回RECONSUME_LATER

if (ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.hasHook()) {
                consumeMessageContext.setStatus(status.toString());
                consumeMessageContext.setSuccess(ConsumeConcurrentlyStatus.CONSUME_SUCCESS == status);
                ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.executeHookAfter(consumeMessageContext);
            }

第六步：执行钩子函数after方法

//对消费结果的处理
if (!processQueue.isDropped()) {
    ConsumeMessageConcurrentlyService.this.processConsumeResult(status, context, this);
} else {
    log.warn("processQueue is dropped without process consume result. messageQueue={}, msgs={}", messageQueue, msgs);
}

第七步：processConsumeResult来对消费结果进行处理，进入processConsumeResult方法

int ackIndex = context.getAckIndex();
if (consumeRequest.getMsgs().isEmpty())
    return;
switch (status) {
    case CONSUME_SUCCESS:
        if (ackIndex >= consumeRequest.getMsgs().size()) {
            ackIndex = consumeRequest.getMsgs().size() - 1;
        }
        int ok = ackIndex + 1;
        int failed = consumeRequest.getMsgs().size() - ok;
        this.getConsumerStatsManager().incConsumeOKTPS(consumerGroup, consumeRequest.getMessageQueue().getTopic(), ok);
        this.getConsumerStatsManager().incConsumeFailedTPS(consumerGroup, consumeRequest.getMessageQueue().getTopic(), failed);
        break;
    case RECONSUME_LATER:
        ackIndex = -1;
        this.getConsumerStatsManager().incConsumeFailedTPS(consumerGroup, consumeRequest.getMessageQueue().getTopic(),
            consumeRequest.getMsgs().size());
        break;
    default:
        break;
}

第八步：定义了ackIndex，这个值初始化等于Integer.MAX_VALUE，如果返回成功，那么ackIndex=消息数-1，如果返回失败ackIndex=-1

case CLUSTERING:
//集群模式下
List<MessageExt> msgBackFailed = new ArrayList<MessageExt>(consumeRequest.getMsgs().size());
for (int i = ackIndex + 1; i < consumeRequest.getMsgs().size(); i++) {
    MessageExt msg = consumeRequest.getMsgs().get(i);
    //发送sendMessageBack
    boolean result = this.sendMessageBack(msg, context);
    if (!result) {
        msg.setReconsumeTimes(msg.getReconsumeTimes() + 1);
        msgBackFailed.add(msg);
    }
}
if (!msgBackFailed.isEmpty()) {
    consumeRequest.getMsgs().removeAll(msgBackFailed);
    //更新消息消费进度，不管消费成功与否，上述这些消息消费成功，其实就是修改消费偏移量。（失败的，会进行重试，会创建新的消息)
    this.submitConsumeRequestLater(msgBackFailed, consumeRequest.getProcessQueue(), consumeRequest.getMessageQueue());
}

第九步：集群模式下，判断ackIndex，如果等于-1，那么就要调用sendMessageBack方法，就是消息的ACK，所以在RocketMQ中，只有失败的消息才会ACK，这个方法是把消费失败的消息重新发送给broker，broker的处理逻辑就是根据重试次数依托定时消息机制来完成消息重试，broker在重试消息的时候会创建一个条新的消息，而不是用老的消息，如果到达一定的次数，那么进入死信队列，我在工作中会把即将进入死信队列的消息拿出来以json的格式放入mongodb中，通过界面的方法展示这些失败的消息，并在界面上继续提供重试的功能来处理这些失败的消息。如果重新发送失败，那么会延迟5s后重新消费。

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

第十步：不管是消费成功还是消费失败的消息，都会更新消费进度，首先从processQueue中移除所有消费成功的消息并返回offset，这里要注意一点，就是这个offset是processQueue中的msgTreeMap的最小的key，为什么要这样做呢，我的理解也是无奈之举，因为消费进度的推进是offset决定的，因为是线程池消费，不能保证先消费的是offset大的那条消息，所以推进消费进度只能取最小的那条消息的offset，这样在消费端重启的时候就可能会导致消息重复消费。

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RocketMQ消息消费源码分析(二消息的消费)

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