RocketMQ源码解析八（Consumer并发消费消息）

快来打我* 2022-09-12 07:47 25阅读 0赞

> **RocketMQ版本4.6.0，记录自己看源码的过程**

回顾一下消息拉取，PullMessageService 负责对消息队列进行消息拉取，从远端服务器拉取消息后将消息存人ProcessQueue消息队列处理队列中，然后调用ConsumeMessageService\#submitConsumeRequest方法进行消息消费，使用线程池来消费消息，确保了消息拉取与消息消费的解耦。RocketMQ使用ConsumeMessageService来实现消息消费的处理逻辑。RocketMQ支持顺序消费与并发消费，这里将重点关注并发消费的消费流程，顺序消费将在之后的文档分析。

消息拉取一文中提到会将消息任务提交给ConsumeMessageConcurrentlyService中的线程池执行，这里再重新看下

/** * 提交消费消息请求到线程池中消费 */
    @Override
    public void submitConsumeRequest(
        final List<MessageExt> msgs,
        final ProcessQueue processQueue,
        final MessageQueue messageQueue,
        final boolean dispatchToConsume) { 
        // 一次消费几条消息，默认为1条
        final int consumeBatchSize = this.defaultMQPushConsumer.getConsumeMessageBatchMaxSize();
        // 如果一次拉取的消息数量<=并发消费数量，则一次性将这一批消息都放到consumeRequest中提交给消费线程池消费
        if (msgs.size() <= consumeBatchSize) { 
            ConsumeRequest consumeRequest = new ConsumeRequest(msgs, processQueue, messageQueue);
            try { 
                // 将消费任务提交给消费线程池消费
                this.consumeExecutor.submit(consumeRequest);
            } catch (RejectedExecutionException e) { 
                this.submitConsumeRequestLater(consumeRequest);
            }
        } else { 
            // 分批次提交，默认每次提交1条
            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);
                }
            }
        }
    }

如果拉取的消息条数大于consumeMessageBatchMaxSize，则对拉取消息进行分页，每页consumeMessageBatchMaxSize条消息，创建多个ConsumeRequest任务并提交到消费线程池。

/** * 消费线程 */
    class ConsumeRequest implements Runnable { 
        // 默认是1条
        private final List<MessageExt> msgs;
        private final ProcessQueue processQueue;
        private final MessageQueue messageQueue;
    
        public ConsumeRequest(List<MessageExt> msgs, ProcessQueue processQueue, MessageQueue messageQueue) { 
            this.msgs = msgs;
            this.processQueue = processQueue;
            this.messageQueue = messageQueue;
        }
    
        public List<MessageExt> getMsgs() { 
            return msgs;
        }
    
        public ProcessQueue getProcessQueue() { 
            return processQueue;
        }
    
        @Override
        public void run() { 
            // 先判断processQueue的dropped，如果为true，则说明可能在重平衡时该消息队列被分配给
            // 别的消费者了，应该停止对该消息队列的消费
            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;
            }
    
            // 在启动consumer时设置的监听
            MessageListenerConcurrently listener = ConsumeMessageConcurrentlyService.this.messageListener;
            ConsumeConcurrentlyContext context = new ConsumeConcurrentlyContext(messageQueue);
            ConsumeConcurrentlyStatus status = null;
          
            // 如果此消息的主题为（%RETRY%+消费组的名称），那么将会将此消息的topic重置为原始消息的topic。
            // 即此消息的真实topic会存储在properties当中，键为RETRY_TOPIC，值为真实topic，将真实topic取出赋予此消息
            defaultMQPushConsumerImpl.resetRetryAndNamespace(msgs, defaultMQPushConsumer.getConsumerGroup());
    
            ConsumeMessageContext consumeMessageContext = null;
            if (ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.hasHook()) { 
                consumeMessageContext = new ConsumeMessageContext();
                consumeMessageContext.setNamespace(defaultMQPushConsumer.getNamespace());
                consumeMessageContext.setConsumerGroup(defaultMQPushConsumer.getConsumerGroup());
                consumeMessageContext.setProps(new HashMap<String, String>());
                consumeMessageContext.setMq(messageQueue);
                consumeMessageContext.setMsgList(msgs);
                consumeMessageContext.setSuccess(false);
                ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.executeHookBefore(consumeMessageContext);
            }
    
            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()));
                    }
                }
                // 调用消息监听器
                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 (null == status) { 
                // 表示消费出现异常了并且没有进行处理
                if (hasException) { 
                    returnType = ConsumeReturnType.EXCEPTION;
                } else { 
                    // 返回null
                    returnType = ConsumeReturnType.RETURNNULL;
                }
            } else if (consumeRT >= defaultMQPushConsumer.getConsumeTimeout() * 60 * 1000) {  // 超时
                returnType = ConsumeReturnType.TIME_OUT;
            } else if (ConsumeConcurrentlyStatus.RECONSUME_LATER == status) {  // 消费失败
                returnType = ConsumeReturnType.FAILED;
            } else if (ConsumeConcurrentlyStatus.CONSUME_SUCCESS == status) {  // 消费成功
                returnType = ConsumeReturnType.SUCCESS;
            }
    
            if (ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.hasHook()) { 
                consumeMessageContext.getProps().put(MixAll.CONSUME_CONTEXT_TYPE, returnType.name());
            }
    
            // 不管是异常还是返回null，都需要重试消息
            if (null == status) { 
                log.warn("consumeMessage return null, Group: {} Msgs: {} MQ: {}",
                    ConsumeMessageConcurrentlyService.this.consumerGroup,
                    msgs,
                    messageQueue);
                status = ConsumeConcurrentlyStatus.RECONSUME_LATER;
            }
    
            if (ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.hasHook()) { 
                consumeMessageContext.setStatus(status.toString());
                consumeMessageContext.setSuccess(ConsumeConcurrentlyStatus.CONSUME_SUCCESS == status);
                ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.executeHookAfter(consumeMessageContext);
            }
    
            ConsumeMessageConcurrentlyService.this.getConsumerStatsManager()
                .incConsumeRT(ConsumeMessageConcurrentlyService.this.consumerGroup, messageQueue.getTopic(), consumeRT);
    
            if (!processQueue.isDropped()) { 
                // 处理消费结果
                ConsumeMessageConcurrentlyService.this.processConsumeResult(status, context, this);
            } else { 
                log.warn("processQueue is dropped without process consume result. messageQueue={}, msgs={}", messageQueue, msgs);
            }
        }
    
        public MessageQueue getMessageQueue() { 
            return messageQueue;
        }
    
    }

Step1：先判断processQueue的dropped，如果为true，则说明可能在重平衡时该消息队列被分配给别的消费者了，应该停止对该消息队列的消费。  
Step2：如果消息是重试消息，则会将消息的topic和queueId还原成原本的topic和queueId。  
Step3：构建ConsumeMessageContext对象。  
Step4：调用消息监听器。  
Step5：如果processQueue没被停止则处理消费结果。

看看如何处理消费结果

/** * 处理消费结果 */
    public void processConsumeResult(
        final ConsumeConcurrentlyStatus status,
        final ConsumeConcurrentlyContext context,
        final ConsumeRequest consumeRequest
    ) { 
        // 设置ackIndex，这个值在创建ConsumeConcurrentlyContext时默认为Integer.MAX_VALUE
        int ackIndex = context.getAckIndex();
    
        if (consumeRequest.getMsgs().isEmpty())
            return;
    
        switch (status) { 
            // 消费成功
            case CONSUME_SUCCESS:
                // 设置ackIndex值为 消息数-1，默认情况下这个值是0
                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;
            // 需要重试消息
            case RECONSUME_LATER:
                // 设置为-1用于下面重发消息
                ackIndex = -1;
                this.getConsumerStatsManager().incConsumeFailedTPS(consumerGroup, consumeRequest.getMessageQueue().getTopic(),
                    consumeRequest.getMsgs().size());
                break;
            default:
                break;
        }
    
        switch (this.defaultMQPushConsumer.getMessageModel()) { 
            // 广播模式不会重试消息，消费失败就丢弃了，也相当于消费成功了
            case BROADCASTING:
                for (int i = ackIndex + 1; i < consumeRequest.getMsgs().size(); i++) { 
                    MessageExt msg = consumeRequest.getMsgs().get(i);
                    log.warn("BROADCASTING, the message consume failed, drop it, {}", msg.toString());
                }
                break;
            case CLUSTERING:
                List<MessageExt> msgBackFailed = new ArrayList<MessageExt>(consumeRequest.getMsgs().size());
                // 重发这批并发消息，默认只有1条（会重新生成新的消息，这批消息默认消费成功，会更新消费进度，不会卡在这）
                for (int i = ackIndex + 1; i < consumeRequest.getMsgs().size(); i++) { 
                    MessageExt msg = consumeRequest.getMsgs().get(i);
                    // 重新将消息发到broker
                    boolean result = this.sendMessageBack(msg, context);
                    if (!result) { 
                        msg.setReconsumeTimes(msg.getReconsumeTimes() + 1);
                        msgBackFailed.add(msg);
                    }
                }
    
                // 如果重发消息失败，则会将这些发送失败的消息重新包装起来5S后转发给消费线程池继续消费
                if (!msgBackFailed.isEmpty()) { 
                    consumeRequest.getMsgs().removeAll(msgBackFailed);
    
                    this.submitConsumeRequestLater(msgBackFailed, consumeRequest.getProcessQueue(), consumeRequest.getMessageQueue());
                }
                break;
            default:
                break;
        }
    
        // 不管这条消息消费成功与否，都会更新消费进度，表示该条消息消费成功
        // 将这次消费的消息从ProcessQueue中移除
        // 这里的返回值分两种情况：
        // 1、如果删除该消息列表后processQueue为空了，则offset为processQueue中最大的偏移量+1，消费进度推进到最后面
        // 2、如果processQueue不为空，则offset为processQueue中剩余的第一条消息，消费进度只能推进到这
        long offset = consumeRequest.getProcessQueue().removeMessage(consumeRequest.getMsgs());
        if (offset >= 0 && !consumeRequest.getProcessQueue().isDropped()) { 
            // 更新本地消费进度，后台定时任务会定时将该消费进度同步到broker中
            this.defaultMQPushConsumerImpl.getOffsetStore().updateOffset(consumeRequest.getMessageQueue(), offset, true);
        }
    }

消息消费状态有两种，CONSUME\_SUCCESS表示消费成功，RECONSUME\_LATER表示需要重试消息。当重试时，这些并发消息都会进行重试，rocketmq会为每条消息重新创建一条与原先消息属性相同的消息，拥有一个唯一的新msgId，并存储原消息ID，该消息会存入到commitLog文件中，与原先的消息没有任何关联，该消息也会进入到ConsumerQueue队列中，将拥有一个全新的队列偏移量。重试消息详细流程在后面文档再分析。

当然，不管消费成功与否，都会将这次消费的消息从ProcessQueue中删除

public long removeMessage(final List<MessageExt> msgs) { 
        long result = -1;
        final long now = System.currentTimeMillis();
        try { 
            this.lockTreeMap.writeLock().lockInterruptibly();
            this.lastConsumeTimestamp = now;
            try { 
                if (!msgTreeMap.isEmpty()) { 
                    result = this.queueOffsetMax + 1;
                    int removedCnt = 0;
                    // 将这次批量消费的消息都从msgTreeMap中删除
                    for (MessageExt msg : msgs) { 
                        MessageExt prev = msgTreeMap.remove(msg.getQueueOffset());
                        if (prev != null) { 
                            removedCnt--;
                            msgSize.addAndGet(0 - msg.getBody().length);
                        }
                    }
                    msgCount.addAndGet(removedCnt);
    
                    // 如果删除完后processQueue已经没消息了，表示消息都消费成功了，则消费进度更新到
                    // 队列中最大的偏移量+1处，如果map不为空，则表示还没消费完，不能将消费进度更新到
                    // 最大偏移量处，需设置在最小处，等最前面的消费成功消费后消费进度才能向后推移更新
                    if (!msgTreeMap.isEmpty()) { 
                        result = msgTreeMap.firstKey();
                    }
                }
            } finally { 
                this.lockTreeMap.writeLock().unlock();
            }
        } catch (Throwable t) { 
            log.error("removeMessage exception", t);
        }
    
        return result;
    }

并根据返回的offset更新本地消费进度，由后台定时任务定时同步到broker

public class RemoteBrokerOffsetStore implements OffsetStore { 
        /** * 保存一个消费组中每个消息队列的消费进度，会定时同步到broke中 */
        private ConcurrentMap<MessageQueue, AtomicLong> offsetTable =
            new ConcurrentHashMap<MessageQueue, AtomicLong>();
    
        /** * 更新本地消费进度，消费者在后台有一个定时任务，有定时将该消费进度同步到broker */
        @Override
        public void updateOffset(MessageQueue mq, long offset, boolean increaseOnly) { 
            if (mq != null) { 
                AtomicLong offsetOld = this.offsetTable.get(mq);
                if (null == offsetOld) { 
                    offsetOld = this.offsetTable.putIfAbsent(mq, new AtomicLong(offset));
                }
    
                if (null != offsetOld) { 
                    if (increaseOnly) { 
                        MixAll.compareAndIncreaseOnly(offsetOld, offset);
                    } else { 
                        offsetOld.set(offset);
                    }
                }
            }
        }
    }

![在这里插入图片描述][c488c6d5711a7bd5d49cb0f2224c0acb.png_pic_center]

**参考资料**  
《儒猿技术窝——从 0 开始带你成为消息中间件实战高手》

[c488c6d5711a7bd5d49cb0f2224c0acb.png_pic_center]: /images/20220828/b453015cfe78438fae636b25c8b7d3c5.png