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1、概述

本文接:《RocketMQ 源码分析 —— Message 拉取与消费(上)》

主要解析 Consumer消费 逻辑涉及到的源码。

2、Consumer

MQ 提供了两类消费者:

  • PushConsumer:
    • 在大多数场景下使用。
    • 名字虽然是 Push 开头,实际在实现时,使用 Pull 方式实现。通过 Pull 不断不断不断轮询 Broker 获取消息。当不存在新消息时,Broker挂起请求,直到有新消息产生,取消挂起,返回新消息。这样,基本和 Broker 主动 Push 做到接近的实时性(当然,还是有相应的实时性损失)。原理类似 长轮询( Long-Polling )
  • PullConsumer

本文主要讲解PushConsumer,部分讲解PullConsumer,跳过顺序消费
本文主要讲解PushConsumer,部分讲解PullConsumer,跳过顺序消费
本文主要讲解PushConsumer,部分讲解PullConsumer,跳过顺序消费

3、PushConsumer 一览

先看一张 PushConsumer 包含的组件以及组件之间的交互图:

PushConsumer手绘图.png

  • RebalanceService:均衡消息队列服务,负责分配当前 Consumer 可消费的消息队列( MessageQueue )。当有新的 Consumer 的加入或移除,都会重新分配消息队列。
  • PullMessageService:拉取消息服务,不断不断不断Broker 拉取消息,并提交消费任务到 ConsumeMessageService
  • ConsumeMessageService:消费消息服务,不断不断不断消费消息,并处理消费结果。
  • RemoteBrokerOffsetStoreConsumer 消费进度管理,负责从 Broker 获取消费进度,同步消费进度到 Broker
  • ProcessQueue :消息处理队列。
  • MQClientInstance :封装对 NamesrvBroker 的 API调用,提供给 ProducerConsumer 使用。

4、PushConsumer 订阅

DefaultMQPushConsumerImpl#subscribe(…)

1: public void subscribe(String topic, String subExpression) throws MQClientException {
2: try {
3: // 创建订阅数据
4: SubscriptionData subscriptionData = FilterAPI.buildSubscriptionData(this.defaultMQPushConsumer.getConsumerGroup(), //
5: topic, subExpression);
6: this.rebalanceImpl.getSubscriptionInner().put(topic, subscriptionData);
7: // 通过心跳同步Consumer信息到Broker
8: if (this.mQClientFactory != null) {
9: this.mQClientFactory.sendHeartbeatToAllBrokerWithLock();
10: }
11: } catch (Exception e) {
12: throw new MQClientException("subscription exception", e);
13: }
14: }
  • 说明 :订阅 Topic
  • 第 3 至 6 行 :创建订阅数据。详细解析见:FilterAPI.buildSubscriptionData(…)
  • 第 7 至 10 行 :通过心跳同步 Consumer 信息到 Broker

FilterAPI.buildSubscriptionData(…)

1: public static SubscriptionData buildSubscriptionData(final String consumerGroup, String topic,
2: String subString) throws Exception {
3: SubscriptionData subscriptionData = new SubscriptionData();
4: subscriptionData.setTopic(topic);
5: subscriptionData.setSubString(subString);
6: // 处理订阅表达式
7: if (null == subString || subString.equals(SubscriptionData.SUB_ALL) || subString.length() == 0) {
8: subscriptionData.setSubString(SubscriptionData.SUB_ALL);
9: } else {
10: String[] tags = subString.split("\\|\\|");
11: if (tags.length > 0) {
12: for (String tag : tags) {
13: if (tag.length() > 0) {
14: String trimString = tag.trim();
15: if (trimString.length() > 0) {
16: subscriptionData.getTagsSet().add(trimString);
17: subscriptionData.getCodeSet().add(trimString.hashCode());
18: }
19: }
20: }
21: } else {
22: throw new Exception("subString split error");
23: }
24: }
25:
26: return subscriptionData;
27: }
  • 说明 :根据 Topic 和 订阅表达式 创建订阅数据
  • subscriptionData.subVersion = System.currentTimeMillis()。

DefaultMQPushConsumer#registerMessageListener(…)

1: public void registerMessageListener(MessageListenerConcurrently messageListener) {
2: this.messageListener = messageListener;
3: this.defaultMQPushConsumerImpl.registerMessageListener(messageListener);
4: }
  • 说明 :注册消息监听器。

5、PushConsumer 消息队列分配

RebalanceService&PushConsumer分配队列

RebalanceService

1: public class RebalanceService extends ServiceThread {
2:
3: /**
4: * 等待间隔,单位:毫秒
5: */
6: private static long waitInterval =
7: Long.parseLong(System.getProperty(
8: "rocketmq.client.rebalance.waitInterval", "20000"));
9:
10: private final Logger log = ClientLogger.getLog();
11: /**
12: * MQClient对象
13: */
14: private final MQClientInstance mqClientFactory;
15:
16: public RebalanceService(MQClientInstance mqClientFactory) {
17: this.mqClientFactory = mqClientFactory;
18: }
19:
20: @Override
21: public void run() {
22: log.info(this.getServiceName() + " service started");
23:
24: while (!this.isStopped()) {
25: this.waitForRunning(waitInterval);
26: this.mqClientFactory.doRebalance();
27: }
28:
29: log.info(this.getServiceName() + " service end");
30: }
31:
32: @Override
33: public String getServiceName() {
34: return RebalanceService.class.getSimpleName();
35: }
36: }
  • 说明 :均衡消息队列服务,负责分配当前 Consumer 可消费的消息队列( MessageQueue )。
  • 第 26 行 :调用 MQClientInstance#doRebalance(...) 分配消息队列。目前有三种情况情况下触发:

    • 第 25 行 等待超时,每 20s 调用一次。
    • PushConsumer 启动时,调用 rebalanceService#wakeup(...) 触发。
    • Broker 通知 Consumer 加入 或 移除时,Consumer 响应通知,调用 rebalanceService#wakeup(...) 触发。

    详细解析见:MQClientInstance#doRebalance(…)

MQClientInstance#doRebalance(…)

1: public void doRebalance() {
2: for (Map.Entry<String, MQConsumerInner> entry : this.consumerTable.entrySet()) {
3: MQConsumerInner impl = entry.getValue();
4: if (impl != null) {
5: try {
6: impl.doRebalance();
7: } catch (Throwable e) {
8: log.error("doRebalance exception", e);
9: }
10: }
11: }
12: }
  • 说明 :遍历当前 Client 包含的 consumerTable( Consumer集合 ),执行消息队列分配。
  • 疑问:目前代码调试下来,consumerTable 只包含 Consumer 自己。😈有大大对这个疑问有解答的,烦请解答下。
  • 第 6 行 :调用 MQConsumerInner#doRebalance(...) 进行队列分配。DefaultMQPushConsumerImplDefaultMQPullConsumerImpl 分别对该接口方法进行了实现。DefaultMQPushConsumerImpl#doRebalance(...) 详细解析见:DefaultMQPushConsumerImpl#doRebalance(…)

DefaultMQPushConsumerImpl#doRebalance(…)

1: public void doRebalance() {
2: if (!this.pause) {
3: this.rebalanceImpl.doRebalance(this.isConsumeOrderly());
4: }
5: }

RebalanceImpl#doRebalance(…)

1: /**
2: * 执行分配消息队列
3: *
4: * @param isOrder 是否顺序消息
5: */
6: public void doRebalance(final boolean isOrder) {
7: // 分配每个 topic 的消息队列
8: Map<String, SubscriptionData> subTable = this.getSubscriptionInner();
9: if (subTable != null) {
10: for (final Map.Entry<String, SubscriptionData> entry : subTable.entrySet()) {
11: final String topic = entry.getKey();
12: try {
13: this.rebalanceByTopic(topic, isOrder);
14: } catch (Throwable e) {
15: if (!topic.startsWith(MixAll.RETRY_GROUP_TOPIC_PREFIX)) {
16: log.warn("rebalanceByTopic Exception", e);
17: }
18: }
19: }
20: }
21: // 移除未订阅的topic对应的消息队列
22: this.truncateMessageQueueNotMyTopic();
23: }
24:
25: /**
26: * 移除未订阅的消息队列
27: */
28: private void truncateMessageQueueNotMyTopic() {
29: Map<String, SubscriptionData> subTable = this.getSubscriptionInner();
30: for (MessageQueue mq : this.processQueueTable.keySet()) {
31: if (!subTable.containsKey(mq.getTopic())) {
32:
33: ProcessQueue pq = this.processQueueTable.remove(mq);
34: if (pq != null) {
35: pq.setDropped(true);
36: log.info("doRebalance, {}, truncateMessageQueueNotMyTopic remove unnecessary mq, {}", consumerGroup, mq);
37: }
38: }
39: }
40: }
  • #doRebalance(...) 说明 :执行分配消息队列。
    • 第 7 至 20 行 :循环订阅主题集合( subscriptionInner ),分配每一个 Topic 的消息队列。
    • 第 22 行 :移除未订阅的 Topic 的消息队列。
  • #truncateMessageQueueNotMyTopic(...) 说明 :移除未订阅的消息队列。当调用 DefaultMQPushConsumer#unsubscribe(topic) 时,只移除订阅主题集合( subscriptionInner ),对应消息队列移除在该方法。

RebalanceImpl#rebalanceByTopic(…)

1: private void rebalanceByTopic(final String topic, final boolean isOrder) {
2: switch (messageModel) {
3: case BROADCASTING: {
4: Set<MessageQueue> mqSet = this.topicSubscribeInfoTable.get(topic);
5: if (mqSet != null) {
6: boolean changed = this.updateProcessQueueTableInRebalance(topic, mqSet, isOrder);
7: if (changed) {
8: this.messageQueueChanged(topic, mqSet, mqSet);
9: log.info("messageQueueChanged {} {} {} {}", //
10: consumerGroup, //
11: topic, //
12: mqSet, //
13: mqSet);
14: }
15: } else {
16: log.warn("doRebalance, {}, but the topic[{}] not exist.", consumerGroup, topic);
17: }
18: break;
19: }
20: case CLUSTERING: {
21: // 获取 topic 对应的 队列 和 consumer信息
22: Set<MessageQueue> mqSet = this.topicSubscribeInfoTable.get(topic);
23: List<String> cidAll = this.mQClientFactory.findConsumerIdList(topic, consumerGroup);
24: if (null == mqSet) {
25: if (!topic.startsWith(MixAll.RETRY_GROUP_TOPIC_PREFIX)) {
26: log.warn("doRebalance, {}, but the topic[{}] not exist.", consumerGroup, topic);
27: }
28: }
29:
30: if (null == cidAll) {
31: log.warn("doRebalance, {} {}, get consumer id list failed", consumerGroup, topic);
32: }
33:
34: if (mqSet != null && cidAll != null) {
35: // 排序 消息队列 和 消费者数组。因为是在Client进行分配队列,排序后,各Client的顺序才能保持一致。
36: List<MessageQueue> mqAll = new ArrayList<>();
37: mqAll.addAll(mqSet);
38:
39: Collections.sort(mqAll);
40: Collections.sort(cidAll);
41:
42: AllocateMessageQueueStrategy strategy = this.allocateMessageQueueStrategy;
43:
44: // 根据 队列分配策略 分配消息队列
45: List<MessageQueue> allocateResult;
46: try {
47: allocateResult = strategy.allocate(//
48: this.consumerGroup, //
49: this.mQClientFactory.getClientId(), //
50: mqAll, //
51: cidAll);
52: } catch (Throwable e) {
53: log.error("AllocateMessageQueueStrategy.allocate Exception. allocateMessageQueueStrategyName={}", strategy.getName(),
54: e);
55: return;
56: }
57:
58: Set<MessageQueue> allocateResultSet = new HashSet<>();
59: if (allocateResult != null) {
60: allocateResultSet.addAll(allocateResult);
61: }
62:
63: // 更新消息队列
64: boolean changed = this.updateProcessQueueTableInRebalance(topic, allocateResultSet, isOrder);
65: if (changed) {
66: log.info(
67: "rebalanced result changed. allocateMessageQueueStrategyName={}, group={}, topic={}, clientId={}, mqAllSize={}, cidAllSize={}, rebalanceResultSize={}, rebalanceResultSet={}",
68: strategy.getName(), consumerGroup, topic, this.mQClientFactory.getClientId(), mqSet.size(), cidAll.size(),
69: allocateResultSet.size(), allocateResultSet);
70: this.messageQueueChanged(topic, mqSet, allocateResultSet);
71: }
72: }
73: break;
74: }
75: default:
76: break;
77: }
78: }
79:
80: /**
81: * 当负载均衡时,更新 消息处理队列
82: * - 移除 在processQueueTable && 不存在于 mqSet 里的消息队列
83: * - 增加 不在processQueueTable && 存在于mqSet 里的消息队列
84: *
85: * @param topic Topic
86: * @param mqSet 负载均衡结果后的消息队列数组
87: * @param isOrder 是否顺序
88: * @return 是否变更
89: */
90: private boolean updateProcessQueueTableInRebalance(final String topic, final Set<MessageQueue> mqSet, final boolean isOrder) {
91: boolean changed = false;
92:
93: // 移除 在processQueueTable && 不存在于 mqSet 里的消息队列
94: Iterator<Entry<MessageQueue, ProcessQueue>> it = this.processQueueTable.entrySet().iterator();
95: while (it.hasNext()) { // TODO 待读:
96: Entry<MessageQueue, ProcessQueue> next = it.next();
97: MessageQueue mq = next.getKey();
98: ProcessQueue pq = next.getValue();
99:
100: if (mq.getTopic().equals(topic)) {
101: if (!mqSet.contains(mq)) { // 不包含的队列
102: pq.setDropped(true);
103: if (this.removeUnnecessaryMessageQueue(mq, pq)) {
104: it.remove();
105: changed = true;
106: log.info("doRebalance, {}, remove unnecessary mq, {}", consumerGroup, mq);
107: }
108: } else if (pq.isPullExpired()) { // 队列拉取超时,进行清理
109: switch (this.consumeType()) {
110: case CONSUME_ACTIVELY:
111: break;
112: case CONSUME_PASSIVELY:
113: pq.setDropped(true);
114: if (this.removeUnnecessaryMessageQueue(mq, pq)) {
115: it.remove();
116: changed = true;
117: log.error("[BUG]doRebalance, {}, remove unnecessary mq, {}, because pull is pause, so try to fixed it",
118: consumerGroup, mq);
119: }
120: break;
121: default:
122: break;
123: }
124: }
125: }
126: }
127:
128: // 增加 不在processQueueTable && 存在于mqSet 里的消息队列。
129: List<PullRequest> pullRequestList = new ArrayList<>(); // 拉消息请求数组
130: for (MessageQueue mq : mqSet) {
131: if (!this.processQueueTable.containsKey(mq)) {
132: if (isOrder && !this.lock(mq)) {
133: log.warn("doRebalance, {}, add a new mq failed, {}, because lock failed", consumerGroup, mq);
134: continue;
135: }
136:
137: this.removeDirtyOffset(mq);
138: ProcessQueue pq = new ProcessQueue();
139: long nextOffset = this.computePullFromWhere(mq);
140: if (nextOffset >= 0) {
141: ProcessQueue pre = this.processQueueTable.putIfAbsent(mq, pq);
142: if (pre != null) {
143: log.info("doRebalance, {}, mq already exists, {}", consumerGroup, mq);
144: } else {
145: log.info("doRebalance, {}, add a new mq, {}", consumerGroup, mq);
146: PullRequest pullRequest = new PullRequest();
147: pullRequest.setConsumerGroup(consumerGroup);
148: pullRequest.setNextOffset(nextOffset);
149: pullRequest.setMessageQueue(mq);
150: pullRequest.setProcessQueue(pq);
151: pullRequestList.add(pullRequest);
152: changed = true;
153: }
154: } else {
155: log.warn("doRebalance, {}, add new mq failed, {}", consumerGroup, mq);
156: }
157: }
158: }
159:
160: // 发起消息拉取请求
161: this.dispatchPullRequest(pullRequestList);
162:
163: return changed;
164: }
  • #rebalanceByTopic(...) 说明 :分配 Topic 的消息队列。
    • 第 3 至 19 行 :广播模式( BROADCASTING ) 下,分配 Topic 对应的所有消息队列。
    • 第 20 至 74 行 :集群模式( CLUSTERING ) 下,分配 Topic 对应的部分消息队列。
      • 第 21 至 40 行 :获取 Topic 对应的消息队列和消费者们,并对其进行排序。因为各 Consumer 是在本地分配消息队列,排序后才能保证各 Consumer 顺序一致。
      • 第 42 至 61 行 :根据 队列分配策略( AllocateMessageQueueStrategy ) 分配消息队列。详细解析见:AllocateMessageQueueStrategy
      • 第 63 至 72 行 :更新 Topic 对应的消息队列。
  • #updateProcessQueueTableInRebalance(...) 说明 :当分配队列时,更新 Topic 对应的消息队列,并返回是否有变更。
    • 第 93 至 126 行 :移除不存在于分配的消息队列( mqSet ) 的 消息处理队列( processQueueTable )。
      • 第 103 行 :移除不需要的消息队列。详细解析见:RebalancePushImpl#removeUnnecessaryMessageQueue(…)
      • 第 108 至 120 行 :队列拉取超时,即 当前时间 - 最后一次拉取消息时间 > 120s ( 120s 可配置),判定发生 BUG,过久未进行消息拉取,移除消息队列。移除后,下面#新增队列逻辑#可以重新加入新的该消息队列。
    • 第 128 至 158 行 :增加 分配的消息队列( mqSet ) 新增的消息队列。
    • 第 161 行 :发起新增的消息队列消息拉取请求。详细解析见:RebalancePushImpl#dispatchPullRequest(…)

RebalanceImpl#removeUnnecessaryMessageQueue(…)

RebalancePushImpl#removeUnnecessaryMessageQueue(…)

1: public boolean removeUnnecessaryMessageQueue(MessageQueue mq, ProcessQueue pq) {
2: // 同步队列的消费进度,并移除之。
3: this.defaultMQPushConsumerImpl.getOffsetStore().persist(mq);
4: this.defaultMQPushConsumerImpl.getOffsetStore().removeOffset(mq);
5: // TODO 顺序消费
6: if (this.defaultMQPushConsumerImpl.isConsumeOrderly()
7: && MessageModel.CLUSTERING.equals(this.defaultMQPushConsumerImpl.messageModel())) {
8: try {
9: if (pq.getLockConsume().tryLock(1000, TimeUnit.MILLISECONDS)) {
10: try {
11: return this.unlockDelay(mq, pq);
12: } finally {
13: pq.getLockConsume().unlock();
14: }
15: } else {
16: log.warn("[WRONG]mq is consuming, so can not unlock it, {}. maybe hanged for a while, {}", //
17: mq, //
18: pq.getTryUnlockTimes());
19:
20: pq.incTryUnlockTimes();
21: }
22: } catch (Exception e) {
23: log.error("removeUnnecessaryMessageQueue Exception", e);
24: }
25:
26: return false;
27: }
28: return true;
29: }

[PullConsumer] RebalancePullImpl#removeUnnecessaryMessageQueue(…)

1: public boolean removeUnnecessaryMessageQueue(MessageQueue mq, ProcessQueue pq) {
2: this.defaultMQPullConsumerImpl.getOffsetStore().persist(mq);
3: this.defaultMQPullConsumerImpl.getOffsetStore().removeOffset(mq);
4: return true;
5: }
  • 说明 :移除不需要的消息队列相关的信息,并返回移除成功。RebalancePushImpl#removeUnnecessaryMessageQueue(...)基本一致。

RebalancePushImpl#dispatchPullRequest(…)

1: public void dispatchPullRequest(List<PullRequest> pullRequestList) {
2: for (PullRequest pullRequest : pullRequestList) {
3: this.defaultMQPushConsumerImpl.executePullRequestImmediately(pullRequest);
4: log.info("doRebalance, {}, add a new pull request {}", consumerGroup, pullRequest);
5: }
6: }
  • 说明 :发起消息拉取请求。该调用是PushConsumer不断不断不断拉取消息的起点

DefaultMQPushConsumerImpl#executePullRequestImmediately(…)

1: public void executePullRequestImmediately(final PullRequest pullRequest) {
2: this.mQClientFactory.getPullMessageService().executePullRequestImmediately(pullRequest);
3: }
  • 说明 :提交拉取请求。提交后,PullMessageService 异步执行非阻塞。详细解析见:PullMessageService

AllocateMessageQueueStrategy

AllocateMessageQueueStrategy类图

AllocateMessageQueueAveragely

1: public class AllocateMessageQueueAveragely implements AllocateMessageQueueStrategy {
2: private final Logger log = ClientLogger.getLog();
3:
4: @Override
5: public List<MessageQueue> allocate(String consumerGroup, String currentCID, List<MessageQueue> mqAll,
6: List<String> cidAll) {
7: // 校验参数是否正确
8: if (currentCID == null || currentCID.length() < 1) {
9: throw new IllegalArgumentException("currentCID is empty");
10: }
11: if (mqAll == null || mqAll.isEmpty()) {
12: throw new IllegalArgumentException("mqAll is null or mqAll empty");
13: }
14: if (cidAll == null || cidAll.isEmpty()) {
15: throw new IllegalArgumentException("cidAll is null or cidAll empty");
16: }
17:
18: List<MessageQueue> result = new ArrayList<>();
19: if (!cidAll.contains(currentCID)) {
20: log.info("[BUG] ConsumerGroup: {} The consumerId: {} not in cidAll: {}",
21: consumerGroup,
22: currentCID,
23: cidAll);
24: return result;
25: }
26: // 平均分配
27: int index = cidAll.indexOf(currentCID); // 第几个consumer。
28: int mod = mqAll.size() % cidAll.size(); // 余数,即多少消息队列无法平均分配。
29: int averageSize =
30: mqAll.size() <= cidAll.size() ? 1 : (mod > 0 && index < mod ? mqAll.size() / cidAll.size()
31: + 1 : mqAll.size() / cidAll.size());
32: int startIndex = (mod > 0 && index < mod) ? index * averageSize : index * averageSize + mod; // 有余数的情况下,[0, mod) 平分余数,即每consumer多分配一个节点;第index开始,跳过前mod余数。
33: int range = Math.min(averageSize, mqAll.size() - startIndex); // 分配队列数量。之所以要Math.min()的原因是,mqAll.size() <= cidAll.size(),部分consumer分配不到消息队列。
34: for (int i = 0; i < range; i++) {
35: result.add(mqAll.get((startIndex + i) % mqAll.size()));
36: }
37: return result;
38: }
39:
40: @Override
41: public String getName() {
42: return "AVG";
43: }
44: }
  • 说明 :平均分配队列策略。
  • 第 7 至 25 行 :参数校验。
  • 第 26 至 36 行 :平均分配消息队列。
    • 第 27 行 :index :当前 Consumer 在消费集群里是第几个。这里就是为什么需要对传入的 cidAll 参数必须进行排序的原因。如果不排序,Consumer 在本地计算出来的 index 无法一致,影响计算结果。
    • 第 28 行 :mod :余数,即多少消息队列无法平均分配。
    • 第 29 至 31 行 :averageSize :代码可以简化成 (mod > 0 && index < mod ? mqAll.size() / cidAll.size() + 1 : mqAll.size() / cidAll.size())
      • [ 0, mod )mqAll.size() / cidAll.size() + 1。前面 modConsumer 平分余数,多获得 1 个消息队列。
      • [ mod, cidAll.size() )mqAll.size() / cidAll.size()
    • 第 32 行 :startIndexConsumer 分配消息队列开始位置。
    • 第 33 行 :range :分配队列数量。之所以要 Math#min(...) 的原因:当 mqAll.size() <= cidAll.size() 时,最后几个 Consumer 分配不到消息队列。
    • 第 34 至 36 行 :生成分配消息队列结果。
  • 举个例子:

固定消息队列长度为4

Consumer 2 可以整除*Consumer 3 不可整除*Consumer 5 无法都分配*
消息队列[0]Consumer[0]Consumer[0]Consumer[0]
消息队列[1]Consumer[0]Consumer[0]Consumer[1]
消息队列[2]Consumer[1]Consumer[1]Consumer[2]
消息队列[3]Consumer[1]Consumer[2]Consumer[3]

AllocateMessageQueueByMachineRoom

1: public class AllocateMessageQueueByMachineRoom implements AllocateMessageQueueStrategy {
2: /**
3: * 消费者消费brokerName集合
4: */
5: private Set<String> consumeridcs;
6:
7: @Override
8: public List<MessageQueue> allocate(String consumerGroup, String currentCID, List<MessageQueue> mqAll,
9: List<String> cidAll) {
10: // 参数校验
11: List<MessageQueue> result = new ArrayList<MessageQueue>();
12: int currentIndex = cidAll.indexOf(currentCID);
13: if (currentIndex < 0) {
14: return result;
15: }
16: // 计算符合当前配置的消费者数组('consumeridcs')对应的消息队列
17: List<MessageQueue> premqAll = new ArrayList<MessageQueue>();
18: for (MessageQueue mq : mqAll) {
19: String[] temp = mq.getBrokerName().split("@");
20: if (temp.length == 2 && consumeridcs.contains(temp[0])) {
21: premqAll.add(mq);
22: }
23: }
24: // 平均分配
25: int mod = premqAll.size() / cidAll.size();
26: int rem = premqAll.size() % cidAll.size();
27: int startIndex = mod * currentIndex;
28: int endIndex = startIndex + mod;
29: for (int i = startIndex; i < endIndex; i++) {
30: result.add(mqAll.get(i));
31: }
32: if (rem > currentIndex) {
33: result.add(premqAll.get(currentIndex + mod * cidAll.size()));
34: }
35: return result;
36: }
37:
38: @Override
39: public String getName() {
40: return "MACHINE_ROOM";
41: }
42:
43: public Set<String> getConsumeridcs() {
44: return consumeridcs;
45: }
46:
47: public void setConsumeridcs(Set<String> consumeridcs) {
48: this.consumeridcs = consumeridcs;
49: }
50: }
  • 说明 :平均分配可消费的 Broker 对应的消息队列。
  • 第 7 至 15 行 :参数校验。
  • 第 16 至 23 行 :计算可消费的 Broker 对应的消息队列。
  • 第 25 至 34 行 :平均分配消息队列。该平均分配方式和 AllocateMessageQueueAveragely 略有不同,其是将多余的结尾部分分配给前 remConsumer
  • 疑问:使用该分配策略时,ConsumerBroker 分配需要怎么配置。😈等研究主从相关源码时,仔细考虑下。

AllocateMessageQueueAveragelyByCircle

1: public class AllocateMessageQueueAveragelyByCircle implements AllocateMessageQueueStrategy {
2: private final Logger log = ClientLogger.getLog();
3:
4: @Override
5: public List<MessageQueue> allocate(String consumerGroup, String currentCID, List<MessageQueue> mqAll,
6: List<String> cidAll) {
7: // 校验参数是否正确
8: if (currentCID == null || currentCID.length() < 1) {
9: throw new IllegalArgumentException("currentCID is empty");
10: }
11: if (mqAll == null || mqAll.isEmpty()) {
12: throw new IllegalArgumentException("mqAll is null or mqAll empty");
13: }
14: if (cidAll == null || cidAll.isEmpty()) {
15: throw new IllegalArgumentException("cidAll is null or cidAll empty");
16: }
17:
18: List<MessageQueue> result = new ArrayList<MessageQueue>();
19: if (!cidAll.contains(currentCID)) {
20: log.info("[BUG] ConsumerGroup: {} The consumerId: {} not in cidAll: {}",
21: consumerGroup,
22: currentCID,
23: cidAll);
24: return result;
25: }
26:
27: // 环状分配
28: int index = cidAll.indexOf(currentCID);
29: for (int i = index; i < mqAll.size(); i++) {
30: if (i % cidAll.size() == index) {
31: result.add(mqAll.get(i));
32: }
33: }
34: return result;
35: }
36:
37: @Override
38: public String getName() {
39: return "AVG_BY_CIRCLE";
40: }
41: }
  • 说明 :环状分配消息队列。

AllocateMessageQueueByConfig

1: public class AllocateMessageQueueByConfig implements AllocateMessageQueueStrategy {
2: private List<MessageQueue> messageQueueList;
3:
4: @Override
5: public List<MessageQueue> allocate(String consumerGroup, String currentCID, List<MessageQueue> mqAll,
6: List<String> cidAll) {
7: return this.messageQueueList;
8: }
9:
10: @Override
11: public String getName() {
12: return "CONFIG";
13: }
14:
15: public List<MessageQueue> getMessageQueueList() {
16: return messageQueueList;
17: }
18:
19: public void setMessageQueueList(List<MessageQueue> messageQueueList) {
20: this.messageQueueList = messageQueueList;
21: }
22: }
  • 说明 :分配配置的消息队列。
  • 疑问 :该分配策略的使用场景。

5、PushConsumer 消费进度读取

RebalancePushImpl#computePullFromWhere(…)

1: public long computePullFromWhere(MessageQueue mq) {
2: long result = -1;
3: final ConsumeFromWhere consumeFromWhere = this.defaultMQPushConsumerImpl.getDefaultMQPushConsumer().getConsumeFromWhere();
4: final OffsetStore offsetStore = this.defaultMQPushConsumerImpl.getOffsetStore();
5: switch (consumeFromWhere) {
6: case CONSUME_FROM_LAST_OFFSET_AND_FROM_MIN_WHEN_BOOT_FIRST: // 废弃
7: case CONSUME_FROM_MIN_OFFSET: // 废弃
8: case CONSUME_FROM_MAX_OFFSET: // 废弃
9: case CONSUME_FROM_LAST_OFFSET: {
10: long lastOffset = offsetStore.readOffset(mq, ReadOffsetType.READ_FROM_STORE);
11: if (lastOffset >= 0) {
12: result = lastOffset;
13: }
14: // First start,no offset
15: else if (-1 == lastOffset) {
16: if (mq.getTopic().startsWith(MixAll.RETRY_GROUP_TOPIC_PREFIX)) {
17: result = 0L;
18: } else {
19: try {
20: result = this.mQClientFactory.getMQAdminImpl().maxOffset(mq);
21: } catch (MQClientException e) {
22: result = -1;
23: }
24: }
25: } else {
26: result = -1;
27: }
28: break;
29: }
30: case CONSUME_FROM_FIRST_OFFSET: {
31: long lastOffset = offsetStore.readOffset(mq, ReadOffsetType.READ_FROM_STORE);
32: if (lastOffset >= 0) {
33: result = lastOffset;
34: } else if (-1 == lastOffset) {
35: result = 0L;
36: } else {
37: result = -1;
38: }
39: break;
40: }
41: case CONSUME_FROM_TIMESTAMP: {
42: long lastOffset = offsetStore.readOffset(mq, ReadOffsetType.READ_FROM_STORE);
43: if (lastOffset >= 0) {
44: result = lastOffset;
45: } else if (-1 == lastOffset) {
46: if (mq.getTopic().startsWith(MixAll.RETRY_GROUP_TOPIC_PREFIX)) {
47: try {
48: result = this.mQClientFactory.getMQAdminImpl().maxOffset(mq);
49: } catch (MQClientException e) {
50: result = -1;
51: }
52: } else {
53: try {
54: long timestamp = UtilAll.parseDate(this.defaultMQPushConsumerImpl.getDefaultMQPushConsumer().getConsumeTimestamp(),
55: UtilAll.YYYY_MMDD_HHMMSS).getTime();
56: result = this.mQClientFactory.getMQAdminImpl().searchOffset(mq, timestamp);
57: } catch (MQClientException e) {
58: result = -1;
59: }
60: }
61: } else {
62: result = -1;
63: }
64: break;
65: }
66:
67: default:
68: break;
69: }
70:
71: return result;
72: }
  • 说明 :计算消息队列开始消费位置。
  • PushConsumer 读取消费进度有三种选项:
    • CONSUME_FROM_LAST_OFFSET :第 6 至 29 行 :一个新的消费集群第一次启动从队列的最后位置开始消费。后续再启动接着上次消费的进度开始消费
    • CONSUME_FROM_FIRST_OFFSET :第 30 至 40 行 :一个新的消费集群第一次启动从队列的最前位置开始消费。后续再启动接着上次消费的进度开始消费
    • CONSUME_FROM_TIMESTAMP :第 41 至 65 行 :一个新的消费集群第一次启动从指定时间点开始消费。后续再启动接着上次消费的进度开始消费

[PullConsumer] RebalancePullImpl#computePullFromWhere(…)

暂时跳过。😈

6、PushConsumer 拉取消息

DefaultMQPushConsumerImpl拉取消息

PullMessageService

1: public class PullMessageService extends ServiceThread {
2: private final Logger log = ClientLogger.getLog();
3: /**
4: * 拉取消息请求队列
5: */
6: private final LinkedBlockingQueue<PullRequest> pullRequestQueue = new LinkedBlockingQueue<>();
7: /**
8: * MQClient对象
9: */
10: private final MQClientInstance mQClientFactory;
11: /**
12: * 定时器。用于延迟提交拉取请求
13: */
14: private final ScheduledExecutorService scheduledExecutorService = Executors
15: .newSingleThreadScheduledExecutor(new ThreadFactory() {
16: @Override
17: public Thread newThread(Runnable r) {
18: return new Thread(r, "PullMessageServiceScheduledThread");
19: }
20: });
21:
22: public PullMessageService(MQClientInstance mQClientFactory) {
23: this.mQClientFactory = mQClientFactory;
24: }
25:
26: /**
27: * 执行延迟拉取消息请求
28: *
29: * @param pullRequest 拉取消息请求
30: * @param timeDelay 延迟时长
31: */
32: public void executePullRequestLater(final PullRequest pullRequest, final long timeDelay) {
33: this.scheduledExecutorService.schedule(new Runnable() {
34:
35: @Override
36: public void run() {
37: PullMessageService.this.executePullRequestImmediately(pullRequest);
38: }
39: }, timeDelay, TimeUnit.MILLISECONDS);
40: }
41:
42: /**
43: * 执行立即拉取消息请求
44: *
45: * @param pullRequest 拉取消息请求
46: */
47: public void executePullRequestImmediately(final PullRequest pullRequest) {
48: try {
49: this.pullRequestQueue.put(pullRequest);
50: } catch (InterruptedException e) {
51: log.error("executePullRequestImmediately pullRequestQueue.put", e);
52: }
53: }
54:
55: /**
56: * 执行延迟任务
57: *
58: * @param r 任务
59: * @param timeDelay 延迟时长
60: */
61: public void executeTaskLater(final Runnable r, final long timeDelay) {
62: this.scheduledExecutorService.schedule(r, timeDelay, TimeUnit.MILLISECONDS);
63: }
64:
65: public ScheduledExecutorService getScheduledExecutorService() {
66: return scheduledExecutorService;
67: }
68:
69: /**
70: * 拉取消息
71: *
72: * @param pullRequest 拉取消息请求
73: */
74: private void pullMessage(final PullRequest pullRequest) {
75: final MQConsumerInner consumer = this.mQClientFactory.selectConsumer(pullRequest.getConsumerGroup());
76: if (consumer != null) {
77: DefaultMQPushConsumerImpl impl = (DefaultMQPushConsumerImpl) consumer;
78: impl.pullMessage(pullRequest);
79: } else {
80: log.warn("No matched consumer for the PullRequest {}, drop it", pullRequest);
81: }
82: }
83:
84: @Override
85: public void run() {
86: log.info(this.getServiceName() + " service started");
87:
88: while (!this.isStopped()) {
89: try {
90: PullRequest pullRequest = this.pullRequestQueue.take();
91: if (pullRequest != null) {
92: this.pullMessage(pullRequest);
93: }
94: } catch (InterruptedException e) {
95: } catch (Exception e) {
96: log.error("Pull Message Service Run Method exception", e);
97: }
98: }
99:
100: log.info(this.getServiceName() + " service end");
101: }
102:
103: @Override
104: public String getServiceName() {
105: return PullMessageService.class.getSimpleName();
106: }
107:
108: }
  • 说明 :拉取消息服务,不断不断不断从 Broker 拉取消息,并提交消费任务到 ConsumeMessageService
  • #executePullRequestLater(...) :第 26 至 40 行 : 提交延迟拉取消息请求。
  • #executePullRequestImmediately(...) :第 42 至 53 行 :提交立即拉取消息请求。
  • #executeTaskLater(...) :第 55 至 63 行 :提交延迟任务
  • #pullMessage(...) :第 69 至 82 行 :执行拉取消息逻辑。详细解析见:DefaultMQPushConsumerImpl#pullMessage(…)
  • #run(...) :第 84 至 101 行 :循环拉取消息请求队列( pullRequestQueue ),进行消息拉取。

DefaultMQPushConsumerImpl#pullMessage(…)

1: public void pullMessage(final PullRequest pullRequest) {
2: final ProcessQueue processQueue = pullRequest.getProcessQueue();
3: if (processQueue.isDropped()) {
4: log.info("the pull request[{}] is dropped.", pullRequest.toString());
5: return;
6: }
7:
8: // 设置队列最后拉取消息时间
9: pullRequest.getProcessQueue().setLastPullTimestamp(System.currentTimeMillis());
10:
11: // 判断consumer状态是否运行中。如果不是,则延迟拉取消息。
12: try {
13: this.makeSureStateOK();
14: } catch (MQClientException e) {
15: log.warn("pullMessage exception, consumer state not ok", e);
16: this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_EXCEPTION);
17: return;
18: }
19:
20: // 判断是否暂停中。
21: if (this.isPause()) {
22: log.warn("consumer was paused, execute pull request later. instanceName={}, group={}", this.defaultMQPushConsumer.getInstanceName(), this.defaultMQPushConsumer.getConsumerGroup());
23: this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_SUSPEND);
24: return;
25: }
26:
27: // 判断是否超过最大持有消息数量。默认最大值为1000。
28: long size = processQueue.getMsgCount().get();
29: if (size > this.defaultMQPushConsumer.getPullThresholdForQueue()) {
30: this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_FLOW_CONTROL); // 提交延迟消息拉取请求。50ms。
31: if ((flowControlTimes1++ % 1000) == 0) {
32: log.warn(
33: "the consumer message buffer is full, so do flow control, minOffset={}, maxOffset={}, size={}, pullRequest={}, flowControlTimes={}",
34: processQueue.getMsgTreeMap().firstKey(), processQueue.getMsgTreeMap().lastKey(), size, pullRequest, flowControlTimes1);
35: }
36: return;
37: }
38:
39: if (!this.consumeOrderly) { // 判断消息跨度是否过大。
40: if (processQueue.getMaxSpan() > this.defaultMQPushConsumer.getConsumeConcurrentlyMaxSpan()) {
41: this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_FLOW_CONTROL); // 提交延迟消息拉取请求。50ms。
42: if ((flowControlTimes2++ % 1000) == 0) {
43: log.warn(
44: "the queue's messages, span too long, so do flow control, minOffset={}, maxOffset={}, maxSpan={}, pullRequest={}, flowControlTimes={}",
45: processQueue.getMsgTreeMap().firstKey(), processQueue.getMsgTreeMap().lastKey(), processQueue.getMaxSpan(),
46: pullRequest, flowControlTimes2);
47: }
48: return;
49: }
50: } else { // TODO 顺序消费
51: if (processQueue.isLocked()) {
52: if (!pullRequest.isLockedFirst()) {
53: final long offset = this.rebalanceImpl.computePullFromWhere(pullRequest.getMessageQueue());
54: boolean brokerBusy = offset < pullRequest.getNextOffset();
55: log.info("the first time to pull message, so fix offset from broker. pullRequest: {} NewOffset: {} brokerBusy: {}",
56: pullRequest, offset, brokerBusy);
57: if (brokerBusy) {
58: log.info("[NOTIFYME]the first time to pull message, but pull request offset larger than broker consume offset. pullRequest: {} NewOffset: {}",
59: pullRequest, offset);
60: }
61:
62: pullRequest.setLockedFirst(true);
63: pullRequest.setNextOffset(offset);
64: }
65: } else {
66: this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_EXCEPTION);
67: log.info("pull message later because not locked in broker, {}", pullRequest);
68: return;
69: }
70: }
71:
72: // 获取Topic 对应的订阅信息。若不存在,则延迟拉取消息
73: final SubscriptionData subscriptionData = this.rebalanceImpl.getSubscriptionInner().get(pullRequest.getMessageQueue().getTopic());
74: if (null == subscriptionData) {
75: this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_EXCEPTION);
76: log.warn("find the consumer's subscription failed, {}", pullRequest);
77: return;
78: }
79:
80: final long beginTimestamp = System.currentTimeMillis();
81:
82: PullCallback pullCallback = new PullCallback() {
83: @Override
84: public void onSuccess(PullResult pullResult) {
85: if (pullResult != null) {
86: pullResult = DefaultMQPushConsumerImpl.this.pullAPIWrapper.processPullResult(pullRequest.getMessageQueue(), pullResult,
87: subscriptionData);
88:
89: switch (pullResult.getPullStatus()) {
90: case FOUND:
91: // 设置下次拉取消息队列位置
92: long prevRequestOffset = pullRequest.getNextOffset();
93: pullRequest.setNextOffset(pullResult.getNextBeginOffset());
94:
95: // 统计
96: long pullRT = System.currentTimeMillis() - beginTimestamp;
97: DefaultMQPushConsumerImpl.this.getConsumerStatsManager().incPullRT(pullRequest.getConsumerGroup(),
98: pullRequest.getMessageQueue().getTopic(), pullRT);
99:
100: long firstMsgOffset = Long.MAX_VALUE;
101: if (pullResult.getMsgFoundList() == null || pullResult.getMsgFoundList().isEmpty()) {
102: DefaultMQPushConsumerImpl.this.executePullRequestImmediately(pullRequest);
103: } else {
104: firstMsgOffset = pullResult.getMsgFoundList().get(0).getQueueOffset();
105:
106: // 统计
107: DefaultMQPushConsumerImpl.this.getConsumerStatsManager().incPullTPS(pullRequest.getConsumerGroup(),
108: pullRequest.getMessageQueue().getTopic(), pullResult.getMsgFoundList().size());
109:
110: // 提交拉取到的消息到消息处理队列
111: boolean dispathToConsume = processQueue.putMessage(pullResult.getMsgFoundList());
112:
113: // 提交消费请求
114: DefaultMQPushConsumerImpl.this.consumeMessageService.submitConsumeRequest(//
115: pullResult.getMsgFoundList(), //
116: processQueue, //
117: pullRequest.getMessageQueue(), //
118: dispathToConsume);
119:
120: // 提交下次拉取消息请求
121: if (DefaultMQPushConsumerImpl.this.defaultMQPushConsumer.getPullInterval() > 0) {
122: DefaultMQPushConsumerImpl.this.executePullRequestLater(pullRequest,
123: DefaultMQPushConsumerImpl.this.defaultMQPushConsumer.getPullInterval());
124: } else {
125: DefaultMQPushConsumerImpl.this.executePullRequestImmediately(pullRequest);
126: }
127: }
128:
129: // 下次拉取消息队列位置小于上次拉取消息队列位置 或者 第一条消息的消息队列位置小于上次拉取消息队列位置,则判定为BUG,输出log
130: if (pullResult.getNextBeginOffset() < prevRequestOffset//
131: || firstMsgOffset < prevRequestOffset) {
132: log.warn(
133: "[BUG] pull message result maybe data wrong, nextBeginOffset: {} firstMsgOffset: {} prevRequestOffset: {}", //
134: pullResult.getNextBeginOffset(), //
135: firstMsgOffset, //
136: prevRequestOffset);
137: }
138:
139: break;
140: case NO_NEW_MSG:
141: // 设置下次拉取消息队列位置
142: pullRequest.setNextOffset(pullResult.getNextBeginOffset());
143:
144: // 持久化消费进度
145: DefaultMQPushConsumerImpl.this.correctTagsOffset(pullRequest);
146:
147: // 立即提交拉取消息请求
148: DefaultMQPushConsumerImpl.this.executePullRequestImmediately(pullRequest);
149: break;
150: case NO_MATCHED_MSG:
151: // 设置下次拉取消息队列位置
152: pullRequest.setNextOffset(pullResult.getNextBeginOffset());
153:
154: // 持久化消费进度
155: DefaultMQPushConsumerImpl.this.correctTagsOffset(pullRequest);
156:
157: // 提交立即拉取消息请求
158: DefaultMQPushConsumerImpl.this.executePullRequestImmediately(pullRequest);
159: break;
160: case OFFSET_ILLEGAL:
161: log.warn("the pull request offset illegal, {} {}", //
162: pullRequest.toString(), pullResult.toString());
163: // 设置下次拉取消息队列位置
164: pullRequest.setNextOffset(pullResult.getNextBeginOffset());
165:
166: // 设置消息处理队列为dropped
167: pullRequest.getProcessQueue().setDropped(true);
168:
169: // 提交延迟任务,进行消费处理队列移除。不立即移除的原因:可能有地方正在使用,避免受到影响。
170: DefaultMQPushConsumerImpl.this.executeTaskLater(new Runnable() {
171:
172: @Override
173: public void run() {
174: try {
175: // 更新消费进度,同步消费进度到Broker
176: DefaultMQPushConsumerImpl.this.offsetStore.updateOffset(pullRequest.getMessageQueue(),
177: pullRequest.getNextOffset(), false);
178: DefaultMQPushConsumerImpl.this.offsetStore.persist(pullRequest.getMessageQueue());
179:
180: // 移除消费处理队列
181: DefaultMQPushConsumerImpl.this.rebalanceImpl.removeProcessQueue(pullRequest.getMessageQueue());
182:
183: log.warn("fix the pull request offset, {}", pullRequest);
184: } catch (Throwable e) {
185: log.error("executeTaskLater Exception", e);
186: }
187: }
188: }, 10000);
189: break;
190: default:
191: break;
192: }
193: }
194: }
195:
196: @Override
197: public void onException(Throwable e) {
198: if (!pullRequest.getMessageQueue().getTopic().startsWith(MixAll.RETRY_GROUP_TOPIC_PREFIX)) {
199: log.warn("execute the pull request exception", e);
200: }
201:
202: // 提交延迟拉取消息请求
203: DefaultMQPushConsumerImpl.this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_EXCEPTION);
204: }
205: };
206:
207: // 集群消息模型下,计算提交的消费进度。
208: boolean commitOffsetEnable = false;
209: long commitOffsetValue = 0L;
210: if (MessageModel.CLUSTERING == this.defaultMQPushConsumer.getMessageModel()) {
211: commitOffsetValue = this.offsetStore.readOffset(pullRequest.getMessageQueue(), ReadOffsetType.READ_FROM_MEMORY);
212: if (commitOffsetValue > 0) {
213: commitOffsetEnable = true;
214: }
215: }
216:
217: // 计算请求的 订阅表达式 和 是否进行filtersrv过滤消息
218: String subExpression = null;
219: boolean classFilter = false;
220: SubscriptionData sd = this.rebalanceImpl.getSubscriptionInner().get(pullRequest.getMessageQueue().getTopic());
221: if (sd != null) {
222: if (this.defaultMQPushConsumer.isPostSubscriptionWhenPull() && !sd.isClassFilterMode()) {
223: subExpression = sd.getSubString();
224: }
225:
226: classFilter = sd.isClassFilterMode();
227: }
228:
229: // 计算拉取消息系统标识
230: int sysFlag = PullSysFlag.buildSysFlag(//
231: commitOffsetEnable, // commitOffset
232: true, // suspend
233: subExpression != null, // subscription
234: classFilter // class filter
235: );
236:
237: // 执行拉取。如果拉取请求发生异常时,提交延迟拉取消息请求。
238: try {
239: this.pullAPIWrapper.pullKernelImpl(//
240: pullRequest.getMessageQueue(), // 1
241: subExpression, // 2
242: subscriptionData.getSubVersion(), // 3
243: pullRequest.getNextOffset(), // 4
244: this.defaultMQPushConsumer.getPullBatchSize(), // 5
245: sysFlag, // 6
246: commitOffsetValue, // 7
247: BROKER_SUSPEND_MAX_TIME_MILLIS, // 8
248: CONSUMER_TIMEOUT_MILLIS_WHEN_SUSPEND, // 9
249: CommunicationMode.ASYNC, // 10
250: pullCallback// 11
251: );
252: } catch (Exception e) {
253: log.error("pullKernelImpl exception", e);
254: this.executePullRequestLater(pullRequest, PULL_TIME_DELAY_MILLS_WHEN_EXCEPTION);
255: }
256: }
257:
258: private void correctTagsOffset(final PullRequest pullRequest) {
259: if (0L == pullRequest.getProcessQueue().getMsgCount().get()) {
260: this.offsetStore.updateOffset(pullRequest.getMessageQueue(), pullRequest.getNextOffset(), true);
261: }
262: }
  • #pullMessage(...) 说明 :拉取消息。
    • 第 3 至 6 行 :消息处理队列已经终止,不进行消息拉取。
    • 第 9 行 :设置消息处理队列最后拉取消息时间。
    • 第 11 至 18 行 :Consumer 未处于运行中状态,不进行消息拉取,提交延迟拉取消息请求。
    • 第 20 至 25 行 : Consumer 处于暂停中,不进行消息拉取,提交延迟拉取消息请求。
    • 第 27 至 37 行 :消息处理队列持有消息超过最大允许值(默认:1000条),不进行消息拉取,提交延迟拉取消息请求。
    • 第 39 至 49 行 :Consumer并发消费 并且 消息队列持有消息跨度过大(消息跨度 = 持有消息最后一条和第一条的消息位置差,默认:2000),不进行消息拉取,提交延迟拉取消息请求。
    • 第 50 至 70 行 :顺序消费 相关跳过,详细解析见:《RocketMQ 源码分析 —— Message 顺序发送与消费》
    • 第 72 至 78 行 :Topic 对应的订阅信息不存在,不进行消息拉取,提交延迟拉取消息请求。
    • 第 222 至 224 行 :判断请求是否使用 Consumer 本地的订阅信息( SubscriptionData ),而不使用 Broker 里的订阅信息。详细解析见:PullMessageProcessor#processRequest(…) 第 64 至 110 行代码
    • 第 226 行 :是否开启过滤类过滤模式。详细解析见:《RocketMQ 源码分析 —— Filtersrv》
    • 第 229 至 235 行 :计算拉取消息请求系统标识。详细解析见:PullMessageRequestHeader.sysFlag
    • 第 237 至 255 行 :
  • PullCallback :拉取消息回调:
    • 第 86 行 :处理拉取结果。详细逻辑见:PullAPIWrapper#processPullResult(…)
    • 第 89 至 192 行 :处理拉取状态结果:
      • 第 90 至 139 行 :拉取到消息( FOUND ) :
        • 第 91 至 93 行 :设置下次拉取消息队列位置。
        • 第 95 至 97 行 :统计。
        • 第 101 至 102 行 :拉取到消息的消息列表为空,提交立即拉取消息请求。为什么会存在拉取到消息,但是消息结果未空呢?原因见:PullAPIWrapper#processPullResult(…)
        • 第 106 至 108 行 :统计。
        • 第 111 行 :提交拉取到的消息到消息处理队列。详细解析见:ProcessQueue#putMessage(…)
        • 第 113 至 118 行 :提交消费请求到 ConsumeMessageService。详细解析见:ConsumeMessageConcurrentlyService
        • 第 120 至 126 行 :根据拉取频率( pullInterval ),提交立即或者延迟拉取消息请求。默认拉取频率为 0ms ,提交立即拉取消息请求。
        • 第 129 至 137 行 :下次拉取消息队列位置小于上次拉取消息队列位置 或者 第一条消息的消息队列位置小于上次拉取消息队列位置,则判定为BUG,输出警告日志。
          • 第 140 至 149 行 :没有新消息( NO_NEW_MSG ) :
        • 第 142 行 : 设置下次拉取消息队列位置。
        • 第 145 行 :更正消费进度。详细解析见:#correctTagsOffset(...)
        • 第 148 行 :提交立即拉取消息请求。
          • 第 150 至 159 行 :有新消息但是不匹配( NO_MATCHED_MSG )。逻辑同 NO_NEW_MSG
          • 第 160 至 189 行 :拉取请求的消息队列位置不合法 (OFFSET_ILLEGAL)。
        • 第 164 行 :设置下次拉取消息队列位置。
        • 第 167 行 :设置消息处理队列为 dropped
        • 第 169 至 188 行 :提交延迟任务,进行队列移除。
          • 第 175 至 178 行 :更新消费进度,同步消费进度到 Broker
          • 第 181 行 :移除消费处理队列。
            • 疑问:为什么不立即移除???
              • 第 196 至 204 行 :发生异常,提交延迟拉取消息请求。
  • #correctTagsOffset(...) :更正消费进度。
    • 第 258 至 261 行 : 当消费处理队列持有消息数量为 0 时,更新消费进度为拉取请求的拉取消息队列位置。

PullAPIWrapper#pullKernelImpl(…)

1: /**
2: * 拉取消息核心方法
3: *
4: * @param mq 消息队列
5: * @param subExpression 订阅表达式
6: * @param subVersion 订阅版本号
7: * @param offset 拉取队列开始位置
8: * @param maxNums 拉取消息数量
9: * @param sysFlag 拉取请求系统标识
10: * @param commitOffset 提交消费进度
11: * @param brokerSuspendMaxTimeMillis broker挂起请求最大时间
12: * @param timeoutMillis 请求broker超时时长
13: * @param communicationMode 通讯模式
14: * @param pullCallback 拉取回调
15: * @return 拉取消息结果。只有通讯模式为同步时,才返回结果,否则返回null。
16: * @throws MQClientException 当寻找不到 broker 时,或发生其他client异常
17: * @throws RemotingException 当远程调用发生异常时
18: * @throws MQBrokerException 当 broker 发生异常时。只有通讯模式为同步时才会发生该异常。
19: * @throws InterruptedException 当发生中断异常时
20: */
21: protected PullResult pullKernelImpl(
22: final MessageQueue mq,
23: final String subExpression,
24: final long subVersion,
25: final long offset,
26: final int maxNums,
27: final int sysFlag,
28: final long commitOffset,
29: final long brokerSuspendMaxTimeMillis,
30: final long timeoutMillis,
31: final CommunicationMode communicationMode,
32: final PullCallback pullCallback
33: ) throws MQClientException, RemotingException, MQBrokerException, InterruptedException {
34: // 获取Broker信息
35: FindBrokerResult findBrokerResult =
36: this.mQClientFactory.findBrokerAddressInSubscribe(mq.getBrokerName(),
37: this.recalculatePullFromWhichNode(mq), false);
38: if (null == findBrokerResult) {
39: this.mQClientFactory.updateTopicRouteInfoFromNameServer(mq.getTopic());
40: findBrokerResult =
41: this.mQClientFactory.findBrokerAddressInSubscribe(mq.getBrokerName(),
42: this.recalculatePullFromWhichNode(mq), false);
43: }
44:
45: // 请求拉取消息
46: if (findBrokerResult != null) {
47: int sysFlagInner = sysFlag;
48:
49: if (findBrokerResult.isSlave()) {
50: sysFlagInner = PullSysFlag.clearCommitOffsetFlag(sysFlagInner);
51: }
52:
53: PullMessageRequestHeader requestHeader = new PullMessageRequestHeader();
54: requestHeader.setConsumerGroup(this.consumerGroup);
55: requestHeader.setTopic(mq.getTopic());
56: requestHeader.setQueueId(mq.getQueueId());
57: requestHeader.setQueueOffset(offset);
58: requestHeader.setMaxMsgNums(maxNums);
59: requestHeader.setSysFlag(sysFlagInner);
60: requestHeader.setCommitOffset(commitOffset);
61: requestHeader.setSuspendTimeoutMillis(brokerSuspendMaxTimeMillis);
62: requestHeader.setSubscription(subExpression);
63: requestHeader.setSubVersion(subVersion);
64:
65: String brokerAddr = findBrokerResult.getBrokerAddr();
66: if (PullSysFlag.hasClassFilterFlag(sysFlagInner)) { // TODO filtersrv
67: brokerAddr = computPullFromWhichFilterServer(mq.getTopic(), brokerAddr);
68: }
69:
70: PullResult pullResult = this.mQClientFactory.getMQClientAPIImpl().pullMessage(
71: brokerAddr,
72: requestHeader,
73: timeoutMillis,
74: communicationMode,
75: pullCallback);
76:
77: return pullResult;
78: }
79:
80: // Broker信息不存在,则抛出异常
81: throw new MQClientException("The broker[" + mq.getBrokerName() + "] not exist", null);
82: }

PullAPIWrapper#recalculatePullFromWhichNode(…)

1: /**
2: * 消息队列 与 拉取Broker 的映射
3: * 当拉取消息时,会通过该映射获取拉取请求对应的Broker
4: */
5: private ConcurrentHashMap<MessageQueue, AtomicLong/* brokerId */> pullFromWhichNodeTable =
6: new ConcurrentHashMap<MessageQueue, AtomicLong>(32);
7: /**
8: * 是否使用默认Broker
9: */
10: private volatile boolean connectBrokerByUser = false;
11: /**
12: * 默认Broker编号
13: */
14: private volatile long defaultBrokerId = MixAll.MASTER_ID;
15:
16: /**
17: * 计算消息队列拉取消息对应的Broker编号
18: *
19: * @param mq 消息队列
20: * @return Broker编号
21: */
22: public long recalculatePullFromWhichNode(final MessageQueue mq) {
23: // 若开启默认Broker开关,则返回默认Broker编号
24: if (this.isConnectBrokerByUser()) {
25: return this.defaultBrokerId;
26: }
27:
28: // 若消息队列映射拉取Broker存在,则返回映射Broker编号
29: AtomicLong suggest = this.pullFromWhichNodeTable.get(mq);
30: if (suggest != null) {
31: return suggest.get();
32: }
33:
34: // 返回Broker主节点编号
35: return MixAll.MASTER_ID;
36: }
  • 说明 :计算消息队列拉取消息对应的 Broker 编号。

MQClientInstance#findBrokerAddressInSubscribe(…)

1: /**
2: * Broker名字 和 Broker地址相关 Map
3: */
4: private final ConcurrentHashMap<String/* Broker Name */, HashMap<Long/* brokerId */, String/* address */>> brokerAddrTable =
5: new ConcurrentHashMap<>();
6:
7: /**
8: * 获得Broker信息
9: *
10: * @param brokerName broker名字
11: * @param brokerId broker编号
12: * @param onlyThisBroker 是否必须是该broker
13: * @return Broker信息
14: */
15: public FindBrokerResult findBrokerAddressInSubscribe(//
16: final String brokerName, //
17: final long brokerId, //
18: final boolean onlyThisBroker//
19: ) {
20: String brokerAddr = null; // broker地址
21: boolean slave = false; // 是否为从节点
22: boolean found = false; // 是否找到
23:
24: // 获得Broker信息
25: HashMap<Long/* brokerId */, String/* address */> map = this.brokerAddrTable.get(brokerName);
26: if (map != null && !map.isEmpty()) {
27: brokerAddr = map.get(brokerId);
28: slave = brokerId != MixAll.MASTER_ID;
29: found = brokerAddr != null;
30:
31: // 如果不强制获得,选择一个Broker
32: if (!found && !onlyThisBroker) {
33: Entry<Long, String> entry = map.entrySet().iterator().next();
34: brokerAddr = entry.getValue();
35: slave = entry.getKey() != MixAll.MASTER_ID;
36: found = true;
37: }
38: }
39:
40: // 找到broker,则返回信息
41: if (found) {
42: return new FindBrokerResult(brokerAddr, slave);
43: }
44:
45: // 找不到,则返回空
46: return null;
47: }
  • 说明 :获取 Broker 信息(Broker 地址、是否为从节点)。

PullAPIWrapper#processPullResult(…)

1: /**
2: * 处理拉取结果
3: * 1. 更新消息队列拉取消息Broker编号的映射
4: * 2. 解析消息,并根据订阅信息消息tagCode匹配合适消息
5: *
6: * @param mq 消息队列
7: * @param pullResult 拉取结果
8: * @param subscriptionData 订阅信息
9: * @return 拉取结果
10: */
11: public PullResult processPullResult(final MessageQueue mq, final PullResult pullResult,
12: final SubscriptionData subscriptionData) {
13: PullResultExt pullResultExt = (PullResultExt) pullResult;
14:
15: // 更新消息队列拉取消息Broker编号的映射
16: this.updatePullFromWhichNode(mq, pullResultExt.getSuggestWhichBrokerId());
17:
18: // 解析消息,并根据订阅信息消息tagCode匹配合适消息
19: if (PullStatus.FOUND == pullResult.getPullStatus()) {
20: // 解析消息
21: ByteBuffer byteBuffer = ByteBuffer.wrap(pullResultExt.getMessageBinary());
22: List<MessageExt> msgList = MessageDecoder.decodes(byteBuffer);
23:
24: // 根据订阅信息消息tagCode匹配合适消息
25: List<MessageExt> msgListFilterAgain = msgList;
26: if (!subscriptionData.getTagsSet().isEmpty() && !subscriptionData.isClassFilterMode()) {
27: msgListFilterAgain = new ArrayList<>(msgList.size());
28: for (MessageExt msg : msgList) {
29: if (msg.getTags() != null) {
30: if (subscriptionData.getTagsSet().contains(msg.getTags())) {
31: msgListFilterAgain.add(msg);
32: }
33: }
34: }
35: }
36:
37: // Hook
38: if (this.hasHook()) {
39: FilterMessageContext filterMessageContext = new FilterMessageContext();
40: filterMessageContext.setUnitMode(unitMode);
41: filterMessageContext.setMsgList(msgListFilterAgain);
42: this.executeHook(filterMessageContext);
43: }
44:
45: // 设置消息队列当前最小/最大位置到消息拓展字段
46: for (MessageExt msg : msgListFilterAgain) {
47: MessageAccessor.putProperty(msg, MessageConst.PROPERTY_MIN_OFFSET,
48: Long.toString(pullResult.getMinOffset()));
49: MessageAccessor.putProperty(msg, MessageConst.PROPERTY_MAX_OFFSET,
50: Long.toString(pullResult.getMaxOffset()));
51: }
52:
53: // 设置消息列表
54: pullResultExt.setMsgFoundList(msgListFilterAgain);
55: }
56:
57: // 清空消息二进制数组
58: pullResultExt.setMessageBinary(null);
59:
60: return pullResult;
61: }
  • 说明 :处理拉取结果。
    • 更新消息队列拉取消息 Broker 编号的映射。
    • 解析消息,并根据订阅信息消息 tagCode匹配合适消息。
  • 第 16 行 :更新消息队列拉取消息 Broker 编号的映射。下次拉取消息时,如果未设置默认拉取的 Broker 编号,会使用更新后的 Broker 编号。
  • 第 18 至 55 行 :解析消息,并根据订阅信息消息 tagCode 匹配合适消息。
    • 第 20 至 22 行 :解析消息。详细解析见:《RocketMQ 源码分析 —— Message基础》
    • 第 24 至 35 行 :根据订阅信息tagCode 匹配消息。
    • 第 37 至 43 行 :Hook
    • 第 45 至 51 行 :设置消息队列当前最小/最大位置到消息拓展字段。
    • 第 54 行 :设置消息队列。
  • 第 58 行 :清空消息二进制数组。

ProcessQueue#putMessage(…)

1: /**
2: * 消息映射读写锁
3: */
4: private final ReadWriteLock lockTreeMap = new ReentrantReadWriteLock();
5: /**
6: * 消息映射
7: * key:消息队列位置
8: */
9: private final TreeMap<Long, MessageExt> msgTreeMap = new TreeMap<>();
10: /**
11: * 消息数
12: */
13: private final AtomicLong msgCount = new AtomicLong();
14: /**
15: * 添加消息最大队列位置
16: */
17: private volatile long queueOffsetMax = 0L;
18: /**
19: * 是否正在消费
20: */
21: private volatile boolean consuming = false;
22: /**
23: * Broker累计消息数量
24: * 计算公式 = queueMaxOffset - 新添加消息数组[n - 1].queueOffset
25: * Acc = Accumulation
26: * cnt = (猜测)对比度
27: */
28: private volatile long msgAccCnt = 0;
29:
30: /**
31: * 添加消息,并返回是否提交给消费者
32: * 返回true,当有新消息添加成功时,
33: *
34: * @param msgs 消息
35: * @return 是否提交给消费者
36: */
37: public boolean putMessage(final List<MessageExt> msgs) {
38: boolean dispatchToConsume = false;
39: try {
40: this.lockTreeMap.writeLock().lockInterruptibly();
41: try {
42: // 添加消息
43: int validMsgCnt = 0;
44: for (MessageExt msg : msgs) {
45: MessageExt old = msgTreeMap.put(msg.getQueueOffset(), msg);
46: if (null == old) {
47: validMsgCnt++;
48: this.queueOffsetMax = msg.getQueueOffset();
49: }
50: }
51: msgCount.addAndGet(validMsgCnt);
52:
53: // 计算是否正在消费
54: if (!msgTreeMap.isEmpty() && !this.consuming) {
55: dispatchToConsume = true;
56: this.consuming = true;
57: }
58:
59: // Broker累计消息数量
60: if (!msgs.isEmpty()) {
61: MessageExt messageExt = msgs.get(msgs.size() - 1);
62: String property = messageExt.getProperty(MessageConst.PROPERTY_MAX_OFFSET);
63: if (property != null) {
64: long accTotal = Long.parseLong(property) - messageExt.getQueueOffset();
65: if (accTotal > 0) {
66: this.msgAccCnt = accTotal;
67: }
68: }
69: }
70: } finally {
71: this.lockTreeMap.writeLock().unlock();
72: }
73: } catch (InterruptedException e) {
74: log.error("putMessage exception", e);
75: }
76:
77: return dispatchToConsume;
78: }

总结

如果用最简单粗暴的方式描述 PullConsumer 拉取消息的过程,那就是如下的代码:

while (true) {
if (不满足拉取消息) {
Thread.sleep(间隔);
continue;
}
主动拉取消息();
}

6、PushConsumer 消费消息

DefaultMQPushConsumerImpl消费消息

ConsumeMessageConcurrentlyService 提交消费请求

ConsumeMessageConcurrentlyService#submitConsumeRequest(…)

1: /**
2: * 消费线程池队列
3: */
4: private final BlockingQueue<Runnable> consumeRequestQueue;
5: /**
6: * 消费线程池
7: */
8: private final ThreadPoolExecutor consumeExecutor;
9:
10: public void submitConsumeRequest(//
11: final List<MessageExt> msgs, //
12: final ProcessQueue processQueue, //
13: final MessageQueue messageQueue, //
14: final boolean dispatchToConsume) {
15: final int consumeBatchSize = this.defaultMQPushConsumer.getConsumeMessageBatchMaxSize();
16: if (msgs.size() <= consumeBatchSize) { // 提交消息小于批量消息数,直接提交消费请求
17: ConsumeRequest consumeRequest = new ConsumeRequest(msgs, processQueue, messageQueue);
18: try {
19: this.consumeExecutor.submit(consumeRequest);
20: } catch (RejectedExecutionException e) {
21: this.submitConsumeRequestLater(consumeRequest);
22: }
23: } else { // 提交消息大于批量消息数,进行分拆成多个消费请求
24: for (int total = 0; total < msgs.size(); ) {
25: // 计算当前拆分请求包含的消息
26: List<MessageExt> msgThis = new ArrayList<>(consumeBatchSize);
27: for (int i = 0; i < consumeBatchSize; i++, total++) {
28: if (total < msgs.size()) {
29: msgThis.add(msgs.get(total));
30: } else {
31: break;
32: }
33: }
34:
35: // 提交拆分消费请求
36: ConsumeRequest consumeRequest = new ConsumeRequest(msgThis, processQueue, messageQueue);
37: try {
38: this.consumeExecutor.submit(consumeRequest);
39: } catch (RejectedExecutionException e) {
40: // 如果被拒绝,则将当前拆分消息+剩余消息提交延迟消费请求。
41: for (; total < msgs.size(); total++) {
42: msgThis.add(msgs.get(total));
43: }
44: this.submitConsumeRequestLater(consumeRequest);
45: }
46: }
47: }
48: }
  • 说明 :提交立即消费请求。
  • 第 16 至 22 行 :提交消息小于等于批量消费数,直接提交消费请求。
  • 第 23 至 47 行 :当提交消息大于批量消费数,进行分拆成多个请求。
    • 第 25 至 33 行 :计算当前拆分请求包含的消息。
    • 第 35 至 38 行 :提交拆分消费请求。
    • 第 39 至 44 行 :提交请求被拒绝,则将当前拆分消息 + 剩余消息提交延迟消费请求,结束拆分循环。

ConsumeMessageConcurrentlyService#submitConsumeRequestLater

1: /**
2: * 提交延迟消费请求
3: *
4: * @param msgs 消息列表
5: * @param processQueue 消息处理队列
6: * @param messageQueue 消息队列
7: */
8: private void submitConsumeRequestLater(//
9: final List<MessageExt> msgs, //
10: final ProcessQueue processQueue, //
11: final MessageQueue messageQueue//
12: ) {
13:
14: this.scheduledExecutorService.schedule(new Runnable() {
15:
16: @Override
17: public void run() {
18: ConsumeMessageConcurrentlyService.this.submitConsumeRequest(msgs, processQueue, messageQueue, true);
19: }
20: }, 5000, TimeUnit.MILLISECONDS);
21: }
22:
23: /**
24: * 提交延迟消费请求
25: * @param consumeRequest 消费请求
26: */
27: private void submitConsumeRequestLater(final ConsumeRequest consumeRequest//
28: ) {
29:
30: this.scheduledExecutorService.schedule(new Runnable() {
31:
32: @Override
33: public void run() {
34: ConsumeMessageConcurrentlyService.this.consumeExecutor.submit(consumeRequest); // TODO BUG ?
35: }
36: }, 5000, TimeUnit.MILLISECONDS);
37: }
  • 说明 :提交延迟消费请求。
  • 第 34 行 :直接调用 ConsumeMessageConcurrentlyService.this.consumeExecutor.submit(consumeRequest);。如果消息数超过批量消费上限,会不会是BUG

ConsumeRequest

1: class ConsumeRequest implements Runnable {
2:
3: /**
4: * 消费消息列表
5: */
6: private final List<MessageExt> msgs;
7: /**
8: * 消息处理队列
9: */
10: private final ProcessQueue processQueue;
11: /**
12: * 消息队列
13: */
14: private final MessageQueue messageQueue;
15:
16: public ConsumeRequest(List<MessageExt> msgs, ProcessQueue processQueue, MessageQueue messageQueue) {
17: this.msgs = msgs;
18: this.processQueue = processQueue;
19: this.messageQueue = messageQueue;
20: }
21:
22: @Override
23: public void run() {
24: // 废弃队列不进行消费
25: if (this.processQueue.isDropped()) {
26: log.info("the message queue not be able to consume, because it's dropped. group={} {}", ConsumeMessageConcurrentlyService.this.consumerGroup, this.messageQueue);
27: return;
28: }
29:
30: MessageListenerConcurrently listener = ConsumeMessageConcurrentlyService.this.messageListener; // 监听器
31: ConsumeConcurrentlyContext context = new ConsumeConcurrentlyContext(messageQueue); // 消费Context
32: ConsumeConcurrentlyStatus status = null; // 消费结果状态
33:
34: // Hook
35: ConsumeMessageContext consumeMessageContext = null;
36: if (ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.hasHook()) {
37: consumeMessageContext = new ConsumeMessageContext();
38: consumeMessageContext.setConsumerGroup(defaultMQPushConsumer.getConsumerGroup());
39: consumeMessageContext.setProps(new HashMap<String, String>());
40: consumeMessageContext.setMq(messageQueue);
41: consumeMessageContext.setMsgList(msgs);
42: consumeMessageContext.setSuccess(false);
43: ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.executeHookBefore(consumeMessageContext);
44: }
45:
46: long beginTimestamp = System.currentTimeMillis();
47: boolean hasException = false;
48: ConsumeReturnType returnType = ConsumeReturnType.SUCCESS; // 消费返回结果类型
49: try {
50: // 当消息为重试消息,设置Topic为原始Topic
51: ConsumeMessageConcurrentlyService.this.resetRetryTopic(msgs);
52:
53: // 设置开始消费时间
54: if (msgs != null && !msgs.isEmpty()) {
55: for (MessageExt msg : msgs) {
56: MessageAccessor.setConsumeStartTimeStamp(msg, String.valueOf(System.currentTimeMillis()));
57: }
58: }
59:
60: // 进行消费
61: status = listener.consumeMessage(Collections.unmodifiableList(msgs), context);
62: } catch (Throwable e) {
63: log.warn("consumeMessage exception: {} Group: {} Msgs: {} MQ: {}",
64: RemotingHelper.exceptionSimpleDesc(e), //
65: ConsumeMessageConcurrentlyService.this.consumerGroup,
66: msgs,
67: messageQueue);
68: hasException = true;
69: }
70:
71: // 解析消费返回结果类型
72: long consumeRT = System.currentTimeMillis() - beginTimestamp;
73: if (null == status) {
74: if (hasException) {
75: returnType = ConsumeReturnType.EXCEPTION;
76: } else {
77: returnType = ConsumeReturnType.RETURNNULL;
78: }
79: } else if (consumeRT >= defaultMQPushConsumer.getConsumeTimeout() * 60 * 1000) {
80: returnType = ConsumeReturnType.TIME_OUT;
81: } else if (ConsumeConcurrentlyStatus.RECONSUME_LATER == status) {
82: returnType = ConsumeReturnType.FAILED;
83: } else if (ConsumeConcurrentlyStatus.CONSUME_SUCCESS == status) {
84: returnType = ConsumeReturnType.SUCCESS;
85: }
86:
87: // Hook
88: if (ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.hasHook()) {
89: consumeMessageContext.getProps().put(MixAll.CONSUME_CONTEXT_TYPE, returnType.name());
90: }
91:
92: // 消费结果状态为空时,则设置为稍后重新消费
93: if (null == status) {
94: log.warn("consumeMessage return null, Group: {} Msgs: {} MQ: {}",
95: ConsumeMessageConcurrentlyService.this.consumerGroup,
96: msgs,
97: messageQueue);
98: status = ConsumeConcurrentlyStatus.RECONSUME_LATER;
99: }
100:
101: // Hook
102: if (ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.hasHook()) {
103: consumeMessageContext.setStatus(status.toString());
104: consumeMessageContext.setSuccess(ConsumeConcurrentlyStatus.CONSUME_SUCCESS == status);
105: ConsumeMessageConcurrentlyService.this.defaultMQPushConsumerImpl.executeHookAfter(consumeMessageContext);
106: }
107:
108: // 统计
109: ConsumeMessageConcurrentlyService.this.getConsumerStatsManager()
110: .incConsumeRT(ConsumeMessageConcurrentlyService.this.consumerGroup, messageQueue.getTopic(), consumeRT);
111:
112: // 处理消费结果
113: if (!processQueue.isDropped()) {
114: ConsumeMessageConcurrentlyService.this.processConsumeResult(status, context, this);
115: } else {
116: log.warn("processQueue is dropped without process consume result. messageQueue={}, msgs={}", messageQueue, msgs);
117: }
118: }
119:
120: }
  • 说明 :消费请求。提交请求执行消费。
  • 第 24 至 28 行 :废弃处理队列不进行消费。
  • 第 34 至 44 行 :Hook。
  • 第 51 行 :当消息为重试消息,设置 Topic为原始 Topic。例如:原始 TopicTopicTest,重试时 Topic%RETRY%please_rename_unique_group_name_4,经过该方法,Topic 设置回 TopicTest
  • 第 53 至 58 行 :设置开始消费时间。
  • 第 61 行 :进行消费
  • 第 71 至 85 行 :解析消费返回结果类型
  • 第 87 至 90 行 :Hook
  • 第 92 至 99 行 :消费结果状态未空时,则设置消费结果状态为稍后消费。
  • 第 101 至 106 行 :Hook
  • 第 108 至 110 行 :统计。
  • 第 112 至 117 行 :处理消费结果。如果消费处理队列被移除,恰好消息被消费,则可能导致消息重复消费,因此,消息消费要尽最大可能性实现幂等性。详细解析见:ConsumeMessageConcurrentlyService#processConsumeResult(…)

ConsumeMessageConcurrentlyService#processConsumeResult(…)

1: public void processConsumeResult(//
2: final ConsumeConcurrentlyStatus status, //
3: final ConsumeConcurrentlyContext context, //
4: final ConsumeRequest consumeRequest//
5: ) {
6: int ackIndex = context.getAckIndex();
7:
8: // 消息为空,直接返回
9: if (consumeRequest.getMsgs().isEmpty())
10: return;
11:
12: // 计算从consumeRequest.msgs[0]到consumeRequest.msgs[ackIndex]的消息消费成功
13: switch (status) {
14: case CONSUME_SUCCESS:
15: if (ackIndex >= consumeRequest.getMsgs().size()) {
16: ackIndex = consumeRequest.getMsgs().size() - 1;
17: }
18: // 统计成功/失败数量
19: int ok = ackIndex + 1;
20: int failed = consumeRequest.getMsgs().size() - ok;
21: this.getConsumerStatsManager().incConsumeOKTPS(consumerGroup, consumeRequest.getMessageQueue().getTopic(), ok);
22: this.getConsumerStatsManager().incConsumeFailedTPS(consumerGroup, consumeRequest.getMessageQueue().getTopic(), failed);
23: break;
24: case RECONSUME_LATER:
25: ackIndex = -1;
26: // 统计成功/失败数量
27: this.getConsumerStatsManager().incConsumeFailedTPS(consumerGroup, consumeRequest.getMessageQueue().getTopic(),
28: consumeRequest.getMsgs().size());
29: break;
30: default:
31: break;
32: }
33:
34: // 处理消费失败的消息
35: switch (this.defaultMQPushConsumer.getMessageModel()) {
36: case BROADCASTING: // 广播模式,无论是否消费失败,不发回消息到Broker,只打印Log
37: for (int i = ackIndex + 1; i < consumeRequest.getMsgs().size(); i++) {
38: MessageExt msg = consumeRequest.getMsgs().get(i);
39: log.warn("BROADCASTING, the message consume failed, drop it, {}", msg.toString());
40: }
41: break;
42: case CLUSTERING:
43: // 发回消息失败到Broker。
44: List<MessageExt> msgBackFailed = new ArrayList<>(consumeRequest.getMsgs().size());
45: for (int i = ackIndex + 1; i < consumeRequest.getMsgs().size(); i++) {
46: MessageExt msg = consumeRequest.getMsgs().get(i);
47: boolean result = this.sendMessageBack(msg, context);
48: if (!result) {
49: msg.setReconsumeTimes(msg.getReconsumeTimes() + 1);
50: msgBackFailed.add(msg);
51: }
52: }
53:
54: // 发回Broker失败的消息,直接提交延迟重新消费
55: if (!msgBackFailed.isEmpty()) {
56: consumeRequest.getMsgs().removeAll(msgBackFailed);
57:
58: this.submitConsumeRequestLater(msgBackFailed, consumeRequest.getProcessQueue(), consumeRequest.getMessageQueue());
59: }
60: break;
61: default:
62: break;
63: }
64:
65: // 移除消费成功消息,并更新最新消费进度
66: long offset = consumeRequest.getProcessQueue().removeMessage(consumeRequest.getMsgs());
67: if (offset >= 0 && !consumeRequest.getProcessQueue().isDropped()) {
68: this.defaultMQPushConsumerImpl.getOffsetStore().updateOffset(consumeRequest.getMessageQueue(), offset, true);
69: }
70: }
  • 说明 :处理消费结果。
  • 第 8 至 10 行 :消费请求消息未空时,直接返回。
  • 第 12 至 32 行 :计算 ackIndex 值。consumeRequest.msgs[0 - ackIndex]为消费成功,需要进行 ack 确认。
    • 第 14 至 23 行 :CONSUME_SUCCESSackIndex = context.getAckIndex()
    • 第 24 至 29 行 :RECONSUME_LATERackIndex = -1
  • 第34 至 63 行 :处理消费失败的消息。
    • 第 36 至 41 行 :BROADCASTING :广播模式,无论是否消费失败,不发回消息到 Broker,只打印日志。
    • 第 42 至 60 行 :CLUSTERING :集群模式,消费失败的消息发回到 Broker
      • 第 43 至 52 行 :发回消费失败的消息到 Broker。详细解析见:DefaultMQPushConsumerImpl#sendMessageBack(…)
      • 第 54 至 59 行 :发回 Broker 失败的消息,直接提交延迟重新消费。
      • 如果发回 Broker 成功,结果因为例如网络异常,导致 Consumer以为发回失败,判定消费发回失败,会导致消息重复消费,因此,消息消费要尽最大可能性实现幂等性。
  • 第 65 至 69 行 :移除【消费成功】【消费失败但发回Broker成功】的消息,并更新最新消费进度。

ProcessQueue#removeMessage(…)

1: /**
2: * 移除消息,并返回第一条消息队列位置
3: *
4: * @param msgs 消息
5: * @return 消息队列位置
6: */
7: public long removeMessage(final List<MessageExt> msgs) {
8: long result = -1;
9: final long now = System.currentTimeMillis();
10: try {
11: this.lockTreeMap.writeLock().lockInterruptibly();
12: this.lastConsumeTimestamp = now;
13: try {
14: if (!msgTreeMap.isEmpty()) {
15: result = this.queueOffsetMax + 1; // 这里+1的原因是:如果msgTreeMap为空时,下一条获得的消息位置为queueOffsetMax+1
16:
17: // 移除消息
18: int removedCnt = 0;
19: for (MessageExt msg : msgs) {
20: MessageExt prev = msgTreeMap.remove(msg.getQueueOffset());
21: if (prev != null) {
22: removedCnt--;
23: }
24: }
25: msgCount.addAndGet(removedCnt);
26:
27: if (!msgTreeMap.isEmpty()) {
28: result = msgTreeMap.firstKey();
29: }
30: }
31: } finally {
32: this.lockTreeMap.writeLock().unlock();
33: }
34: } catch (Throwable t) {
35: log.error("removeMessage exception", t);
36: }
37:
38: return result;
39: }

ConsumeMessageConcurrentlyService#cleanExpireMsg(…)

1: public void start() {
2: this.cleanExpireMsgExecutors.scheduleAtFixedRate(new Runnable() {
3:
4: @Override
5: public void run() {
6: cleanExpireMsg();
7: }
8:
9: }, this.defaultMQPushConsumer.getConsumeTimeout(), this.defaultMQPushConsumer.getConsumeTimeout(), TimeUnit.MINUTES);
10: }
11:
12: /**
13: * 清理过期消息
14: */
15: private void cleanExpireMsg() {
16: Iterator<Map.Entry<MessageQueue, ProcessQueue>> it =
17: this.defaultMQPushConsumerImpl.getRebalanceImpl().getProcessQueueTable().entrySet().iterator();
18: while (it.hasNext()) {
19: Map.Entry<MessageQueue, ProcessQueue> next = it.next();
20: ProcessQueue pq = next.getValue();
21: pq.cleanExpiredMsg(this.defaultMQPushConsumer);
22: }
23: }
  • 说明 :定时清理过期消息,默认周期:15min。

ProcessQueue#cleanExpiredMsg(…)

1: public void cleanExpiredMsg(DefaultMQPushConsumer pushConsumer) {
2: // 顺序消费时,直接返回
3: if (pushConsumer.getDefaultMQPushConsumerImpl().isConsumeOrderly()) {
4: return;
5: }
6:
7: // 循环移除消息
8: int loop = msgTreeMap.size() < 16 ? msgTreeMap.size() : 16; // 每次循环最多移除16条
9: for (int i = 0; i < loop; i++) {
10: // 获取第一条消息。判断是否超时,若不超时,则结束循环
11: MessageExt msg = null;
12: try {
13: this.lockTreeMap.readLock().lockInterruptibly();
14: try {
15: if (!msgTreeMap.isEmpty() && System.currentTimeMillis() - Long.parseLong(MessageAccessor.getConsumeStartTimeStamp(msgTreeMap.firstEntry().getValue())) > pushConsumer.getConsumeTimeout() * 60 * 1000) {
16: msg = msgTreeMap.firstEntry().getValue();
17: } else {
18: break;
19: }
20: } finally {
21: this.lockTreeMap.readLock().unlock();
22: }
23: } catch (InterruptedException e) {
24: log.error("getExpiredMsg exception", e);
25: }
26:
27: try {
28: // 发回超时消息
29: pushConsumer.sendMessageBack(msg, 3);
30: log.info("send expire msg back. topic={}, msgId={}, storeHost={}, queueId={}, queueOffset={}", msg.getTopic(), msg.getMsgId(), msg.getStoreHost(), msg.getQueueId(), msg.getQueueOffset());
31:
32: // 判断此时消息是否依然是第一条,若是,则进行移除
33: try {
34: this.lockTreeMap.writeLock().lockInterruptibly();
35: try {
36: if (!msgTreeMap.isEmpty() && msg.getQueueOffset() == msgTreeMap.firstKey()) {
37: try {
38: msgTreeMap.remove(msgTreeMap.firstKey());
39: } catch (Exception e) {
40: log.error("send expired msg exception", e);
41: }
42: }
43: } finally {
44: this.lockTreeMap.writeLock().unlock();
45: }
46: } catch (InterruptedException e) {
47: log.error("getExpiredMsg exception", e);
48: }
49: } catch (Exception e) {
50: log.error("send expired msg exception", e);
51: }
52: }
53: }
  • 说明 :移除过期消息。
  • 第 2 至 5 行 :顺序消费时,直接返回。
  • 第 7 至 9 行 :循环移除消息。默认最大循环次数:16次。
  • 第 10 至 25 行 :获取第一条消息。判断是否超时,若不超时,则结束循环。
  • 第 29 行 :发回超时消息到Broker
  • 第 32 至 48 行 :判断此时消息是否依然是第一条,若是,则进行移除。

7、PushConsumer 发回消费失败消息

DefaultMQPushConsumerImpl#sendMessageBack(…)

1: public void sendMessageBack(MessageExt msg, int delayLevel, final String brokerName)
2: throws RemotingException, MQBrokerException, InterruptedException, MQClientException {
3: try {
4: // Consumer发回消息
5: String brokerAddr = (null != brokerName) ? this.mQClientFactory.findBrokerAddressInPublish(brokerName)
6: : RemotingHelper.parseSocketAddressAddr(msg.getStoreHost());
7: this.mQClientFactory.getMQClientAPIImpl().consumerSendMessageBack(brokerAddr, msg,
8: this.defaultMQPushConsumer.getConsumerGroup(), delayLevel, 5000, getMaxReconsumeTimes());
9: } catch (Exception e) { // TODO 疑问:什么情况下会发生异常
10: // 异常时,使用Client内置Producer发回消息
11: log.error("sendMessageBack Exception, " + this.defaultMQPushConsumer.getConsumerGroup(), e);
12:
13: Message newMsg = new Message(MixAll.getRetryTopic(this.defaultMQPushConsumer.getConsumerGroup()), msg.getBody());
14:
15: String originMsgId = MessageAccessor.getOriginMessageId(msg);
16: MessageAccessor.setOriginMessageId(newMsg, UtilAll.isBlank(originMsgId) ? msg.getMsgId() : originMsgId);
17:
18: newMsg.setFlag(msg.getFlag());
19: MessageAccessor.setProperties(newMsg, msg.getProperties());
20: MessageAccessor.putProperty(newMsg, MessageConst.PROPERTY_RETRY_TOPIC, msg.getTopic());
21: MessageAccessor.setReconsumeTime(newMsg, String.valueOf(msg.getReconsumeTimes() + 1));
22: MessageAccessor.setMaxReconsumeTimes(newMsg, String.valueOf(getMaxReconsumeTimes()));
23: newMsg.setDelayTimeLevel(3 + msg.getReconsumeTimes());
24:
25: this.mQClientFactory.getDefaultMQProducer().send(newMsg);
26: }
27: }
  • 说明 :发回消息。
  • 第 4 至 8 行 :Consumer 发回消息。详细解析见:MQClientAPIImpl#consumerSendMessageBack(…)
  • 第 10 至 25 行 :发生异常时,Consumer 内置默认 Producer 发送消息。
    • 😈疑问:什么样的情况下会发生异常呢?

MQClientAPIImpl#consumerSendMessageBack(…)

1: /**
2: * Consumer发回消息
3: * @param addr Broker地址
4: * @param msg 消息
5: * @param consumerGroup 消费分组
6: * @param delayLevel 延迟级别
7: * @param timeoutMillis 超时
8: * @param maxConsumeRetryTimes 消费最大重试次数
9: * @throws RemotingException 当远程调用发生异常时
10: * @throws MQBrokerException 当Broker发生异常时
11: * @throws InterruptedException 当线程中断时
12: */
13: public void consumerSendMessageBack(
14: final String addr,
15: final MessageExt msg,
16: final String consumerGroup,
17: final int delayLevel,
18: final long timeoutMillis,
19: final int maxConsumeRetryTimes
20: ) throws RemotingException, MQBrokerException, InterruptedException {
21: ConsumerSendMsgBackRequestHeader requestHeader = new ConsumerSendMsgBackRequestHeader();
22: RemotingCommand request = RemotingCommand.createRequestCommand(RequestCode.CONSUMER_SEND_MSG_BACK, requestHeader);
23:
24: requestHeader.setGroup(consumerGroup);
25: requestHeader.setOriginTopic(msg.getTopic());
26: requestHeader.setOffset(msg.getCommitLogOffset());
27: requestHeader.setDelayLevel(delayLevel);
28: requestHeader.setOriginMsgId(msg.getMsgId());
29: requestHeader.setMaxReconsumeTimes(maxConsumeRetryTimes);
30:
31: RemotingCommand response = this.remotingClient.invokeSync(MixAll.brokerVIPChannel(this.clientConfig.isVipChannelEnabled(), addr),
32: request, timeoutMillis);
33: assert response != null;
34: switch (response.getCode()) {
35: case ResponseCode.SUCCESS: {
36: return;
37: }
38: default:
39: break;
40: }
41:
42: throw new MQBrokerException(response.getCode(), response.getRemark());
43: }

8、Consumer 消费进度

OffsetStore

OffsetStore类图.png

  • RemoteBrokerOffsetStoreConsumer 集群模式 下,使用远程 Broker 消费进度。
  • LocalFileOffsetStoreConsumer 广播模式下,使用本地 文件 消费进度。

OffsetStore#load(…)

LocalFileOffsetStore#load(…)

1: @Override
2: public void load() throws MQClientException {
3: // 从本地硬盘读取消费进度
4: OffsetSerializeWrapper offsetSerializeWrapper = this.readLocalOffset();
5: if (offsetSerializeWrapper != null && offsetSerializeWrapper.getOffsetTable() != null) {
6: offsetTable.putAll(offsetSerializeWrapper.getOffsetTable());
7:
8: // 打印每个消息队列的消费进度
9: for (MessageQueue mq : offsetSerializeWrapper.getOffsetTable().keySet()) {
10: AtomicLong offset = offsetSerializeWrapper.getOffsetTable().get(mq);
11: log.info("load consumer's offset, {} {} {}",
12: this.groupName,
13: mq,
14: offset.get());
15: }
16: }
17: }
  • 说明 :从本地文件加载消费进度到内存。
OffsetSerializeWrapper
1: public class OffsetSerializeWrapper extends RemotingSerializable {
2: private ConcurrentHashMap<MessageQueue, AtomicLong> offsetTable =
3: new ConcurrentHashMap<>();
4:
5: public ConcurrentHashMap<MessageQueue, AtomicLong> getOffsetTable() {
6: return offsetTable;
7: }
8:
9: public void setOffsetTable(ConcurrentHashMap<MessageQueue, AtomicLong> offsetTable) {
10: this.offsetTable = offsetTable;
11: }
12: }
  • 说明 :本地 Offset 存储序列化。
Yunai-MacdeMacBook-Pro-2:config yunai$ cat /Users/yunai/.rocketmq_offsets/192.168.17.0@DEFAULT/please_rename_unique_group_name_1/offsets.json
{
"offsetTable":{{
"brokerName":"broker-a",
"queueId":3,
"topic":"TopicTest"
}:1470,{
"brokerName":"broker-a",
"queueId":2,
"topic":"TopicTest"
}:1471,{
"brokerName":"broker-a",
"queueId":1,
"topic":"TopicTest"
}:1470,{
"brokerName":"broker-a",
"queueId":0,
"topic":"TopicTest"
}:1470
}
}

RemoteBrokerOffsetStore#load(…)

1: @Override
2: public void load() {
3: }
  • 说明 :不进行加载,实际读取消费进度时,从 Broker 获取。

OffsetStore#readOffset(…)

读取消费进度类型:

  • READ_FROM_MEMORY :从内存读取。
  • READ_FROM_STORE :从存储( Broker文件 )读取。
  • MEMORY_FIRST_THEN_STORE :优先从内存读取,读取不到,从存储读取。

LocalFileOffsetStore#readOffset(…)

1: @Override
2: public long readOffset(final MessageQueue mq, final ReadOffsetType type) {
3: if (mq != null) {
4: switch (type) {
5: case MEMORY_FIRST_THEN_STORE:
6: case READ_FROM_MEMORY: {
7: AtomicLong offset = this.offsetTable.get(mq);
8: if (offset != null) {
9: return offset.get();
10: } else if (ReadOffsetType.READ_FROM_MEMORY == type) {
11: return -1;
12: }
13: }
14: case READ_FROM_STORE: {
15: OffsetSerializeWrapper offsetSerializeWrapper;
16: try {
17: offsetSerializeWrapper = this.readLocalOffset();
18: } catch (MQClientException e) {
19: return -1;
20: }
21: if (offsetSerializeWrapper != null && offsetSerializeWrapper.getOffsetTable() != null) {
22: AtomicLong offset = offsetSerializeWrapper.getOffsetTable().get(mq);
23: if (offset != null) {
24: this.updateOffset(mq, offset.get(), false);
25: return offset.get();
26: }
27: }
28: }
29: default:
30: break;
31: }
32: }
33:
34: return -1;
35: }
  • 第 16 行 :从 文件 读取消费进度。

RemoteBrokerOffsetStore#readOffset(…)

1: @Override
2: public long readOffset(final MessageQueue mq, final ReadOffsetType type) {
3: if (mq != null) {
4: switch (type) {
5: case MEMORY_FIRST_THEN_STORE:
6: case READ_FROM_MEMORY: {
7: AtomicLong offset = this.offsetTable.get(mq);
8: if (offset != null) {
9: return offset.get();
10: } else if (ReadOffsetType.READ_FROM_MEMORY == type) {
11: return -1;
12: }
13: }
14: case READ_FROM_STORE: {
15: try {
16: long brokerOffset = this.fetchConsumeOffsetFromBroker(mq);
17: AtomicLong offset = new AtomicLong(brokerOffset);
18: this.updateOffset(mq, offset.get(), false);
19: return brokerOffset;
20: }
21: // No offset in broker
22: catch (MQBrokerException e) {
23: return -1;
24: }
25: //Other exceptions
26: catch (Exception e) {
27: log.warn("fetchConsumeOffsetFromBroker exception, " + mq, e);
28: return -2;
29: }
30: }
31: default:
32: break;
33: }
34: }
35:
36: return -1;
37: }
  • 第 16 行 :从 Broker 读取消费进度。

OffsetStore#updateOffset(…)

该方法 RemoteBrokerOffsetStoreLocalFileOffsetStore 实现相同。

1: @Override
2: public void updateOffset(MessageQueue mq, long offset, boolean increaseOnly) {
3: if (mq != null) {
4: AtomicLong offsetOld = this.offsetTable.get(mq);
5: if (null == offsetOld) {
6: offsetOld = this.offsetTable.putIfAbsent(mq, new AtomicLong(offset));
7: }
8:
9: if (null != offsetOld) {
10: if (increaseOnly) {
11: MixAll.compareAndIncreaseOnly(offsetOld, offset);
12: } else {
13: offsetOld.set(offset);
14: }
15: }
16: }
17: }

OffsetStore#persistAll(…)

LocalFileOffsetStore#persistAll(…)

1: @Override
2: public void persistAll(Set<MessageQueue> mqs) {
3: if (null == mqs || mqs.isEmpty())
4: return;
5:
6: OffsetSerializeWrapper offsetSerializeWrapper = new OffsetSerializeWrapper();
7: for (Map.Entry<MessageQueue, AtomicLong> entry : this.offsetTable.entrySet()) {
8: if (mqs.contains(entry.getKey())) {
9: AtomicLong offset = entry.getValue();
10: offsetSerializeWrapper.getOffsetTable().put(entry.getKey(), offset);
11: }
12: }
13:
14: String jsonString = offsetSerializeWrapper.toJson(true);
15: if (jsonString != null) {
16: try {
17: MixAll.string2File(jsonString, this.storePath);
18: } catch (IOException e) {
19: log.error("persistAll consumer offset Exception, " + this.storePath, e);
20: }
21: }
22: }
  • 说明 :持久化消费进度。将消费进度写入文件

RemoteBrokerOffsetStore#persistAll(…)

1: @Override
2: public void persistAll(Set<MessageQueue> mqs) {
3: if (null == mqs || mqs.isEmpty())
4: return;
5:
6: // 持久化消息队列
7: final HashSet<MessageQueue> unusedMQ = new HashSet<>();
8: if (!mqs.isEmpty()) {
9: for (Map.Entry<MessageQueue, AtomicLong> entry : this.offsetTable.entrySet()) {
10: MessageQueue mq = entry.getKey();
11: AtomicLong offset = entry.getValue();
12: if (offset != null) {
13: if (mqs.contains(mq)) {
14: try {
15: this.updateConsumeOffsetToBroker(mq, offset.get());
16: log.info("[persistAll] Group: {} ClientId: {} updateConsumeOffsetToBroker {} {}",
17: this.groupName,
18: this.mQClientFactory.getClientId(),
19: mq,
20: offset.get());
21: } catch (Exception e) {
22: log.error("updateConsumeOffsetToBroker exception, " + mq.toString(), e);
23: }
24: } else {
25: unusedMQ.add(mq);
26: }
27: }
28: }
29: }
30:
31: // 移除不适用的消息队列
32: if (!unusedMQ.isEmpty()) {
33: for (MessageQueue mq : unusedMQ) {
34: this.offsetTable.remove(mq);
35: log.info("remove unused mq, {}, {}", mq, this.groupName);
36: }
37: }
38: }
  • 说明 :持久化指定消息队列数组的消费进度到 Broker,并移除非指定消息队列。

MQClientInstance#persistAllConsumerOffset(…)

1: private void startScheduledTask() {
2: // 定时同步消费进度
3: this.scheduledExecutorService.scheduleAtFixedRate(new Runnable() {
4:
5: @Override
6: public void run() {
7: try {
8: MQClientInstance.this.cleanOfflineBroker();
9: MQClientInstance.this.sendHeartbeatToAllBrokerWithLock();
10: } catch (Exception e) {
11: log.error("ScheduledTask sendHeartbeatToAllBroker exception", e);
12: }
13: }
14: }, 1000, this.clientConfig.getHeartbeatBrokerInterval(), TimeUnit.MILLISECONDS);
15: }
  • 说明 :定时进行持久化,默认周期:5000ms。
  • 重要说明 :
    • 消费进度持久化不仅仅只有定时持久化,拉取消息、分配消息队列等等操作,都会进行消费进度持久化。
    • 消费进度持久化不仅仅只有定时持久化,拉取消息、分配消息队列等等操作,都会进行消费进度持久化。
    • 消费进度持久化不仅仅只有定时持久化,拉取消息、分配消息队列等等操作,都会进行消费进度持久化。

9、结尾

😈可能是本系列最长的一篇文章,如有表达错误和不清晰,请多多见谅。
感谢对本系列的阅读、收藏、点赞、分享,特别是翻到结尾。😜真的有丢丢长。

文章目录
  1. 1. 1、概述
  2. 2. 2、Consumer
  3. 3. 3、PushConsumer 一览
  4. 4. 4、PushConsumer 订阅
    1. 4.1. DefaultMQPushConsumerImpl#subscribe(…)
      1. 4.1.1. FilterAPI.buildSubscriptionData(…)
    2. 4.2. DefaultMQPushConsumer#registerMessageListener(…)
  5. 5. 5、PushConsumer 消息队列分配
    1. 5.1. RebalanceService
    2. 5.2. MQClientInstance#doRebalance(…)
    3. 5.3. DefaultMQPushConsumerImpl#doRebalance(…)
    4. 5.4. RebalanceImpl#doRebalance(…)
      1. 5.4.1. RebalanceImpl#rebalanceByTopic(…)
      2. 5.4.2. RebalanceImpl#removeUnnecessaryMessageQueue(…)
        1. 5.4.2.1. RebalancePushImpl#removeUnnecessaryMessageQueue(…)
        2. 5.4.2.2. [PullConsumer] RebalancePullImpl#removeUnnecessaryMessageQueue(…)
      3. 5.4.3. RebalancePushImpl#dispatchPullRequest(…)
        1. 5.4.3.1. DefaultMQPushConsumerImpl#executePullRequestImmediately(…)
      4. 5.4.4. AllocateMessageQueueStrategy
        1. 5.4.4.1. AllocateMessageQueueAveragely
        2. 5.4.4.2. AllocateMessageQueueByMachineRoom
        3. 5.4.4.3. AllocateMessageQueueAveragelyByCircle
        4. 5.4.4.4. AllocateMessageQueueByConfig
  6. 6. 5、PushConsumer 消费进度读取
    1. 6.1. RebalancePushImpl#computePullFromWhere(…)
    2. 6.2. [PullConsumer] RebalancePullImpl#computePullFromWhere(…)
  7. 7. 6、PushConsumer 拉取消息
    1. 7.1. PullMessageService
    2. 7.2. DefaultMQPushConsumerImpl#pullMessage(…)
      1. 7.2.1. PullAPIWrapper#pullKernelImpl(…)
        1. 7.2.1.1. PullAPIWrapper#recalculatePullFromWhichNode(…)
        2. 7.2.1.2. MQClientInstance#findBrokerAddressInSubscribe(…)
      2. 7.2.2. PullAPIWrapper#processPullResult(…)
      3. 7.2.3. ProcessQueue#putMessage(…)
    3. 7.3. 总结
  8. 8. 6、PushConsumer 消费消息
    1. 8.1. ConsumeMessageConcurrentlyService 提交消费请求
      1. 8.1.1. ConsumeMessageConcurrentlyService#submitConsumeRequest(…)
      2. 8.1.2. ConsumeMessageConcurrentlyService#submitConsumeRequestLater
    2. 8.2. ConsumeRequest
    3. 8.3. ConsumeMessageConcurrentlyService#processConsumeResult(…)
      1. 8.3.1. ProcessQueue#removeMessage(…)
    4. 8.4. ConsumeMessageConcurrentlyService#cleanExpireMsg(…)
      1. 8.4.1. ProcessQueue#cleanExpiredMsg(…)
  9. 9. 7、PushConsumer 发回消费失败消息
    1. 9.1. DefaultMQPushConsumerImpl#sendMessageBack(…)
      1. 9.1.1. MQClientAPIImpl#consumerSendMessageBack(…)
  10. 10. 8、Consumer 消费进度
    1. 10.1. OffsetStore
      1. 10.1.1. OffsetStore#load(…)
        1. 10.1.1.1. LocalFileOffsetStore#load(…)
          1. 10.1.1.1.1. OffsetSerializeWrapper
        2. 10.1.1.2. RemoteBrokerOffsetStore#load(…)
      2. 10.1.2. OffsetStore#readOffset(…)
        1. 10.1.2.1. LocalFileOffsetStore#readOffset(…)
        2. 10.1.2.2. RemoteBrokerOffsetStore#readOffset(…)
      3. 10.1.3. OffsetStore#updateOffset(…)
      4. 10.1.4. OffsetStore#persistAll(…)
        1. 10.1.4.1. LocalFileOffsetStore#persistAll(…)
        2. 10.1.4.2. RemoteBrokerOffsetStore#persistAll(…)
        3. 10.1.4.3. MQClientInstance#persistAllConsumerOffset(…)
  11. 11. 9、结尾