RocketMQ源码解析-生产者投递消息策略
以下源码基于Rocket MQ 4.7.0
1. 消息类型
2. 基于Queue队列轮询算法投递
2.1 默认轮询算法
默认情况下，采用了最简单的轮询算法，这种算法有个很好的特性就是，保证每一个Queue队列的消息投递数量尽可能均匀。看一下代码的实现，
//DefaultMQProducerImpl selectOneMessageQueue选择队列
public MessageQueue selectOneMessageQueue(final TopicPublishInfo tpInfo, final String lastBrokerName) {
return this.mqFaultStrategy.selectOneMessageQueue(tpInfo, lastBrokerName);
}
//MQFaultStrategy selectOneMessageQueue
public MessageQueue selectOneMessageQueue(final TopicPublishInfo tpInfo, final String lastBrokerName) {
if (this.sendLatencyFaultEnable) {
try {
int index = tpInfo.getSendWhichQueue().getAndIncrement();
for (int i = 0; i < tpInfo.getMessageQueueList().size(); i++) {
int pos = Math.abs(index++) % tpInfo.getMessageQueueList().size();
if (pos < 0)
pos = 0;
MessageQueue mq = tpInfo.getMessageQueueList().get(pos);
if (latencyFaultTolerance.isAvailable(mq.getBrokerName())) {
if (null == lastBrokerName || mq.getBrokerName().equals(lastBrokerName))
return mq;
}
}
final String notBestBroker = latencyFaultTolerance.pickOneAtLeast();
int writeQueueNums = tpInfo.getQueueIdByBroker(notBestBroker);
if (writeQueueNums > 0) {
final MessageQueue mq = tpInfo.selectOneMessageQueue();
if (notBestBroker != null) {
mq.setBrokerName(notBestBroker);
mq.setQueueId(tpInfo.getSendWhichQueue().getAndIncrement() % writeQueueNums);
}
return mq;
} else {
latencyFaultTolerance.remove(notBestBroker);
}
} catch (Exception e) {
log.error("Error occurred when selecting message queue", e);
}
return tpInfo.selectOneMessageQueue();
}
return tpInfo.selectOneMessageQueue(lastBrokerName);
}
在默认的情况下 sendLatencyFaultEnable=false 直接调用的是 TopicPublishInfo.selectOneMessageQueue 方法:
//发布的对象中TopicPublishInfo
public class TopicPublishInfo {
//基于线程上下文的计数递增--用于轮询目的
private volatile ThreadLocalIndex sendWhichQueue = new ThreadLocalIndex();
public MessageQueue selectOneMessageQueue(final String lastBrokerName) {
if (lastBrokerName == null) {
return selectOneMessageQueue();
} else {
int index = this.sendWhichQueue.getAndIncrement();
for (int i = 0; i < this.messageQueueList.size(); i++) {
//轮询
int pos = Math.abs(index++) % this.messageQueueList.size();
if (pos < 0)
pos = 0;
MessageQueue mq = this.messageQueueList.get(pos);
if (!mq.getBrokerName().equals(lastBrokerName)) {
return mq;
}
}
return selectOneMessageQueue();
}
}
//获取消费队列
public MessageQueue selectOneMessageQueue() {
int index = this.sendWhichQueue.getAndIncrement();
int pos = Math.abs(index) % this.messageQueueList.size();
if (pos < 0)
pos = 0;
return this.messageQueueList.get(pos);
}
}
2.2 默认投递方式的增强
基于Queue队列轮询算法和消息投递延迟最小的策略投递，默认的投递方式比较简单，但是也暴露了一个问题，就是有些Queue队列可能由于自身数量积压等原因，可能在投递的过程比较长，对于这样的Queue队列会影响后续投递的效果。 基于这种现象，RocketMQ在每发送一个MQ消息后，都会统计一下消息投递的时间延迟，根据这个时间延迟，可以知道往哪些Queue队列投递的速度快。 在这种场景下，会优先使用消息投递延迟最小的策略，如果没有生效，再使用Queue队列轮询的方式。
public MessageQueue selectOneMessageQueue(final TopicPublishInfo tpInfo, final String lastBrokerName) {
if (this.sendLatencyFaultEnable) {
try {
int index = tpInfo.getSendWhichQueue().getAndIncrement();
for (int i = 0; i < tpInfo.getMessageQueueList().size(); i++) {
int pos = Math.abs(index++) % tpInfo.getMessageQueueList().size();
if (pos < 0)
pos = 0;
//轮询获取
MessageQueue mq = tpInfo.getMessageQueueList().get(pos);
//第一次返回一定是true
if (latencyFaultTolerance.isAvailable(mq.getBrokerName())) {
if (null == lastBrokerName || mq.getBrokerName().equals(lastBrokerName))
return mq;
}
}
// 从延迟容错broker列表中挑选一个容错性最好的一个 broker
final String notBestBroker = latencyFaultTolerance.pickOneAtLeast();
int writeQueueNums = tpInfo.getQueueIdByBroker(notBestBroker);
if (writeQueueNums > 0) {
final MessageQueue mq = tpInfo.selectOneMessageQueue();
if (notBestBroker != null) {
// 取余挑选其中一个队列
mq.setBrokerName(notBestBroker);
mq.setQueueId(tpInfo.getSendWhichQueue().getAndIncrement() % writeQueueNums);
}
return mq;
} else {
latencyFaultTolerance.remove(notBestBroker);
}
} catch (Exception e) {
log.error("Error occurred when selecting message queue", e);
}
return tpInfo.selectOneMessageQueue();
}
return tpInfo.selectOneMessageQueue(lastBrokerName);
}
数据的设置在：
private SendResult sendDefaultImpl(
Message msg,
final CommunicationMode communicationMode,
final SendCallback sendCallback,
final long timeout
) throws MQClientException, RemotingException, MQBrokerException, InterruptedException {
//省略代码
//这里就是把发送消息的数据到broker时间
this.updateFaultItem(mq.getBrokerName(), endTimestamp - beginTimestampPrev, false);
//省略代码
}
3. 顺序消息的投递
上面的两种消息的投递方式时序性没有要求的场景，这种投递的速度和效率比较高。而在有些场景下，需要保证同类型消息投递和消费的顺序性。通过一定的策略，将其放置在一个 queue队列中。看一下在生产者中如何发送顺序消息：
public class OrderedProducer {
public static void main(String[] args) throws Exception {
//Instantiate with a producer group name.
MQProducer producer = new DefaultMQProducer("example_group_name");
//Launch the instance.
producer.start();
String[] tags = new String[] {"TagA", "TagB", "TagC", "TagD", "TagE"};
for (int i = 0; i < 100; i++) {
int orderId = i % 10;
//Create a message instance, specifying topic, tag and message body.
Message msg = new Message("TopicTestjjj", tags[i % tags.length], "KEY" + i,
("Hello RocketMQ " + i).getBytes(RemotingHelper.DEFAULT_CHARSET));
SendResult sendResult = producer.send(msg, new MessageQueueSelector() {
@Override
public MessageQueue select(List<MessageQueue> mqs, Message msg, Object arg) {
Integer id = (Integer) arg;
int index = id % mqs.size();
return mqs.get(index);
}
}, orderId);
System.out.printf("%s%n", sendResult);
}
//server shutdown
producer.shutdown();
}
}
上面的例子是官网的一个例子。通过ID来选择发送的broker中的某一个写入队列。生产者在消息的投递过程中使用了 MessageQueueSelector 作为消息队列的选择策略。
public interface MessageQueueSelector {
MessageQueue select(final List<MessageQueue> mqs, final Message msg, final Object arg);
}
在MQ中默认提供了三种实现:
SelectMessageQueueByHash的实现：
public class SelectMessageQueueByHash implements MessageQueueSelector {
@Override
public MessageQueue select(List<MessageQueue> mqs, Message msg, Object arg) {
int value = arg.hashCode();
if (value < 0) {
value = Math.abs(value);
}
value = value % mqs.size();
return mqs.get(value);
}
}
SelectMessageQueueByMachineRoom的实现：
public class SelectMessageQueueByMachineRoom implements MessageQueueSelector {
private Set<String> consumeridcs;
@Override
public MessageQueue select(List<MessageQueue> mqs, Message msg, Object arg) {
return null;
}
public Set<String> getConsumeridcs() {
return consumeridcs;
}
public void setConsumeridcs(Set<String> consumeridcs) {
this.consumeridcs = consumeridcs;
}
}
SelectMessageQueueByRandom的实现：
public class SelectMessageQueueByRandom implements MessageQueueSelector {
private Random random = new Random(System.currentTimeMillis());
@Override
public MessageQueue select(List<MessageQueue> mqs, Message msg, Object arg) {
int value = random.nextInt(mqs.size());
return mqs.get(value);
}
}
通过 MessageQueueSelector 类的实现跨越选择消息发送的队列。对于同一个队列的消息是有序的。不同队列的消息进行消费可能是无序的。