批量发送消息能显著提高传递小消息的性能。限制是这些批量消息应该有相同的topic,相同的waitStoreMsgOK,而且不能是延时消息。此外,这一批消息的总大小不应超过4MB。
如果您每次只发送不超过4MB的消息,则很容易使用批处理,样例如下:
String topic = "BatchTest";
List<Message> messages = new ArrayList<>();
messages.add(new Message(topic, "TagA", "OrderID001", "Hello world 0".getBytes()));
messages.add(new Message(topic, "TagA", "OrderID002", "Hello world 1".getBytes()));
messages.add(new Message(topic, "TagA", "OrderID003", "Hello world 2".getBytes()));
try {
producer.send(messages);
} catch (Exception e) {
e.printStackTrace();
//处理error
}
复杂度只有当你发送大批量时才会增长,你可能不确定它是否超过了大小限制(4MB)。这时候你最好把你的消息列表分割一下:
package io.mvvm.batch;
import org.apache.rocketmq.common.message.Message;
import java.util.Iterator;
import java.util.List;
import java.util.Map;
/**
* 消息列表分割
*/
public class ListSplitter implements Iterator<List<Message>> {
private final int SIZE_LIMIT = 1024 * 1024 * 4;
private final List<Message> messages;
private int currIndex;
public ListSplitter(List<Message> messages) {
this.messages = messages;
}
@Override
public boolean hasNext() {
return currIndex < messages.size();
}
@Override
public List<Message> next() {
int startIndex = getStartIndex();
int nextIndex = startIndex;
int totalSize = 0;
for (; nextIndex < messages.size(); nextIndex++) {
Message message = messages.get(nextIndex);
int tmpSize = calcMessageSize(message);
if (tmpSize + totalSize > SIZE_LIMIT) {
break;
} else {
totalSize += tmpSize;
}
}
List<Message> subList = messages.subList(startIndex, nextIndex);
currIndex = nextIndex;
return subList;
}
private int getStartIndex() {
Message currMessage = messages.get(currIndex);
int tmpSize = calcMessageSize(currMessage);
while (tmpSize > SIZE_LIMIT) {
currIndex += 1;
Message message = messages.get(currIndex);
tmpSize = calcMessageSize(message);
}
return currIndex;
}
private int calcMessageSize(Message message) {
int tmpSize = message.getTopic().length() + message.getBody().length;
Map<String, String> properties = message.getProperties();
for (Map.Entry<String, String> entry : properties.entrySet()) {
tmpSize += entry.getKey().length() + entry.getValue().length();
}
tmpSize = tmpSize + 20; // 增加⽇日志的开销20字节
return tmpSize;
}
}
package io.mvvm.batch;
import org.apache.rocketmq.client.producer.DefaultMQProducer;
import org.apache.rocketmq.client.producer.SendResult;
import org.apache.rocketmq.common.message.Message;
import java.util.ArrayList;
import java.util.List;
/**
* @program: spring-cloud-alibaba
* @description: 批量消息提供者
* @author: 潘
* @create: 2020-12-27 22:32
**/
public class Producer {
public static void main(String[] args) throws Exception{
DefaultMQProducer producer = new DefaultMQProducer("group1");
producer.setNamesrvAddr("127.0.0.1:9876");
producer.start();
String topic = "BatchTest";
List<Message> messages = new ArrayList<>();
messages.add(new Message(topic, "TagA", "OrderID001", "Hello world 0".getBytes()));
messages.add(new Message(topic, "TagA", "OrderID002", "Hello world 1".getBytes()));
messages.add(new Message(topic, "TagA", "OrderID003", "Hello world 2".getBytes()));
//把大的消息分裂成若干个小的消息
ListSplitter splitter = new ListSplitter(messages);
while (splitter.hasNext()) {
try {
List<Message> listItem = splitter.next();
SendResult send = producer.send(listItem);
System.out.println(send);
} catch (Exception e) {
e.printStackTrace();
//处理error
}
}
}
}
package io.mvvm.batch;
import org.apache.rocketmq.client.consumer.DefaultMQPushConsumer;
import org.apache.rocketmq.client.consumer.listener.ConsumeOrderlyContext;
import org.apache.rocketmq.client.consumer.listener.ConsumeOrderlyStatus;
import org.apache.rocketmq.client.consumer.listener.MessageListenerOrderly;
import org.apache.rocketmq.common.consumer.ConsumeFromWhere;
import org.apache.rocketmq.common.message.MessageExt;
import java.util.List;
/**
* @program: spring-cloud-alibaba
* @description: 批量消息消费者
* @author: 潘
* @create: 2020-12-27 22:33
**/
public class Consumer {
public static void main(String[] args) throws Exception {
DefaultMQPushConsumer consumer = new DefaultMQPushConsumer("group1");
consumer.setNamesrvAddr("127.0.0.1:9876");
/**
* 设置Consumer第一次启动是从队列头部开始消费还是队列尾部开始消费<br>
* 如果非第一次启动,那么按照上次消费的位置继续消费
*/
consumer.setConsumeFromWhere(ConsumeFromWhere.CONSUME_FROM_FIRST_OFFSET);
consumer.subscribe("BatchTest", "TagA");
consumer.registerMessageListener(new MessageListenerOrderly() {
@Override
public ConsumeOrderlyStatus consumeMessage(List<MessageExt> msgs, ConsumeOrderlyContext context) {
context.setAutoCommit(true);
for (MessageExt msg : msgs) {
// 可以看到每个queue有唯一的consume线程来消费, 订单对每个queue(分区)有序
System.out.println("consumeThread=" + Thread.currentThread().getName() + "queueId=" + msg.getQueueId() + ", content:" + new String(msg.getBody()));
}
return ConsumeOrderlyStatus.SUCCESS;
}
});
consumer.start();
System.out.println("Consumer Started.");
System.in.read();
}
}