RabbitMQ发布确认-编程知识

1.单个确认

单个确认发布是一种同步确认发布方式，也就是发布一个消息后只有它被确认发布，后续的消息才能继续发布。
缺点:发布速度特别慢,因为若是没有确认发布的消息会阻塞所有后续消息的发布

package com.hong.rabbitmq5;import com.hong.utils.RabbitMQUtil;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.MessageProperties;import java.util.UUID;/*** @Description: 发布确认-单个确认发布* 单个确认发布是一种同步确认发布方式，也就是发布一个消息后只有它被确认发布，后续的消息才能继续发布。* 缺点:发布速度特别慢,因为若是没有确认发布的消息会阻塞所有后续消息的发布* @Author: hong* @Date: 2023-12-21 20:52* @Version: 1.0**/
public class Task5 {public static void main(String[] args) throws Exception{String queueName = UUID.randomUUID().toString();Channel channel = RabbitMQUtil.getChannel();//队列持久化   true持久化channel.queueDeclare(queueName,true,false,false,null);//开启发布确认  默认关闭channel.confirmSelect();long startTime = System.currentTimeMillis();for(int i = 0; i <= 1000; i++){String message = i + "";//消息持久化  MessageProperties.PERSISTENT_TEXT_PLAINchannel.basicPublish("",queueName, MessageProperties.PERSISTENT_TEXT_PLAIN,message.getBytes("UTF-8"));//发布就确认boolean flag = channel.waitForConfirms();if(flag){System.out.println("第"+i+"个消息发布成功!");}}long endTime = System.currentTimeMillis();System.out.println("发布1000个消息单个确认发布总耗时:"+(endTime - startTime)+"ms");}
}

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2. 批量确认

批量确认发布也是一种同步确认发布方式,一批确认一次,相比单个确认发布极大地提升了吞吐量
缺点:一旦出故障难以确认到底是哪个消息出问题了

package com.hong.rabbitmq5;import com.hong.utils.RabbitMQUtil;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.MessageProperties;import java.util.UUID;/*** @Description: 批量确认发布* 批量确认发布也是一种同步确认发布方式,一批确认一次,相比单个确认发布极大地提升了吞吐量* 缺点:一旦出故障难以确认到底是哪个消息出问题了* @Author: hong* @Date: 2024-01-03 17:44* @Version: 1.0**/
public class BatchConfirmPublish {public static void main(String[] args) throws Exception {String queueName = UUID.randomUUID().toString();Channel channel = RabbitMQUtil.getChannel();//队列持久化   true持久化channel.queueDeclare(queueName,true,false,false,null);//开启发布确认  默认关闭channel.confirmSelect();//100个确认一次int batchSize = 100;long startTime = System.currentTimeMillis();for(int i = 1; i <= 1000; i++){String message = i + "";//消息持久化  MessageProperties.PERSISTENT_TEXT_PLAINchannel.basicPublish("",queueName, MessageProperties.PERSISTENT_TEXT_PLAIN,message.getBytes("UTF-8"));if(i%batchSize == 0){//发布就确认channel.waitForConfirms();}}long endTime = System.currentTimeMillis();System.out.println("发布1000个消息,批量确认发布总耗时:"+(endTime - startTime)+"ms");}
}

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3. 异步确认

package com.hong.rabbitmq5;import com.hong.utils.RabbitMQUtil;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.ConfirmCallback;
import com.rabbitmq.client.MessageProperties;import java.util.UUID;
import java.util.concurrent.ConcurrentNavigableMap;
import java.util.concurrent.ConcurrentSkipListMap;/*** @Description: 异步确认发布* @Author: hong* @Date: 2024-01-06 20:41* @Version: 1.0**/
public class AsynConfirmPublish {public static void main(String[] args) throws Exception {Channel channel = RabbitMQUtil.getChannel();//队列的声明String queueName = UUID.randomUUID().toString();//队列持久化   true持久化channel.queueDeclare(queueName,true,false,false,null);//开启发布确认  默认关闭channel.confirmSelect();ConcurrentSkipListMap<Long,String> concurrentSkipListMap =new ConcurrentSkipListMap<>();//消息确认回调的函数ConfirmCallback ackCallback = (deliveryTag, multiple) ->{if(multiple) {//2.删除掉已经确认的消息 剩下的就是未确认的消息ConcurrentNavigableMap<Long, String> confirmed =concurrentSkipListMap.headMap(deliveryTag);confirmed.clear();}else {concurrentSkipListMap.remove(deliveryTag);}System.out.println("确认的消息:" + deliveryTag);};//消息确认失败回调函数ConfirmCallback nackCallback= (deliveryTag,multiple) ->{//3.打印一下未确认的消息都有哪些String message = concurrentSkipListMap.get(deliveryTag);System.out.println("未确认的消息tag:"  + deliveryTag + "-----------未确认的消息是:" + message);};/** 消息的监听器   异步通知*/channel.addConfirmListener(ackCallback,nackCallback);long begin = System.currentTimeMillis();//批量发送消息for (int i = 1; i <= 1000; i++) {String message= "消息" + i;//消息持久化  MessageProperties.PERSISTENT_TEXT_PLAINchannel.basicPublish("",queueName, MessageProperties.PERSISTENT_TEXT_PLAIN,message.getBytes("UTF-8"));//1.此处记录下所有要发送的消息 消息的总和concurrentSkipListMap.put(channel.getNextPublishSeqNo(),message);}//结束时间long end = System.currentTimeMillis();System.out.println("发布1000个消息,异步确认消息总耗时:"+(end-begin)+"ms");}
}