目的:

  RabbitMQ之消息模式(上):https://www.cnblogs.com/huangting/p/11994539.html

  消费端限流

  消息的ACK与重回队列

  TTL消息

  死信队列


消费端限流

什么是消费端的限流? 

假设一个场景,首先,我们RabbitMQ服务器有上万条未处理的消息,我们随便打开一个消费者客户端,会出现下面情况:

巨量的消息瞬间全部推送过来,但是我们单个客户端无法同时处理这么多数据

消费端限流RabbitMQ提供的解决方案

RabbitMQ提供了一种qos(服务质量保证)功能,即在非自动确认消息的前提下,如果一定数目的消息(通过基于Consumer或者Channel设置Qos的值)未被确认前,不进行消费新的消息

Void BasicQos(uint prefetchSize, ushort prefetchCount, bool global);

prefetchSize:0 不限制消息大小

prefetchSize:会告诉RabbitMQ不要同时给一个消费者推送多于N个消息,即一旦有N个消息还没有ack,则该Consumer将block(阻塞)掉,直到有消息ack

Global:true\false是否将上面设置应用于Channel;简单来说,就是上面限制是Channel级别的还是Consumer级别

注意:
prefetchSize和global这两项,RabbitMQ没有实现,暂且不研究;
prefetch_count在no_ask=false的情况下生效,即在自动应答的情况下,这两个值是不生效的

首先启动虚拟机打开centos启动rabbitmq镜像

  不然后期在idea中运行项目绝对报错

自定义消费端代码

package com.javaxh.rabbitmqapi.limit;
import com.rabbitmq.client.AMQP;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.DefaultConsumer;
import com.rabbitmq.client.Envelope; import java.io.IOException; public class MyConsumer extends DefaultConsumer {
private Channel channel ; public MyConsumer(Channel channel) {
super(channel);
this.channel = channel;
} @Override
public void handleDelivery(String consumerTag, Envelope envelope, AMQP.BasicProperties properties, byte[] body) throws IOException {
System.err.println("-----------consume message----------");
System.err.println("consumerTag: " + consumerTag);
System.err.println("envelope: " + envelope);
System.err.println("properties: " + properties);
System.err.println("body: " + new String(body)); channel.basicAck(envelope.getDeliveryTag(), false);
} }

消费端代码:

package com.javaxh.rabbitmqapi.limit;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory; public class Consumer {
public static void main(String[] args) throws Exception {
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.239.131");
connectionFactory.setPort(5672);
connectionFactory.setVirtualHost("/"); Connection connection = connectionFactory.newConnection();
Channel channel = connection.createChannel(); String exchangeName = "test_qos_exchange";
String queueName = "test_qos_queue";
String routingKey = "qos.#"; channel.exchangeDeclare(exchangeName, "topic", true, false, null);
channel.queueDeclare(queueName, true, false, false, null);
channel.queueBind(queueName, exchangeName, routingKey); //1 限流方式 第一件事就是 autoAck设置为 false
channel.basicQos(0, 1, false); channel.basicConsume(queueName, false, new MyConsumer(channel));
}
}

生产端代码:

package com.javaxh.rabbitmqapi.limit;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory; public class Producer {
public static void main(String[] args) throws Exception {
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.239.131");
connectionFactory.setPort(5672);
connectionFactory.setVirtualHost("/"); Connection connection = connectionFactory.newConnection();
Channel channel = connection.createChannel(); String exchange = "test_qos_exchange";
String routingKey = "qos.save"; String msg = "Hello RabbitMQ QOS Message"; for(int i =0; i<5; i ++){
channel.basicPublish(exchange, routingKey, true, null, msg.getBytes());
} }
}

先运行消费端在运行生产端:


消息的ACK与重回队列

消费端手工ACK与NACK

消费端进行消费的时候,如果由于业务异常我们可以进行日志的记录,然后进行补偿

如果由于服务器宕机等严重问题,那么我们就需要手工进行ACK,保障消费端消费成功

消费端的重回队列

  自定义消费者代码

package com.javaxh.rabbitmqapi.ack;
import com.rabbitmq.client.AMQP;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.DefaultConsumer;
import com.rabbitmq.client.Envelope; import java.io.IOException; public class MyConsumer extends DefaultConsumer { private Channel channel ; public MyConsumer(Channel channel) {
super(channel);
this.channel = channel;
} @Override
public void handleDelivery(String consumerTag, Envelope envelope, AMQP.BasicProperties properties, byte[] body) throws IOException {
System.err.println("-----------consume message----------");
System.err.println("body: " + new String(body));
try {
Thread.sleep(2000);
} catch (InterruptedException e) {
e.printStackTrace();
}
if((Integer)properties.getHeaders().get("num") == 0) {
// 手动签收,重回队列
channel.basicNack(envelope.getDeliveryTag(), false, true);
} else {
channel.basicAck(envelope.getDeliveryTag(), false);
} } }

消费端代码:

package com.javaxh.rabbitmqapi.ack;

import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory; public class Consumer {
public static void main(String[] args) throws Exception {
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.239.131");
connectionFactory.setPort(5672);
connectionFactory.setVirtualHost("/"); Connection connection = connectionFactory.newConnection();
Channel channel = connection.createChannel(); String exchangeName = "test_ack_exchange";
String queueName = "test_ack_queue";
String routingKey = "ack.#"; channel.exchangeDeclare(exchangeName, "topic", true, false, null);
channel.queueDeclare(queueName, true, false, false, null);
channel.queueBind(queueName, exchangeName, routingKey); // 手工签收 必须要关闭 autoAck = false
channel.basicConsume(queueName, false, new MyConsumer(channel));
}
}

生产端代码:

package com.javaxh.rabbitmqapi.ack;
import com.rabbitmq.client.AMQP;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory; import java.util.HashMap;
import java.util.Map;
public class Producer {
public static void main(String[] args) throws Exception {
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.239.131");
connectionFactory.setPort(5672);
connectionFactory.setVirtualHost("/"); Connection connection = connectionFactory.newConnection();
Channel channel = connection.createChannel(); String exchange = "test_ack_exchange";
String routingKey = "ack.save"; for(int i =0; i<5; i ++){
Map<String, Object> headers = new HashMap<String, Object>();
headers.put("num", i);
AMQP.BasicProperties properties = new AMQP.BasicProperties.Builder()
.deliveryMode(2)
.contentEncoding("UTF-8")
.headers(headers)
.build();
String msg = "Hello RabbitMQ ACK Message " + i;
channel.basicPublish(exchange, routingKey, true, properties, msg.getBytes());
}
}
}

先运行消费端在运行生产端:

  

去rabbitmq中去查看


TTL消息

TTL是Time To Live的缩写,也就是生存时间

RabbitMQ支持消息的过期时间,在消息发送时可以进行指定

RabbitMQ支持队列的过期时间,从消息入队列开始计算,只要超过了队列的超时时间配置,那么消息自动的清除

纯控制台操作(演示TTL队列消息特点)

针对队列,只要是这个队列的消息,就只有这么长的存活时间

注意:主要针对消息设置,跟交换机、队列、消费者设置毫无关系

消费端代码

package com.javaxh.rabbitmqapi.ttl;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory;
import com.rabbitmq.client.QueueingConsumer; import java.util.Map;
public class Consumer {
public static void main(String[] args) throws Exception { //1 创建一个ConnectionFactory, 并进行配置
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.239.131");
connectionFactory.setPort(5672);
connectionFactory.setVirtualHost("/"); //2 通过连接工厂创建连接
Connection connection = connectionFactory.newConnection(); //3 通过connection创建一个Channel
Channel channel = connection.createChannel(); //4 声明(创建)一个队列
String queueName = "test001";
channel.queueDeclare(queueName, true, false, false, null); //5 创建消费者
QueueingConsumer queueingConsumer = new QueueingConsumer(channel); //6 设置Channel
channel.basicConsume(queueName, true, queueingConsumer); while(true){
//7 获取消息
QueueingConsumer.Delivery delivery = queueingConsumer.nextDelivery();
String msg = new String(delivery.getBody());
System.err.println("消费端: " + msg);
Map<String, Object> headers = delivery.getProperties().getHeaders();
System.err.println("headers get my1 value: " + headers.get("my1")); //Envelope envelope = delivery.getEnvelope();
} }
}

生产端代码:

package com.javaxh.rabbitmqapi.ttl;
import com.rabbitmq.client.AMQP;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory; import java.util.HashMap;
import java.util.Map;
public class Procuder {
public static void main(String[] args) throws Exception {
//1 创建一个ConnectionFactory, 并进行配置
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.239.131");
connectionFactory.setPort(5672);
connectionFactory.setVirtualHost("/"); //2 通过连接工厂创建连接
Connection connection = connectionFactory.newConnection(); //3 通过connection创建一个Channel
Channel channel = connection.createChannel(); Map<String, Object> headers = new HashMap<>();
headers.put("my1", "111");
headers.put("my2", "222"); AMQP.BasicProperties properties = new AMQP.BasicProperties.Builder()
.deliveryMode(2)
.contentEncoding("UTF-8")
.expiration("10000")
.headers(headers)
.build(); //4 通过Channel发送数据
for(int i=0; i < 5; i++){
String msg = "Hello RabbitMQ!";
//1 exchange 2 routingKey
channel.basicPublish("", "test001", properties, msg.getBytes());
} //5 记得要关闭相关的连接
channel.close();
connection.close();
}
}

还是先运行消费端在运行生产端:


死信队列

死信队列:DLX,Dead-Letter-Exchange

利用DLX,当消息在一个队列中变成死信(dead message)之后,它能被重新publish到另一个Exchange,这个Exchange就是DLX

消息变成死信有以下几种情况

    • 消息被拒绝(basic.reject/basic.nack)并且requeue=false
    • 消息TTL过期
    • 队列达到最大长度

死信队列的特点

DLX也是一个正常的Exchange,和一般的Exchange没有区别,它能在任何的队列上被指定,实际上就是设置某个队列的属性;

当这个队列中有死信时,RabbitMQ就会自动的将这个消息重新发布到设置的Exchange上去,进而被路由到另一个队列;

可以监听这个队列中消息做相应的处理,这个特性可以弥补RabbitMQ3.0以前支持的immediate参数的功能

死信队列设置

  • 首先需要设置死信队列的Exchange和Queue,然后进行绑定:

Exchange:dlx.exchange

Queue:dlx.queue

RoutingKey:#

  • 然后我们进行正常声明交换机、队列、绑定,只不过我们需要在队列加上一个参数即可:

Arguments.put(“x-dead-letter-exchange”,”dlx.exchange”);

这样消息在过期、requeue、队列在达到最大长度时,消息就可以直接路由到死信队列

自定义消费端

package com.javaxh.rabbitmqapi.dlx;
import com.rabbitmq.client.AMQP;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.DefaultConsumer;
import com.rabbitmq.client.Envelope;
import java.io.IOException;
public class MyConsumer extends DefaultConsumer {
public MyConsumer(Channel channel) {
super(channel);
} @Override
public void handleDelivery(String consumerTag, Envelope envelope, AMQP.BasicProperties properties, byte[] body) throws IOException {
System.err.println("-----------consume message----------");
System.err.println("consumerTag: " + consumerTag);
System.err.println("envelope: " + envelope);
System.err.println("properties: " + properties);
System.err.println("body: " + new String(body));
}
}

消费端:

package com.javaxh.rabbitmqapi.dlx;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory;
import java.util.HashMap;
import java.util.Map;
public class Consumer {
public static void main(String[] args) throws Exception {
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.239.131");
connectionFactory.setPort(5672);
connectionFactory.setVirtualHost("/"); Connection connection = connectionFactory.newConnection();
Channel channel = connection.createChannel(); // 这就是一个普通的交换机 和 队列 以及路由
String exchangeName = "test_dlx_exchange";
String routingKey = "dlx.#";
String queueName = "test_dlx_queue"; channel.exchangeDeclare(exchangeName, "topic", true, false, null); Map<String, Object> agruments = new HashMap<String, Object>();
agruments.put("x-dead-letter-exchange", "dlx.exchange");
//这个agruments属性,要设置到声明队列上
channel.queueDeclare(queueName, true, false, false, agruments);
channel.queueBind(queueName, exchangeName, routingKey); //要进行死信队列的声明:
channel.exchangeDeclare("dlx.exchange", "topic", true, false, null);
channel.queueDeclare("dlx.queue", true, false, false, null);
channel.queueBind("dlx.queue", "dlx.exchange", "#"); channel.basicConsume(queueName, true, new MyConsumer(channel)); }
}

生产端代码:

package com.javaxh.rabbitmqapi.dlx;
import com.rabbitmq.client.AMQP;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory;
public class Producer {
public static void main(String[] args) throws Exception { ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.239.131");
connectionFactory.setPort(5672);
connectionFactory.setVirtualHost("/"); Connection connection = connectionFactory.newConnection();
Channel channel = connection.createChannel(); String exchange = "test_dlx_exchange";
String routingKey = "dlx.save"; String msg = "Hello RabbitMQ DLX Message"; for(int i =0; i<1; i ++){ AMQP.BasicProperties properties = new AMQP.BasicProperties.Builder()
.deliveryMode(2)
.contentEncoding("UTF-8")
.expiration("10000")
.build();
channel.basicPublish(exchange, routingKey, true, properties, msg.getBytes());
} }
}

谢谢观看!!!

RabbitMQ之消息模式(下)的更多相关文章

  1. RabbitMQ之消息模式简单易懂,超详细分享~~~

    前言 上一篇对RabbitMQ的流程和相关的理论进行初步的概述,如果小伙伴之前对消息队列不是很了解,那么在看理论时会有些困惑,这里以消息模式为切入点,结合理论细节和代码实践的方式一起来学习. 正文 常 ...

  2. RabbitMQ之消息模式2

    消费端限流 什么是消费端的限流? 假设一个场景,首先,我们RabbitMQ服务器有上万条未处理的消息,我们随便打开一个消费者客户端,会出现下面情况: 巨量的消息瞬间全部推送过来,但是我们单个客户端无法 ...

  3. RabbitMQ之消息模式

    目的: 消息如何保证100%的投递 幂等性概念 Confirm确认消息 Return返回消息 自定义消费者 前言: 想必知道消息中间件RabbitMQ的小伙伴,对于引入中间件的好处可以起到抗高并发,削 ...

  4. RabbitMQ之消息模式1

    消息100%的投递 消息如何保障100%的投递成功? 什么是生产端的可靠性投递? 保障消息的成功发出 保障MQ节点的成功接收 发送端收到MQ节点(Broker)确认应答 完善的消息进行补偿机制 BAT ...

  5. 解决spring boot在RabbitMQ堆积消息情况下无法启动问题

    最近遇到一个问题,服务站点上线之前,先去新建需要的rabbitmq并绑定关系,此时 如果发送消息方运行, 那边会造成新建的q消息部分堆积得不到及时消费 那么问题来了? 在消息堆积情况下,服务站点无法启 ...

  6. RabbitMQ入门-消息订阅模式

    消息派发 上篇<RabbitMQ入门-消息派发那些事儿>发布之后,收了不少反馈,其中问的最多的还是有关消息确认以及超时等场景的处理. 楼主,有遇到消费者后台进程不在,但consumer连接 ...

  7. simple模式下rabbitmq的代码

    simple模式代码 package RabbitMQ import ( "fmt" "github.com/streadway/amqp" "log ...

  8. [老老实实学WCF] 第十篇 消息通信模式(下) 双工

    老老实实学WCF 第十篇 消息通信模式(下) 双工 在前一篇的学习中,我们了解了单向和请求/应答这两种消息通信模式.我们知道可以通过配置操作协定的IsOneWay属性来改变模式.在这一篇中我们来研究双 ...

  9. RabbitMQ分布式消息队列服务器(一、Windows下安装和部署)

    RabbitMQ消息队列服务器在Windows下的安装和部署-> 一.Erlang语言环境的搭建 RabbitMQ开源消息队列服务是使用Erlang语言开发的,因此我们要使用他就必须先进行Erl ...

随机推荐

  1. 怎么把ubuntu升级到最新版本

    首先是Ctrl+Alt+T 打开终端,然后在终端中输入指令(更新资源) sudo apt-get update 接着是对软件进行升级.(这是一个漫长的过程,需要下载资源) sudo apt-get u ...

  2. 【转】Impala 中的 Invalidate Metadata 和 Refresh

    前言Impala采用了比较奇葩的多个impalad同时提供服务的方式,并且它会由catalogd缓存全部元数据,再通过statestored完成每一次的元数据的更新到impalad节点上,Impala ...

  3. yum 安装,可以list,但是无法安装Error downloading packages: 。。。。 No such file or directory

    yum 安装,可以list,但是无法安装Error downloading packages: .... No such file or directory # yum install nano Lo ...

  4. Spring域属性和代理模式

    一.域属性 好处:大幅度减少Spring配置 坏处:依赖不能明确管理,可能会有多个bean同时符合注入规则.没有清晰的依赖关系. 1,byName 根据属性名自动装配.此选项将检查容器并根据名字查找 ...

  5. Linux后台运行和关闭程序、查看后台任务

    fg.bg.jobs.&.ctrl+z   1.&    (最经常被用到)     这个用在一个命令的最后,可以把这个命令放到后台执行   2.ctrl + z     可以将一个正在 ...

  6. 查看Linux机器的外网IP

    curl icanhazip.comcurl ifconfig.mecurl curlmyip.comcurl ip.appspot.comcurl ipinfo.io/ipcurl ipecho.n ...

  7. android常见错误之 No resource found that matches the given name

    新手上路,还希望大神多多照顾,刚自学android,遇到很多困难.其中就有这个问题,不知道你们遇到过没有,反正我是很头痛. No resource found that matches the giv ...

  8. activeMQ 的启动 停止 查看状态

    1 启动 : 进入到activeMQ 的 bin 目录,执行   ./activemq start  开启 ,如下: 2  查看activeMQ 是不是启动的状态, ./activemq  statu ...

  9. Linux(环境篇):系统搭建本地FTP后,无法登录(331 Please specify the password.)问题解决

    首先 Linux 搭建ftp,开放21端口.(省略...) 你可能会遇到以下问题:错误 SELinux is disabled 解决: setenforce: SELinux is disabled ...

  10. 【spring源码学习】spring的事务管理源码学习

    一.抽象概念 1.事务管理器 接口:org.springframework.transaction.PlatformTransactionManager 实现类:org.springframework ...