rabiitmq消息模式二
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；
自定义消费端代码
package com.huang.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;
/**
* @auther 宇晨
* @site www.cnblogs.com/bf6rc9qu/
* @company
* @create 2019-12-28 16:13
*/
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.huang.rabbitmqapi.limit;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory;
/**
* @auther 宇晨
* @site www.cnblogs.com/bf6rc9qu/
* @company
* @create 2019-12-28 16:17
*/
public class Consumer {
public static void main(String[] args) throws Exception {
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.188.131");
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));
}
}提供方代码
package com.huang.rabbitmqapi.limit;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory;
/**
* @auther 宇晨
* @site www.cnblogs.com/bf6rc9qu/
* @company
* @create 2019-12-28 17:00
*/
public class Producer {
public static void main(String[] args) throws Exception {
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.188.131");
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());
}
}
}
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
消费端重回队列是为了对没有处理成功的消息，把消息重新回递给Broker！
一般我们在实际应用中，都会关闭重回队列，也就是设置为False；因为重回队列消息有很大概率依然会处理失败！
自定义消费者代码
package com.huang.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;
/**
* @auther 宇晨
* @site www.cnblogs.com/bf6rc9qu/
* @company
* @create 2019-12-28 17:03
*/
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);
}
}
}消费者代码
package com.huang.rabbitmqapi.ack;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory;
/**
* @auther 宇晨
* @site www.cnblogs.com/bf6rc9qu/
* @company
* @create 2019-12-28 17:05
*/
public class Consumer {
public static void main(String[] args) throws Exception {
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.188.131");
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));
}
}生产者代码
package com.huang.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;
/**
* @auther 宇晨
* @site www.cnblogs.com/bf6rc9qu/
* @company
* @create 2019-12-28 17:07
*/
public class Producer {
public static void main(String[] args) throws Exception {
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.188.131");
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());
}
}
}
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.huang.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;
/**
* @auther 宇晨
* @site www.cnblogs.com/bf6rc9qu/
* @company
* @create 2019-12-28 17:05
*/
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("192.168.188.131");
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.huang.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;
/**
* @auther 宇晨
* @site www.cnblogs.com/bf6rc9qu/
* @company
* @create 2019-12-28 17:05
*/
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("192.168.188.131");
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();
}
}
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！
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