RabbitMQ消息100%可靠性投递的解决方案实现(二)
消费端自定义监听
继承DefaultConsumer，重写handleDelivery()方法
public class Producer {
public static final String MQ_HOST = "192.168.222.101";
public static final String MQ_VHOST = "/";
public static final int MQ_PORT = 5672;
public static void main(String[] args) throws IOException, TimeoutException {
//1. 创建一个ConnectionFactory
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost(MQ_HOST);//配置host
connectionFactory.setPort(MQ_PORT);//配置port
connectionFactory.setVirtualHost(MQ_VHOST);//配置vHost
//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();
String exchange = "test_consumer_exchange";
String routingKey = "consumer.save";
//4. 通过Channel发送数据
String message = "Hello Consumer Message";
for (int i = 0; i < 5; i++) {
channel.basicPublish(exchange,routingKey,null,message.getBytes());
}
}
}
public class Consumer {
public static void main(String[] args) throws Exception {
Connection connection = ConnectionUtil.getConn();
//1. 通过connection创建一个Channel
Channel channel = connection.createChannel();
String exchange = "test_consumer_exchange";
String routingKey = "consumer.save";
String queueName = "test_consumer_queue";
//2. 声明一个exchange
channel.exchangeDeclare(exchange,"topic",true,false,null);
//3. 声明一个队列
channel.queueDeclare(queueName,true,false,false,null);
//4. 绑定
channel.queueBind(queueName,exchange,routingKey);
//5. 创建消费者
QueueingConsumer queueingConsumer = new QueueingConsumer(channel);
//6. 设置Channel
channel.basicConsume(queueName,true,new MyConsumer(channel));
/* //7. 获取消息
之前的方式，很ugly
while (true) {
//nextDelivery 会阻塞直到有消息过来
QueueingConsumer.Delivery delivery = queueingConsumer.nextDelivery();
String message = new String(delivery.getBody());
System.out.println("收到:" + message);
}*/
}
private static 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.out.println("——consume message——");
System.out.println("consumerTag:"+consumerTag);
System.out.println("envelope:"+envelope);
System.out.println("properties:"+properties);
System.out.println("body:"+new String(body));
}
}
}
打印如下：
——consume message——
consumerTag:amq.ctag-DLKq_dy8aYspCTUBrnHTew
envelope:Envelope(deliveryTag=1, redeliver=false, exchange=test_consumer_exchange, routingKey=consumer.save)
properties:#contentHeader(content-type=null, content-encoding=null, headers=null, delivery-mode=null, priority=null, correlation-id=null, reply-to=null, expiration=null, message-id=null, timestamp=null, type=null, user-id=null, app-id=null, cluster-id=null)
body:Hello Consumer Message
——consume message——
consumerTag:amq.ctag-DLKq_dy8aYspCTUBrnHTew
envelope:Envelope(deliveryTag=2, redeliver=false, exchange=test_consumer_exchange, routingKey=consumer.save)
properties:#contentHeader(content-type=null, content-encoding=null, headers=null, delivery-mode=null, priority=null, correlation-id=null, reply-to=null, expiration=null, message-id=null, timestamp=null, type=null, user-id=null, app-id=null, cluster-id=null)
body:Hello Consumer Message
...
消息的限流
消费端的限流：
假设，MQ服务器上有上万条未处理的消息，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，但是单个客户端无法同时处理这么多数据，从而导致服务器崩溃
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(设置autoAck为false)，若一定数量的消息(通过基于consume或channel设置Qos的值)未被确认前，不消费新的消息
void BasicQos(unit prefetchSize,unshort prefetchCount,bool global)
- prefetchSize：0 消费的单条消息的大小限制，0代表不限制
- prefetchCount：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掉，直到有消息ack
- global：true\false true:上面设置应用于channel级别; false:应用于consumer级别
public class Producer {
public static final String MQ_HOST = "192.168.222.101";
public static final String MQ_VHOST = "/";
public static final int MQ_PORT = 5672;
public static void main(String[] args) throws IOException, TimeoutException {
//1. 创建一个ConnectionFactory
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost(MQ_HOST);//配置host
connectionFactory.setPort(MQ_PORT);//配置port
connectionFactory.setVirtualHost(MQ_VHOST);//配置vHost
//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();
String exchange = "test_qos_exchange";
String routingKey = "qos.save";
//4. 通过Channel发送数据
String message = "Hello Qos Message";
for (int i = 0; i < 5; i++) {
channel.basicPublish(exchange,routingKey,null,message.getBytes());
}
}
}
public class Consumer {
public static void main(String[] args) throws Exception {
Connection connection = ConnectionUtil.getConn();
//1. 通过connection创建一个Channel
Channel channel = connection.createChannel();
String exchange = "test_qos_exchange";
String routingKey = "qos.#";
String queueName = "test_qos_queue";
//2. 声明一个exchange
channel.exchangeDeclare(exchange,"topic",true,false,null);
//3. 声明一个队列
channel.queueDeclare(queueName,true,false,false,null);
//4. 绑定
channel.queueBind(queueName,exchange,routingKey);
//5. 创建消费者
QueueingConsumer queueingConsumer = new QueueingConsumer(channel);
//6.限流方式 每次只推3条
channel.basicQos(0,3,false);
//7. 设置Channel autoAck一定要设置为false，才能做限流
channel.basicConsume(queueName,false,new MyConsumer(channel));
}
private static 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.out.println("——consume message——");
System.out.println("consumerTag:"+consumerTag);
System.out.println("envelope:"+envelope);
System.out.println("properties:"+properties);
System.out.println("body:"+new String(body));
// 手动签收
channel.basicAck(envelope.getDeliveryTag(),false);
}
}
}
消费端的ACK与重回队列
消费端可以进行手工ACK和NACK(不确认，表示失败)
- 消费端进行消费时，如果由于业务异常，可以进行日志记录，然后进行补偿
- 如果由于服务器宕机等严重问题，需要手工进行ACK保障消费端消费成功
消费端的重回队列：
对没有处理成功的消息，把消息重新传递给Broker
一般在实际应用中，会关闭重回队列
public class Producer {
public static final String MQ_HOST = "192.168.222.101";
public static final String MQ_VHOST = "/";
public static final int MQ_PORT = 5672;
public static void main(String[] args) throws IOException, TimeoutException {
//1. 创建一个ConnectionFactory
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost(MQ_HOST);//配置host
connectionFactory.setPort(MQ_PORT);//配置port
connectionFactory.setVirtualHost(MQ_VHOST);//配置vHost
//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();
String exchange = "test_ack_exchange";
String routingKey = "ack.save";
//4. 通过Channel发送数据
String message = "Hello Ack Message";
for (int i = 0; i < 5; i++) {
Map headers = new HashMap<>();
headers.put("num",i);
AMQP.BasicProperties properties = new AMQP.BasicProperties().builder()
.deliveryMode(2) //持久化
.contentEncoding("UTF-8")
.headers(headers)
.build();
channel.basicPublish(exchange,routingKey,properties,message.getBytes());
}
}
}
public class Consumer {
public static void main(String[] args) throws Exception {
Connection connection = ConnectionUtil.getConn();
//1. 通过connection创建一个Channel
Channel channel = connection.createChannel();
String exchange = "test_ack_exchange";
String routingKey = "ack.#";
String queueName = "test_ack_queue";
//2. 声明一个exchange
channel.exchangeDeclare(exchange,"topic",true,false,null);
//3. 声明一个队列
channel.queueDeclare(queueName,true,false,false,null);
//4. 绑定
channel.queueBind(queueName,exchange,routingKey);
//5. autoAck = false
channel.basicConsume(queueName,false,new MyConsumer(channel));
}
private static 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.out.println("——consume message——");
System.out.println("body:"+new String(body));
System.out.println("num:" + properties.getHeaders().get("num"));
if ((Integer)properties.getHeaders().get("num") == 0 ) {
//requeue:true表示重新入队，重传
channel.basicNack(envelope.getDeliveryTag(),false,true);
} else {
channel.basicAck(envelope.getDeliveryTag(),false);
}
}
}
}
日志：
...
——consume message——
body:Hello Ack Message
num:0
——consume message——
body:Hello Ack Message
num:0
——consume message——
body:Hello Ack Message
num:0
...
num为0的消息会一直回到MQ队列的最尾端，然后一直循环打印，因为一直无法消费
TTL消息
- 生存时间(Time to Live,TTL)，指的是消息的生成时间
- RabbitMQ支持消息的过期时间，在消息发送时可以进行指定
- 还支持队列的过期时间，从消息入队列开始计时，只要超过了队列的超时时间，那么消息会自动的清除
AMQP.BasicProperties properties = new AMQP.BasicProperties.Builder()
.deliveryMode(2) //2:持久化投递；1:非持久化(未消费的消息重启后就没了)
.contentEncoding("UTF-8")
.expiration("5000")//5s 设置消息的TTL
.headers(headers)
.build();
String message = "Hello";
channel.basicPublish("","testQueue",properties,message.getBytes());
}
队列TTL：
Map args = new HashMap<>();
args.put("x-expires", 1800000); //30分钟
channel.queueDeclare("myqueue", false, false, false, args);
死信队列
- 死信队列(Dead-Letter-Exchange,DLX)
- 利用DLX，当消息在队列中变成死信(
dead message:没有消费者去消费)之后，它能被重新publish到另一个Exchange，这个Exchange就是死信队列 - DLX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
- 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，进而被路由到另一个队列
- 可以监听这个队列中的消息并做相应的处理
消息变成死信的情况
- 消息被拒绝(basic.rejcet/basic.nack)且requeue=false
- 消息TTL过期
- 队列达到最大长度
消息中间件消费到的消息处理失败怎么办？
专门有一个后台线程，监控消费者(如 物流）系统是否正常，能否请求的，不停的监视。
一旦发现消费者系统恢复正常，这个后台线程就从死信队列中取出 消费处理失败的消息，重新执行相应逻辑。
死信队列设置
1.首先要设置死信队列的exchange和queue，然后进行绑定：
- Exchange：dlx.exchange
- Queue：dlx.queue
- RoutingKey：#
2.进行正常声明交换机、队列、绑定，只不过需要在队列上加上一个参数：（consumer里添加）arguments.put("x-dead-letter-exchange","dlx.exchange);
3.消息在过期、requeue、队列达到最大长度时，消息就可以直接路由到死信队列
public class Producer {
public static final String MQ_HOST = "192.168.222.101";
public static final String MQ_VHOST = "/";
public static final int MQ_PORT = 5672;
public static void main(String[] args) throws IOException, TimeoutException {
//1. 创建一个ConnectionFactory
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost(MQ_HOST);//配置host
connectionFactory.setPort(MQ_PORT);//配置port
connectionFactory.setVirtualHost(MQ_VHOST);//配置vHost
//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();
String exchange = "test_dlx_exchange";
String routingKey = "dlx.save";
//4. 通过Channel发送数据
String message = "Hello DLX Message";
AMQP.BasicProperties properties = new AMQP.BasicProperties.Builder()
.deliveryMode(2) //2:持久化投递；1:非持久化(未消费的消息重启后就没了)
.contentEncoding("UTF-8")
.expiration("5000")//5s后如果没有消费端消费，会变成死信
.build();
for (int i = 0; i < 1; i++) {
channel.basicPublish(exchange,routingKey,properties,message.getBytes());
}
}
}
public class Consumer {
public static void main(String[] args) throws Exception {
Connection connection = ConnectionUtil.getConn();
//1. 通过connection创建一个Channel
Channel channel = connection.createChannel();
String exchange = "test_dlx_exchange";
String routingKey = "dlx.#";
String queueName = "test_dlx_queue";
String dlxExchange = "dlx.exchange";
String dlxQueue = "dlx.queue";
//2. 声明一个exchange
channel.exchangeDeclare(exchange,"topic",true,false,null);
Map arguments = new HashMap<>();
//路由失败，重发到dlx.exchange
arguments.put("x-dead-letter-exchange",dlxExchange);
/**
* 声明正常队列
* arguments要设置到声明队列上
*/
channel.queueDeclare(queueName,true,false,false,arguments);
channel.queueBind(queueName,exchange,routingKey);
//进行死信队列的声明
channel.exchangeDeclare(dlxExchange,"topic",true,false,null);
channel.queueDeclare(dlxQueue,true,false,false,null);
channel.queueBind(dlxQueue,dlxExchange,"#");
}
private static 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.out.println("——consume message——");
System.out.println("body:"+new String(body));
}
}
}
先启动Consumer,进行生成队列等操作
接着，为了让消息变成死信，停止Consumer
最后，启动Producer
5秒后，消息没被消费，然后就进去了死信队列(注意死信队列中初始值是1)
转自：RabbitMQ学习——高级特性