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BasicQos(uint prfetchSize,ushort prefetchCount,bool global);
前言
- 自定义消费者
- 消息的限流（防止占用内存过多，节点宕机）
- 消息的ACK与重回队列
- TTL消息
- 死信队列
1. 自定义消费者
1.1 消费端自定义监听
- 我们一般就在代码中编写while循环，进行consumer.nextDelivery方法进行获取下一条消息，然后进行消费处理！
- 但是这种轮训的方式肯定是不好的，代码也比较low。
- 我们使用自定义的Consumer更加的方便，解耦性更加的强，也是在实际工作中最常见的使用方式！
1.2 代码演示
1.2.1 生产者
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("192.168.11.76");
connectionFactory.setPort(5672);
connectionFactory.setVirtualHost("/");
Connection connection = connectionFactory.newConnection();
Channel channel = connection.createChannel();
String exchange = "test_consumer_exchange";
String routingKey = "consumer.save";
String msg = "Hello RabbitMQ Consumer Message";
for(int i =0; i<5; i ++){
channel.basicPublish(exchange, routingKey, true, null, msg.getBytes());
}
}
}
1.2.2 消费者
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory;
import com.rabbitmq.client.QueueingConsumer;
import com.rabbitmq.client.QueueingConsumer.Delivery;
public class Consumer {
public static void main(String[] args) throws Exception {
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.11.76");
connectionFactory.setPort(5672);
connectionFactory.setVirtualHost("/");
Connection connection = connectionFactory.newConnection();
Channel channel = connection.createChannel();
String exchangeName = "test_consumer_exchange";
String routingKey = "consumer.#";
String queueName = "test_consumer_queue";
channel.exchangeDeclare(exchangeName, "topic", true, false, null);
channel.queueDeclare(queueName, true, false, false, null);
channel.queueBind(queueName, exchangeName, routingKey);
channel.basicConsume(queueName, true, new MyConsumer(channel));
}
}
1.2.3 自定义类：MyConsumer
import java.io.IOException;
import com.rabbitmq.client.AMQP;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.DefaultConsumer;
import com.rabbitmq.client.Envelope;
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));
}
}
2. 消费端限流
2.1 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！这个时候很容易导致服务器崩溃，出现故障。
为什么不在生产端进行限流呢？
因为在高并发的情况下，客户量就是非常大，所以很难在生产端做限制。因此我们可以用MQ在消费端做限流。
- 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consume或者channel设置Qos的值）未被确认前，不进行消费新的消息。
- 在限流的情况下，千万不要设置自动签收，要设置为手动签收。
- void BasicQos(uint prfetchSize,ushort prefetchCount,bool global);
参数解释：
- prefetchSize:0
- prefetchCount: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掉，直到有消息ack。
- global: true\false 是否将上面设置应用于channel，简单点说，就是上面限制是channel级别还是consumer级别。
- 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。
BasicQos(uint prfetchSize,ushort prefetchCount,bool global);
- 第一个参数：消息的限制大小，消息多少条。一般不做限制，设置为0
- 第二个参数：一次最多处理多少条，实际工作中设置为1就好
- 第三个参数：限流策略在什么上应用。在RabbitMQ一般有两个应用级别：
- 1.通道channel 2.Consumer级别。一般设置为false，true 表示channel级别，false表示在consumer级别
2.2 代码演示
2.2.1 生产者
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("192.168.11.76");
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());
}
}
}
2.2.2 消费者
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory;
import com.rabbitmq.client.QueueingConsumer;
import com.rabbitmq.client.QueueingConsumer.Delivery;
public class Consumer {
public static void main(String[] args) throws Exception {
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.11.76");
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));
}
}
2.2.3 自定义类：MyConsumer
import java.io.IOException;
import com.rabbitmq.client.AMQP;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.DefaultConsumer;
import com.rabbitmq.client.Envelope;
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);
}
}
4. 消费端ACK与重回队列
4.1 消费端的手工ACK和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，那我们就需要手工进行ACK保障消费端消费成功！
4.2 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，把消息重新传递给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.
4.3 代码演示
4.3.1 生产者
import java.util.HashMap;
import java.util.Map;
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("192.168.11.76");
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());
}
}
}
4.3.2 消费者
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory;
import com.rabbitmq.client.QueueingConsumer;
import com.rabbitmq.client.QueueingConsumer.Delivery;
public class Consumer {
public static void main(String[] args) throws Exception {
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.11.76");
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));
}
}
4.3.3 自定义类：MyConsumer
import java.io.IOException;
import com.rabbitmq.client.AMQP;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.DefaultConsumer;
import com.rabbitmq.client.Envelope;
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) {
channel.basicNack(envelope.getDeliveryTag(), false, true);
} else {
channel.basicAck(envelope.getDeliveryTag(), false);
}
}
}
注意：
- 可以看到重回队列会出现重复消费导致死循环的问题，这时候最好设置重试次数，比如超过三次后，消息还是消费失败，就将消息丢弃。
5. TTL队列/消息
5.1 TTL
- 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，那么消息会自动的清除
5.2 演示
直接通过管控台进行演示
通过管控台创建一个队列
x-max-length 队列的最大大小
x-message-ttl 设置10秒钟，如果消息还没有被消费的话，就会被清除。
生产端设置过期时间
AMQP.BasicProperties properties = new AMQP.BasicProperties.Builder()
.deliveryMode(2)
.contentEncoding("UTF-8")
.expiration("10000")
.headers(headers)
.build();这两个属性并不相同，一个对应的是消息体，一个对应的是队列的过期。
6. 死信队列
6.1 死信队列-概念
- 死信队列：DLX,Dead-Letter-Exchange
- RabbitMQ的死信队里与Exchange息息相关
- 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
- 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，这个特征可以弥补RabbitMQ3.0以前支持的immediate参数的功能。
6.2 代码演示
6.2.0 死信队列设置
- 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！
6.2.1 生产者
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("192.168.11.76");
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());
}
}
}
6.2.2 消费者
import java.util.HashMap;
import java.util.Map;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.Connection;
import com.rabbitmq.client.ConnectionFactory;
import com.rabbitmq.client.QueueingConsumer;
import com.rabbitmq.client.QueueingConsumer.Delivery;
public class Consumer {
public static void main(String[] args) throws Exception {
ConnectionFactory connectionFactory = new ConnectionFactory();
connectionFactory.setHost("192.168.11.76");
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));
}
}
6.2.3 自定义类：MyConsumer
import java.io.IOException;
import com.rabbitmq.client.AMQP;
import com.rabbitmq.client.Channel;
import com.rabbitmq.client.DefaultConsumer;
import com.rabbitmq.client.Envelope;
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));
}
}
- 查看queue
- 可以看到test_dlx_queue多了DLX的标识，表示当队列中出现死信的时候，会将消息发送到死信队列dlx_queue中
- 关闭Consumer，只运行Producer
- 过10秒钟后，消息过期
- 在我们工作中，死信队列非常重要，用于消息没有消费者，处于死信状态。我们可以才用补偿机制。
