RabbitMQ消息的处理

Confirm确认与Return返回消息

Confirm消息确认机制：

消息的确认，是指生产者投递消息后，如果Broker收到消息，则会给我们生产这一个应答。

生产者进行接收应答，用来确定这条消息是否正常的发送到Broker，这种方式也是消息的可靠性投递的核心保障。

确认机制流程图：

如何实现Confirm确认消息？

第一步：在channel上开启确认模式：channel.confirmSelect()

第二步：在channel上添加监听：addConfirmListener，监听成功和失败的返回结果，根据具体的结果对消息进行重新发送、或者记录日志等后续处理。

消费者：

public class Consumer {
	public static void main(String[] args) throws Exception {
		//1 创建ConnectionFactory
		ConnectionFactory connectionFactory = new ConnectionFactory();
		connectionFactory.setHost("101.132.178.134");
		connectionFactory.setPort(5672);
		connectionFactory.setVirtualHost("/");
		
		//2 获取connection
		Connection connection = connectionFactory.newConnection();
		
		//3 通过Connection创建一个新的Channel
		Channel channel = connection.createChannel();
		
		String exchangeName = "test_confirm_exchange";
		String routingKey = "confirm.#";
		String queueName = "test_confirm_queue";
		
		//4 声明交换机和队列 然后进行绑定设置, 最后制定路由Key
		channel.exchangeDeclare(exchangeName, "topic", true);
		channel.queueDeclare(queueName, true, false, false, null);
		channel.queueBind(queueName, exchangeName, routingKey);
		
		//5 创建消费者 
		QueueingConsumer queueingConsumer = new QueueingConsumer(channel);
		channel.basicConsume(queueName, true, queueingConsumer);
		
		while(true){
			Delivery delivery = queueingConsumer.nextDelivery();
			String msg = new String(delivery.getBody());
			System.err.println("消费端: " + msg);
		}
	}
}

生产者

public class Producer {
	public static void main(String[] args) throws Exception {

		//1 创建ConnectionFactory
		ConnectionFactory connectionFactory = new ConnectionFactory();
		connectionFactory.setHost("101.132.178.134");
		connectionFactory.setPort(5672);
		connectionFactory.setVirtualHost("/");
		
		//2 获取C	onnection
		Connection connection = connectionFactory.newConnection();
		
		//3 通过Connection创建一个新的Channel
		Channel channel = connection.createChannel();

		//4 指定我们的消息投递模式: 消息的确认模式 
		channel.confirmSelect();
		
		String exchangeName = "test_confirm_exchange";
		String routingKey = "confirm.save";
		
		//5 发送一条消息
		String msg = "Hello RabbitMQ Send confirm message!";
		channel.basicPublish(exchangeName, routingKey, null, msg.getBytes());
		
		//6 添加一个确认监听
		channel.addConfirmListener(new ConfirmListener() {
			@Override
			public void handleNack(long deliveryTag, boolean multiple) throws IOException {
				System.err.println("-------no ack!-----------");
			}
			@Override
			public void handleAck(long deliveryTag, boolean multiple) throws IOException {
				System.err.println("-------ack!-----------");
			}
		});
	}
}

Return消息机制

Return Listener用于处理一些不可路由的消息

我们的消息生产者，通过指定一个Exchange和Routingkey，把消息送到某一个队列中，然后我们的消费者监听队列，进行消息处理操作。

但是在某些情况下，如果我们在发送消息的时候，当前的exchange不存在或者指定的路由key路由不到，这个时候我们需要监听这种不可达的消息，就要使用return listener。

在基础API中有一个关键的配置项：

Mandatory：如果为true，则监听会接收到路由不可达的消息，然后进行后续处理，如果为false，那么broker端自动删除该消息。（默认false）

public class Consumer {
	public static void main(String[] args) throws Exception {

		ConnectionFactory connectionFactory = new ConnectionFactory();
		connectionFactory.setHost("101.132.178.134");
		connectionFactory.setPort(5672);
		connectionFactory.setVirtualHost("/");
		
		Connection connection = connectionFactory.newConnection();
		Channel channel = connection.createChannel();
		
		String exchangeName = "test_return_exchange";
		String routingKey = "return.#";
		String queueName = "test_return_queue";
		
		channel.exchangeDeclare(exchangeName, "topic", true, false, null);
		channel.queueDeclare(queueName, true, false, false, null);
		channel.queueBind(queueName, exchangeName, routingKey);
		
		QueueingConsumer queueingConsumer = new QueueingConsumer(channel);
		
		channel.basicConsume(queueName, true, queueingConsumer);
		
		while(true){
			Delivery delivery = queueingConsumer.nextDelivery();
			String msg = new String(delivery.getBody());
			System.err.println("消费者: " + msg);
		}
	}
}

public class Producer {
	public static void main(String[] args) throws Exception {
		
		ConnectionFactory connectionFactory = new ConnectionFactory();
		connectionFactory.setHost("101.132.178.134");
		connectionFactory.setPort(5672);
		connectionFactory.setVirtualHost("/");
		
		Connection connection = connectionFactory.newConnection();
		Channel channel = connection.createChannel();
		
		String exchange = "test_return_exchange";
		String routingKey = "return.save";
		String routingKeyError = "abc.save";
		
		String msg = "Hello RabbitMQ Return Message";
		
		
		channel.addReturnListener(new ReturnListener() {
			@Override
			public void handleReturn(int replyCode, String replyText, String exchange,
					String routingKey, AMQP.BasicProperties properties, byte[] body) throws IOException {
				
				System.err.println("---------handle  return----------");
				System.err.println("replyCode: " + replyCode);
				System.err.println("replyText: " + replyText);
				System.err.println("exchange: " + exchange);
				System.err.println("routingKey: " + routingKey);
				System.err.println("properties: " + properties);
				System.err.println("body: " + new String(body));
			}
		});
		
		channel.basicPublish(exchange, routingKeyError, true, null, msg.getBytes());
		//channel.basicPublish(exchange, routingKeyError, true, null, msg.getBytes());
	}
}

RabbitMQ消费端自定义监听

我们一般在代码中编写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,比较low。
使用自定义的Consumer更加的方便，解耦性更强

自定义Consumer：

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));
	}
}

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));
	}
}

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());
		}
	}
}

RabbitMQ消费端限流策略

消费端限流

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。（导致服务器崩溃，线上故障）生产端一次推送几百条数据库，客户端只接收一两条，在高并发的情况下，不能再生产端做限流，只能在消费端处理。

解决方法：

RabbitMQ提供了一种qos（服务质量保证）功能，在非自动确认消息的前提下，如果一定数据的消息（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）；

消费端体现，一次最多能处理多少条消息（基本上为1），限流策略在什么上应用（channel--true，consumer---false）

• prefetchSize：0
• prefetchCount：会告诉RabbitMQ不要同时给一个消费者推送多余n个消息，一旦有n个消息还没有ack，则该consumer将block调，知道有消息ack
• global：truefalse是否将上面设置应用于channel，简单的说就是上面限制是channel级别的还是consumer级别，基本使用false

prefetchSize和global这两项，rabbitmq没有实现，暂不研究
prefetch_count在no_ack=false的情况下生效，在自动应答的情况下两个值不生效

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);
	}
}

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));
	}
}

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());
		}
		
	}
}

RabbitMQ消费端ACK与重回队列机制，TTL，死信队列详解

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，那么我们就需要手工进行ACK保障消费端成功。

消费端重回队列

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

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);
		}
	}
}

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));
	}
}

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());
		}
	}
}

TTL队列/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过时间配置，那么消息会自动的清除

AMQP.BasicProperties properties = new AMQP.BasicProperties.Builder()
					.deliveryMode(2)
					.contentEncoding("UTF-8")
					.expiration("10000")
					.build();

消息10s过期，TTL是队列过期时间

DLX死信队列

DLX，Dead-Letter-Exchange

利用DLX，当消息在一个队列中变成死信之后，它能够被重新publish到另一个exchange，这个exchange就是DLX。

消息变成死信情况：

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

DLX也是一个正常的exchange，和一般的exchange没有区别，他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：

首先要设置死信队列的exchange和queue，并进行绑定，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：arguments.put("x-dead-letter-exchange","dlx.exchange");

这样消息在过期、request、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 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));
	}
}

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));
	}
}

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());
		}
	}
}