4、Work-Queue

Work Queues

• using the Java Client

• 

• In the first tutorial we wrote programs to send and receive messages from a named queue. In this one we'll create a Work Queue that will be used to distribute time-consuming tasks among multiple workers.
• The main idea behind Work Queues (aka: Task Queues) is to avoid doing a resource-intensive task immediately and having to wait for it to complete. Instead we schedule the task to be done later.We encapsulate a task as a message and send it to a queue.A worker process running in the background will pop the tasks and eventually execute the job.When you run many workers the tasks will be shared between them.

• This concept is especially useful in web applications where it's impossible to handle a complex task during a short HTTP request window.

  Preparation

• In the previous part of this tutorial we sent a message containing "Hello World!". Now we'll be sending strings that stand for complex tasks.We don't have a real-world task, like images to be resized or pdf files to be rendered, so let's fake it by just pretending we're busy - by using the Thread.sleep() function.We'll take the number of dots in the string as its complexity; every dot will account for one second of "work". For example, a fake task described by Hello... will take three seconds.
• We will slightly modify the Send.java code from our previous example, to allow arbitrary messages to be sent from the command line.This program will schedule tasks to our work queue, so let's name it NewTask.java:

• public class NewTask {
  
  private static final String TASK_QUEUE_NAME = "task_queue";
  
  public static void main(String[] argv) throws Exception {
      ConnectionFactory factory = new ConnectionFactory();
      factory.setHost("localhost");
      Connection connection = factory.newConnection();
      Channel channel = connection.createChannel();
  
      channel.queueDeclare(TASK_QUEUE_NAME, true, false, false, null);
  
      String message="message";
      //String message = getMessage(argv);
      for (int i=0;i<5;i++) {
          message+=".";
          channel.basicPublish("", TASK_QUEUE_NAME,
                  MessageProperties.PERSISTENT_TEXT_PLAIN,
                  message.getBytes("UTF-8"));
          System.out.println(" [x] Sent '" + message + "'");
      }
      channel.close();
      connection.close();
  }

• Our old Recv.java program also requires some changes: it needs to fake a second of work for every dot in the message body. It will handle delivered messages and perform the task, so let's call it Worker.java:

  • public class Worker {
    private static final String TASK_QUEUE_NAME = "task_queue";
    
    public static void main(String[] argv) throws Exception {
        ConnectionFactory factory = new ConnectionFactory();
        factory.setHost("localhost");
        final Connection connection = factory.newConnection();
        final Channel channel = connection.createChannel();
    
        channel.queueDeclare(TASK_QUEUE_NAME, true, false, false, null);
        System.out.println(" [*] Waiting for messages. To exit press CTRL+C");
    
        channel.basicQos(1);
    
        final Consumer consumer = new DefaultConsumer(channel) {
            @Override
            public void handleDelivery(String consumerTag, Envelope envelope, AMQP.BasicProperties properties, byte[] body) throws IOException {
                String message = new String(body, "UTF-8");
    
                System.out.println(" [x] Received '" + message + "'");
                try {
                    doWork(message);
                } finally {
                    System.out.println(" [x] Done");
                    //channel.basicAck(envelope.getDeliveryTag(), false);
                }
            }
        };
        boolean autoAck = true; // acknowledgment is covered below
        channel.basicConsume(TASK_QUEUE_NAME, autoAck, consumer);
    }
    
    private static void doWork(String task) {
        for (char ch : task.toCharArray()) {
            if (ch == '.') {
                try {
                    Thread.sleep(10000);
                } catch (InterruptedException _ignored) {
                    Thread.currentThread().interrupt();
                }
            }
        }
    }
    }

• result:
  

  

  

  Round-robin dispatching循环分发

• One of the advantages of using a Task Queue is the ability to easily parallelise work.If we are building up a backlog of work,we can just add more workers and that way,scale easily.
• First,run two worker instances at the same time.
• Sencond,publish new tasks.
• 结果如上图。

• By default，RabbitMQ will send each message to the next consumer,in sequence.On average every consumer will get the same number of messages.This way of distributing message is called round-robin.

  Message acknowledgment

• Doing a task can take a few seconds.You may wonder what happens if one of the consumers starts a long task and dies with it only partly done.With our current code,once RabbitMQ delivers a message to the costomer it immediately marks it for detetion.In this case ,if you kill a worker we will lose the message it was just processing.We'll also lose all the messsages that were dispatched to this particular worker but were not yet handled.
• But we don't want to lose any tasks.If a worker dies,we'd like the task to be delivered to another workere.
• In order to make sure a message is never lost.RabbitMQ supports message acknowledgments.An ack is sent back by the consumer to tell RabbitMQ that a particular message has been received,processed and that RabbitMQ and that RabbitMQ is free to delete it.
• If a consumer dies(its channel is closed,connection is closed,or TCP connection is lost) without sending an ack.RabbitMQ will understand that a message wasn't processed fully and re-queue it.If there are other consumers online at the same time ,it will then quickly redeliver it to another consumer.That way you can be sure that no message is lost,even if workers occasionally die.
• There aren't any message timeouts;RabbitMQ will redeliver the message when the consumer dies.It's fine even if processing a message takes a very,very long time .
• Manual message acknowledgments are turned on by default .In previous examples we explicitly turned them off via the autoAck-true flag.It's time to set this flag to false and send a proper acknowledgment form the worker,once we're done with a task.

• public static void main(String[] argv) throws Exception {
      ConnectionFactory factory = new ConnectionFactory();
      factory.setHost("localhost");
      final Connection connection = factory.newConnection();
      final Channel channel = connection.createChannel();
  
      channel.queueDeclare(TASK_QUEUE_NAME, true, false, false, null);
      System.out.println(" [*] Waiting for messages. To exit press CTRL+C");
  
      channel.basicQos(1);
  
      final Consumer consumer = new DefaultConsumer(channel) {
          @Override
          public void handleDelivery(String consumerTag, Envelope envelope, AMQP.BasicProperties properties, byte[] body) throws IOException {
              String message = new String(body, "UTF-8");
  
              System.out.println(" [x] Received '" + message + "'");
              try {
                  doWork(message);
              } finally {
                  System.out.println(" [x] Done");
                  channel.basicAck(envelope.getDeliveryTag(), false);
              }
          }
      };
      //boolean autoAck = true; // acknowledgment is covered below
      channel.basicConsume(TASK_QUEUE_NAME, false, consumer);
  }

• Using this code we can be sure that even if you kill a worker while it processing a message,nothing will be lost.Soon after the worker dies all unacknowledged message will be redelivered.
• Acknowledgment must be sent on same channel the delivery it is for was received on.Attempts to acknowledgment using a different channel will result in a channel-level protocol exception..
  • Forgotten acknowledgments

  • It's a common mistake to miss the basicAck .It's an easy error,but the consequences are serious.Messages will be redelivered when your client quits,but RabbitMQ will eat more and more memory as it won't be able to release any unacked messages.

    Message durability

• We have learned how to make sure that even if the consumer dies,the task isn't lost.But our tasks will still be lost if RabbitMQ server stops.
• When RabbitMQ quits or crashs it will forget the queues and messages unless you tell it not to.Two things are required to make sure that messages aren't lost:we need to mark both the queue and messages as durable.
  • First,we need to make sure that RabbitMQ will nerver lose our queue .In order to do so,we need to declare it as durable:

  • boolean durable = true;
    channel.queueDeclare("hello", durable, false, false, null);

  • Although this command is correct by itself ,it won't work in our present setup.That's because we've already defined a queue called 'hello' which is not durable.RabbitMQ doesn't allow you to redefine an existing queue with different parameters and will return an error to any programs that tries to do that.But there is a quick workaround -Let's declare a queue with different name,for example task_queue.
  • This queueDeclare change needs to be applied to both the producer and consumer code .
  • As this point we're sure that the task_queue queue won't be lost even if RabbitMQ restarts.Now we need to mark our messages as persistent-by setting MessageProperties to the value PERSISTENT_TEXT_PLAIN.

  • import com.rabbitmq.client.MessageProperties;
    
    channel.basicPublish("", "task_queue",
        MessageProperties.PERSISTENT_TEXT_PLAIN,
        message.getBytes());

• Note on message persistence

  • Marking messages as persistent doesn't fully guarantee that a message won't be lost.Although it tells RabbitMQ to save the message to disk,there is still a short time window when RabbitMQ has accepted a message and hasn't saved it yet .Also,RabbitMQ doesn't do fsync(2) for every message it may be just saved to cache and not really written to the disk.The persistence guarantee aren't strong,but it's more than enough for our simple task queue.

    Fair dispatch

• You might have noticed that the dispatching still doesn't work exactly as we want.For example in a situation with two workers,when all odd messages are heavy and even message are light,one worker will be constantly busy and the other one will do hardly any work.Well,RabbitMQ doesn't konw anything that and will still dispatch messages evently.
• This happens because RabbitMQ just dispatches a message when the message enters the queue.It doesn't look at the number of unacknowledged messages for a consumer.It just blindly dispatches every n-th message to the n-th consumer.
• 
• In order to defeat that we can use the basicQos method with the prefetchCount=1 setting.This tells RabbitMQ not to give more than one message to a worker at a time.Or in other words,don't dispatch a new message to a worker until it has processed an acknowledged the previous one.Instead ,it will dispatch it to the next worker that is not still busy.

• int prefetchCount = 1;
  channel.basicQos(prefetchCount);

  总结

• Task Queue
• 循环分发 Round-robin dispatch
• 消息确认
• 消息持久化
  • 队列持久化channel.queueDeclare(...,true,...)声明队列时指定
  • 消息持久化channel.basicPublish(...,MessageProperties.PERSISTENT_TEXT_PLAIN,...)发送消息时通过MessageProperties指定
• 平均分发 fair dispatch (可能导致一个worker busy 另一个free)
  • channel.basicQos(1)//等得到ack时在分发下一条消息