openstack nova基础知识——RabbitMQ

nova中各个组件之间的交互是通过“消息队列”来实现的，其中一种实现方法就是使用RabbitMQ，对RabbitMQ的使用，官方文档上有一个非常好的Get Started，由浅及深，结合例子，很容易理解。现在对RabbitMQ的理解，就是利用它可以非常灵活的定制自己想要实现的消息收发机制。

其中，有这样几个角色：producer, consumer, exchange, queue

producer是消息发送者，consumer是消息接受者，中间要通过exchange和queue。producer将消息发送给exchange，exchange决定消息的路由，即决定要将消息发送给哪个queue，然后consumer从queue中取出消息，进行处理，大致流程如下图：

这几个角色当中，我觉得最关键的是这个exchange，它有3种类型：direct, topic, fanout。其中，功能最强大的就是topic，用它完全可以实现direct和fanout的功能。

direct是单条件的路由，即在exchange判断要将消息发送给哪个queue时，判断的依据只能是一个条件;

fanout是广播式的路由，即将消息发送给所有的queue;

topic是多条件的路由，转发消息时，依据的条件是多个，所以只使用topic就可以实现direct和fanout的功能。

上面所说的“条件”，反映到程序中，就是routing_key，这个routing_key出现在两个地方：

    1. 每一个发送的消息都有一个routing_key，表示发送的是一个什么样的消息；

    2. 每一个queue要和exchange绑定，绑定的时候要提供一个routing_key，表示这个queue想要接收什么样的消息。

这样，exchange就可以根据routing_key，来将消息发送到合适的queue中。

基本的思路就这些吧，下面来看一下官方文档上的那由浅及深的六个例子：

（我很喜欢这种风格的文档，整体由浅及深，适合初学者，其次文章没有大量的生僻词汇，而且例子+图片，比较容易懂，更好的是文章还带点小小的幽默，不由得让人汇心一笑，感觉老外做事就是认真细腻，希望自己也能养成这样的风格）

1. Hello World

最简单的情况，发一个消息，接收，打印出来这个消息。

send.py：

#!/usr/bin/env pythonimport pika# 1. Establish a connection with RabbitMQ server.connection = pika.BlockingConnection(pika.ConnectionParameters(               'localhost'))channel = connection.channel()# 2. Create a queue to which the message will be delivered, let's name it 'hello'channel.queue_declare(queue='hello')# 3. Use a default exchange identified by an empty string, which allows us to specify#    exactly to which queue the message should go. The queue name needs to be specified#    in the routing_key parameter:channel.basic_publish(exchange='',                      routing_key='hello',                      body='Hello World!')print " [x] Sent 'Hello World!'"# 4. Close the connectionconnection.close()

recv.py：

#!/usr/bin/env pythonimport pika# 1. Establish a connection with RabbitMQ serverconnection = pika.BlockingConnection(pika.ConnectionParameters(        host='localhost'))channel = connection.channel()# 2. Make sure that the queue exists,run the command as many times as we like, and only one will be created.channel.queue_declare(queue='hello')print ' [*] Waiting for messages. To exit press CTRL+C'# 3. Define a callback function.Whenever we receive a message, #    this callback function is called by the Pika library.def callback(ch, method, properties, body):    print " [x] Received %r" % (body,)# 4. Subscribe the callback function to a queue.#    Tell RabbitMQ that this particular callback function should receive messages from our hello queue.channel.basic_consume(callback,                      queue='hello',                      no_ack=True)# 5. Enter a never-ending loop that waits for data and runs callbacks whenever necessary.channel.start_consuming()

2. 多个consumer

这个例子跟第一个例子基本上一样，只是启动了多个consumer，并且模拟真实情况，即发送的消息使得consumer在短时间内不能完成工作。在这种情况下，多个consumer是如何协调工作的呢？其实，这些都是可以在程序中进行控制的。

send.py

#!/usr/bin/env pythonimport pikaimport sys# 1. Establish a connection with RabbitMQ server.connection = pika.BlockingConnection(pika.ConnectionParameters(               'localhost'))channel = connection.channel()# 2. Create a queue to which the message will be delivered, let's name it 'hello'#    'durable=True' makes the queue persistentchannel.queue_declare(queue='task_queue',durable=True)message=' '.join(sys.argv[1:]) or "Hello World!"# 3. Use a default exchange identified by an empty string, which allows us to specify#    exactly to which queue the message should go. The queue name needs to be specified#    in the routing_key parameter:channel.basic_publish(exchange='',                      routing_key='task_queue',                      body=message,                      properties=pika.BasicProperties(                         delivery_mode = 2, # make message persistent                      ))print " [x] Sent %r" % (message,)# 4. Close the connectionconnection.close()

recv.py:

#!/usr/bin/env pythonimport pikaimport time# 1. Establish a connection with RabbitMQ serverconnection = pika.BlockingConnection(pika.ConnectionParameters(        host='localhost'))channel = connection.channel()# 2. Make sure that the queue exists,run the command as many times as we like, and only one will be created.#    'durable=True' makes the queue persistentchannel.queue_declare(queue='task_queue',durable=True)print ' [*] Waiting for messages. To exit press CTRL+C'# 3. Define a callback function.Whenever we receive a message, #    this callback function is called by the Pika library.##    Send a ack to tell rabbitmq a task is done, then it can release the message.#    If a worker dies, rabbitmq fail to receive the ack, it will redeliver the message to another worker.#    Remember to write the last line code, or rabbitmq will eat more and more memory.def callback(ch, method, properties, body):    print " [x] Received %r" % (body,)    time.sleep(body.count('.'))    print "[x] Done"    ch.basic_ack(delivery_tag = method.delivery_tag) # Fair dispatch: Tell rabbitmq not give a worker more than one messages at a timechannel.basic_qos(prefetch_count=1)# 4. Subscribe the callback function to a queue.#    Tell RabbitMQ that this particular callback function should receive messages from our hello queue.channel.basic_consume(callback,                      queue='task_queue',                      no_ack=False)# turn on the (ack)onwledgment, default is False# 5. Enter a never-ending loop that waits for data and runs callbacks whenever necessary.channel.start_consuming()

3. fanout exchange的例子：

send.py:

#!/usr/bin/env pythonimport pikaimport sysconnection = pika.BlockingConnection(pika.ConnectionParameters(        host='localhost'))channel = connection.channel()# declare a exchange, type is fanout(means broadcast),named 'logs'.# exchange is used to receive messages form producer, and send messages to queue.# there are four exchange types: direct, topic, headers and fanoutchannel.exchange_declare(exchange='logs',                         type='fanout')message = ' '.join(sys.argv[1:]) or "info: Hello World!"channel.basic_publish(exchange='logs',                      routing_key='', #routing_key is '', because 'fanout' exchange will ignore its value.                      body=message)print " [x] Sent %r" % (message,)connection.close()

recv.py:

#!/usr/bin/env pythonimport pikaconnection = pika.BlockingConnection(pika.ConnectionParameters(        host='localhost'))channel = connection.channel()# if a exchange named 'logs' have not declared yet, then declare one, # or just use the existed exchange.channel.exchange_declare(exchange='logs',                         type='fanout')# declare a temporary queue with a random name# 'exclusive=True' flag will delete the queue when the consumer dies.result = channel.queue_declare(exclusive=True)queue_name = result.method.queue# bind the queue to the exchange, to tell the exchange to send messages to our queue.channel.queue_bind(exchange='logs',                   queue=queue_name)print ' [*] Waiting for logs. To exit press CTRL+C'def callback(ch, method, properties, body):    print " [x] %r" % (body,)channel.basic_consume(callback,                      queue=queue_name,                      no_ack=True)channel.start_consuming()

4. direct exchange的例子：

需要注意，一个queue是可以和同一个exchange多次绑定的，每次绑定要用不同的routing_key

send.py:

#!/usr/bin/env pythonimport pikaimport sysconnection = pika.BlockingConnection(pika.ConnectionParameters(        host='localhost'))channel = connection.channel()# declare a exchange, type is direct, named 'logs'.channel.exchange_declare(exchange='direct_logs',                         type='direct')severity = sys.argv[1] if len(sys.argv) > 1 else 'info'message = ' '.join(sys.argv[2:]) or 'Hello World!'# a message is sent to the direct exchange with a routing_key.# a message is identified by the routing_key.channel.basic_publish(exchange='direct_logs',                      routing_key=severity,                      body=message)print " [x] Sent %r:%r" % (severity, message)connection.close()

recv.py:

#!/usr/bin/env pythonimport pikaimport sysconnection = pika.BlockingConnection(pika.ConnectionParameters(        host='localhost'))channel = connection.channel()# declare a direct exchange named 'direct_logs'channel.exchange_declare(exchange='direct_logs',                         type='direct')result = channel.queue_declare(exclusive=True)queue_name = result.method.queueseverities = sys.argv[1:]if not severities:    print >> sys.stderr, "Usage: %s [info] [warning] [error]" % \                         (sys.argv[0],)    sys.exit(1)# Bind the queue to the direct exchange,# 'routing_key' flag tells the direct exchange which kind of message it wants to receive.# A queue can bind multiple times to the same direct exchange with different routing_keys,# which means it wants to receive several kinds of messages.for severity in severities:    channel.queue_bind(exchange='direct_logs',                       queue=queue_name,                       routing_key=severity)print ' [*] Waiting for logs. To exit press CTRL+C'def callback(ch, method, properties, body):    print " [x] %r:%r" % (method.routing_key, body,)channel.basic_consume(callback,                      queue=queue_name,                      no_ack=True)channel.start_consuming()

5. topic exchange的例子

这里的routing_key可以使用一种类似正则表达式的形式，但是特殊字符只能是“*”和“#”，“*”代表一个单词，“#”代表0个或是多个单词。这样发送过来的消息如果符合某个queue的routing_key定义的规则，那么就会转发给这个queue。如下图示例：

send.py:

#!/usr/bin/env pythonimport pikaimport sysconnection = pika.BlockingConnection(pika.ConnectionParameters(        host='localhost'))channel = connection.channel()# declare a exchange, type is topic, named 'topic_logs'.# topic exchange allows to do routing based on multiple criteria.channel.exchange_declare(exchange='topic_logs',                         type='topic')severity = sys.argv[1] if len(sys.argv) > 1 else 'anonymous.info'message = ' '.join(sys.argv[2:]) or 'Hello World!'# a message is sent to the topic exchange with a routing_key.# a message is identified by the routing_key.# the topic routing_key can be like 'topic.host','topic.topic1.topic3', etc# also can use '*'(one word) and '#'(zero or more words) to substitute word(s).channel.basic_publish(exchange='topic_logs',                      routing_key=severity,                      body=message)print " [x] Sent %r:%r" % (severity, message)connection.close()

recv.py:

#!/usr/bin/env pythonimport pikaimport sysconnection = pika.BlockingConnection(pika.ConnectionParameters(        host='localhost'))channel = connection.channel()# declare a topic exchange named 'topic_logs'channel.exchange_declare(exchange='topic_logs',                         type='topic')result = channel.queue_declare(exclusive=True)queue_name = result.method.queuebinding_keys = sys.argv[1:]if not binding_keys:    print >> sys.stderr, "Usage: %s [binding_key]..." % (sys.argv[0],)    sys.exit(1)# Bind the queue to the topic exchange,# 'routing_key' flag tells the topic exchange which kind of message it wants to receive.# A queue can bind multiple times to the same direct exchange with different routing_keys,# which means it wants to receive several kinds of messages.for binding_key in binding_keys:    channel.queue_bind(exchange='topic_logs',                       queue=queue_name,                       routing_key=binding_key)print ' [*] Waiting for logs. To exit press CTRL+C'def callback(ch, method, properties, body):    print " [x] %r:%r" % (method.routing_key, body,)channel.basic_consume(callback,                      queue=queue_name,                      no_ack=True)channel.start_consuming()

6. PRC(Remote Procedure Call，远程过程调用)

目前对这个的理解就是发送一个消息，然后还要得到一个结果，即消息要走一个来回。如下图所示：

client.py:

#!/usr/bin/env pythonimport pikaimport uuidclass FibonacciRpcClient(object):    def __init__(self):        self.connection = pika.BlockingConnection(pika.ConnectionParameters(                host='localhost'))        self.channel = self.connection.channel()        result = self.channel.queue_declare(exclusive=True)        self.callback_queue = result.method.queue        self.channel.basic_consume(self.on_response, no_ack=True,                                   queue=self.callback_queue)    def on_response(self, ch, method, props, body):        if self.corr_id == props.correlation_id:            self.response = body    def call(self, n):        self.response = None        self.corr_id = str(uuid.uuid4())        self.channel.basic_publish(exchange='',                                   routing_key='rpc_queue',                                   properties=pika.BasicProperties(                                         reply_to = self.callback_queue,                                         correlation_id = self.corr_id,                                         ),                                   body=str(n))        while self.response is None:            self.connection.process_data_events()        return int(self.response)fibonacci_rpc = FibonacciRpcClient()print " [x] Requesting fib(30)"response = fibonacci_rpc.call(30)print " [.] Got %r" % (response,)

server.py:

#!/usr/bin/env pythonimport pikaconnection = pika.BlockingConnection(pika.ConnectionParameters(        host='localhost'))channel = connection.channel()channel.queue_declare(queue='rpc_queue')def fib(n):    if n == 0:        return 0    elif n == 1:        return 1    else:        return fib(n-1) + fib(n-2)def on_request(ch, method, props, body):    n = int(body)    print " [.] fib(%s)"  % (n,)    response = fib(n)    ch.basic_publish(exchange='',                     routing_key=props.reply_to,                     properties=pika.BasicProperties(correlation_id = \                                                     props.correlation_id),                     body=str(response))    ch.basic_ack(delivery_tag = method.delivery_tag)channel.basic_qos(prefetch_count=1)channel.basic_consume(on_request, queue='rpc_queue')print " [x] Awaiting RPC requests"channel.start_consuming()

几个RabbitMQ相关的命令：

1. 查看RabbitMQ中有多少个queue，以及每个queue中有多少个消息：$ sudo rabbitmqctl list_queues2. 查看RabbitMQ中exchange的情况：$ sudo rabbitmqctl list_exchanges3. 查看RabbitMQ中exchange和queue绑定情况：$  sudo   rabbitmqctl list_bindings4. 启动/停止RabbitMQ:$  sudo   invoke-rc.d rabbitmq-server stop/start/etc.