Rabbitmq整理

一 消息队列介绍

1.1 介绍

消息队列就是基础数据结构中的“先进先出”的一种数据机构。想一下，生活中买东西，需要排队，先排的人先买消费，就是典型的“先进先出”

1.2 MQ解决什么问题

MQ是一直存在，不过随着微服务架构的流行，成了解决微服务之间问题的常用工具。

应用解耦

以电商应用为例，应用中有订单系统、库存系统、物流系统、支付系统。用户创建订单后，如果耦合调用库存系统、物流系统、支付系统，任何一个子系统出了故障，都会造成下单操作异常。

当转变成基于消息队列的方式后，系统间调用的问题会减少很多，比如物流系统因为发生故障，需要几分钟来修复。在这几分钟的时间里，物流系统要处理的内存被缓存在消息队列中，用户的下单操作可以正常完成。当物流系统恢复后，继续处理订单信息即可，中单用户感受不到物流系统的故障。提升系统的可用性

流量消峰

举个栗子，如果订单系统最多能处理一万次订单，这个处理能力应付正常时段的下单时绰绰有余，正常时段我们下单一秒后就能返回结果。但是在高峰期，如果有两万次下单操作系统是处理不了的，只能限制订单超过一万后不允许用户下单。

使用消息队列做缓冲，我们可以取消这个限制，把一秒内下的订单分散成一段时间来处理，这事有些用户可能在下单十几秒后才能收到下单成功的操作，但是比不能下单的体验要好。

消息分发

多个服务队数据感兴趣，只需要监听同一类消息即可处理。

例如A产生数据，B对数据感兴趣。如果没有消息的队列A每次处理完需要调用一下B服务。过了一段时间C对数据也感性，A就需要改代码，调用B服务，调用C服务。只要有服务需要，A服务都要改动代码。很不方便。

有了消息队列后，A只管发送一次消息，B对消息感兴趣，只需要监听消息。C感兴趣，C也去监听消息。A服务作为基础服务完全不需要有改动

异步消息

有些服务间调用是异步的，例如A调用B，B需要花费很长时间执行，但是A需要知道B什么时候可以执行完，以前一般有两种方式，A过一段时间去调用B的查询api查询。或者A提供一个callback api，B执行完之后调用api通知A服务。这两种方式都不是很优雅

使用消息总线，可以很方便解决这个问题，A调用B服务后，只需要监听B处理完成的消息，当B处理完成后，会发送一条消息给MQ，MQ会将此消息转发给A服务。

这样A服务既不用循环调用B的查询api，也不用提供callback api。同样B服务也不用做这些操作。A服务还能及时的得到异步处理成功的消息

1.3 常见消息队列及比较

结论:

Kafka在于分布式架构，RabbitMQ基于AMQP协议来实现，RocketMQ/思路来源于kafka，改成了主从结构，在事务性可靠性方面做了优化。广泛来说，电商、金融等对事务性要求很高的，可以考虑RabbitMQ和RocketMQ，对性能要求高的可考虑Kafka

二 Rabbitmq安装

官网：https://www.rabbitmq.com/getstarted.html

2.1 服务端原生安装

# 安装配置epel源
# 安装erlang
yum -y install erlang
# 安装RabbitMQ
yum -y install rabbitmq-server

2.2 服务端Docker安装

docker pull rabbitmq:management
docker run -di --name Myrabbitmq -e RABBITMQ_DEFAULT_USER=admin -e RABBITMQ_DEFAULT_PASS=admin -p 15672:15672 -p 5672:5672 rabbitmq:management

2.3 客户端安装

pip3 install pika

2.4 设置用户和密码

rabbitmqctl add_user lqz 123
# 设置用户为administrator角色
rabbitmqctl set_user_tags lqz administrator
# 设置权限
rabbitmqctl set_permissions -p "/" root ".*" ".*" ".*"

# 然后重启rabbiMQ服务
systemctl reatart rabbitmq-server
 
# 然后可以使用刚才的用户远程连接rabbitmq server了。

三 基于Queue实现生产者消费者模型

import Queue
import threading

message = Queue.Queue(10)

def producer(i):
    while True:
        message.put(i)

def consumer(i):
    while True:
        msg = message.get()

for i in range(12):
    t = threading.Thread(target=producer, args=(i,))
    t.start()

for i in range(10):
    t = threading.Thread(target=consumer, args=(i,))
    t.start()

四 基本使用（生产者消费者模型）

对于RabbitMQ来说，生产和消费不再针对内存里的一个Queue对象，而是某台服务器上的RabbitMQ Server实现的消息队列。

生产者

import pika
# 无密码
# connection = pika.BlockingConnection(pika.ConnectionParameters('127.0.0.1'))

# 有密码
credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()
# 声明一个队列(创建一个队列)
channel.queue_declare(queue='lqz')

channel.basic_publish(exchange='',
                      routing_key='lqz', # 消息队列名称
                      body='hello world')
connection.close()

消费者

import pika

credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()

# 声明一个队列(创建一个队列)
channel.queue_declare(queue='lqz')

def callback(ch, method, properties, body):
    print("消费者接受到了任务: %r" % body)

channel.basic_consume(queue='lqz',on_message_callback=callback,auto_ack=True)

channel.start_consuming()

五 消息安全之ack

生产者

import pika
# 无密码
# connection = pika.BlockingConnection(pika.ConnectionParameters('127.0.0.1'))

# 有密码
credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()
# 声明一个队列(创建一个队列)
channel.queue_declare(queue='lqz')

channel.basic_publish(exchange='',
                      routing_key='lqz', # 消息队列名称
                      body='hello world')
connection.close()

消费者

import pika

credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()

# 声明一个队列(创建一个队列)
channel.queue_declare(queue='lqz')

def callback(ch, method, properties, body):
    print("消费者接受到了任务: %r" % body)
    # 通知服务端，消息取走了，如果auto_ack=False，不加下面，消息会一直存在
    # ch.basic_ack(delivery_tag=method.delivery_tag)

channel.basic_consume(queue='lqz',on_message_callback=callback,auto_ack=False)

channel.start_consuming()

六 消息安全之durable持久化

生产者

import pika
# 无密码
# connection = pika.BlockingConnection(pika.ConnectionParameters('127.0.0.1'))

# 有密码
credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()
# 声明一个队列(创建一个队列),durable=True支持持久化，队列必须是新的才可以
channel.queue_declare(queue='lqz1',durable=True)

channel.basic_publish(exchange='',
                      routing_key='lqz1', # 消息队列名称
                      body='111',
                      properties=pika.BasicProperties(
                          delivery_mode=2,  # make message persistent,消息也持久化
                      )
                      )
connection.close()

消费者

import pika

credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()

# 声明一个队列(创建一个队列)
channel.queue_declare(queue='lqz1')

def callback(ch, method, properties, body):
    print("消费者接受到了任务: %r" % body)
    # 通知服务端，消息取走了，如果auto_ack=False，不加下面，消息会一直存在
    # ch.basic_ack(delivery_tag=method.delivery_tag)

channel.basic_consume(queue='lqz1',on_message_callback=callback,auto_ack=False)

channel.start_consuming()

七 闲置消费

正常情况如果有多个消费者，是按照顺序第一个消息给第一个消费者，第二个消息给第二个消费者

但是可能第一个消息的消费者处理消息很耗时，一直没结束，就可以让第二个消费者优先获得闲置的消息

生产者

import pika
# 无密码
# connection = pika.BlockingConnection(pika.ConnectionParameters('127.0.0.1'))

# 有密码
credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()
# 声明一个队列(创建一个队列),durable=True支持持久化，队列必须是新的才可以
channel.queue_declare(queue='lqz123',durable=True)

channel.basic_publish(exchange='',
                      routing_key='lqz123', # 消息队列名称
                      body='111',
                      properties=pika.BasicProperties(
                          delivery_mode=2,  # make message persistent,消息也持久化
                      )
                      )
connection.close()

消费者

import pika

credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()

# 声明一个队列(创建一个队列)
# channel.queue_declare(queue='lqz123')

def callback(ch, method, properties, body):
    print("消费者接受到了任务: %r" % body)
    # 通知服务端，消息取走了，如果auto_ack=False，不加下面，消息会一直存在
    ch.basic_ack(delivery_tag=method.delivery_tag)

channel.basic_qos(prefetch_count=1) #####就只有这一句话 谁闲置谁获取，没必要按照顺序一个一个来
channel.basic_consume(queue='lqz123',on_message_callback=callback,auto_ack=False)

channel.start_consuming()

八 发布订阅

发布者

import pika
credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()

channel.exchange_declare(exchange='m1',exchange_type='fanout')

channel.basic_publish(exchange='m1',
                      routing_key='',
                      body='lqz nb')

connection.close()

订阅者(启动几次订阅者会生成几个队列)

import pika

credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()

# exchange='m1',exchange(秘书)的名称
# exchange_type='fanout' , 秘书工作方式将消息发送给所有的队列
channel.exchange_declare(exchange='m1',exchange_type='fanout')

# 随机生成一个队列
result = channel.queue_declare(queue='',exclusive=True)
queue_name = result.method.queue
print(queue_name)
# 让exchange和queque进行绑定.
channel.queue_bind(exchange='m1',queue=queue_name)


def callback(ch, method, properties, body):
    print("消费者接受到了任务: %r" % body)

channel.basic_consume(queue=queue_name,on_message_callback=callback,auto_ack=True)

channel.start_consuming()

九 发布订阅高级之Routing(按关键字匹配)

发布者

import pika
credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()

channel.exchange_declare(exchange='m2',exchange_type='direct')

channel.basic_publish(exchange='m2',
                      routing_key='bnb', # 多个关键字，指定routing_key
                      body='lqz nb')

connection.close()

订阅者1

import pika

credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()

# exchange='m1',exchange(秘书)的名称
# exchange_type='direct' , 秘书工作方式将消息发送给不同的关键字
channel.exchange_declare(exchange='m2',exchange_type='direct')

# 随机生成一个队列
result = channel.queue_declare(queue='',exclusive=True)
queue_name = result.method.queue
print(queue_name)
# 让exchange和queque进行绑定.
channel.queue_bind(exchange='m2',queue=queue_name,routing_key='nb')
channel.queue_bind(exchange='m2',queue=queue_name,routing_key='bnb')


def callback(ch, method, properties, body):
    print("消费者接受到了任务: %r" % body)

channel.basic_consume(queue=queue_name,on_message_callback=callback,auto_ack=True)

channel.start_consuming()

订阅者2

import pika

credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()

# exchange='m1',exchange(秘书)的名称
# exchange_type='direct' , 秘书工作方式将消息发送给不同的关键字
channel.exchange_declare(exchange='m2',exchange_type='direct')

# 随机生成一个队列
result = channel.queue_declare(queue='',exclusive=True)
queue_name = result.method.queue
print(queue_name)
# 让exchange和queque进行绑定.
channel.queue_bind(exchange='m2',queue=queue_name,routing_key='nb')



def callback(ch, method, properties, body):
    print("消费者接受到了任务: %r" % body)

channel.basic_consume(queue=queue_name,on_message_callback=callback,auto_ack=True)

channel.start_consuming()

九 发布订阅高级之Topic(按关键字模糊匹配)

发布者

import pika
credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()

channel.exchange_declare(exchange='m3',exchange_type='topic')

channel.basic_publish(exchange='m3',
                      # routing_key='lqz.handsome', #都能收到
                      routing_key='lqz.handsome.xx', #只有lqz.#能收到
                      body='lqz nb')

connection.close()

订阅者1

*只能加一个单词

#可以加任意单词字符

import pika

credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()

# exchange='m1',exchange(秘书)的名称
# exchange_type='direct' , 秘书工作方式将消息发送给不同的关键字
channel.exchange_declare(exchange='m3',exchange_type='topic')

# 随机生成一个队列
result = channel.queue_declare(queue='',exclusive=True)
queue_name = result.method.queue
print(queue_name)
# 让exchange和queque进行绑定.
channel.queue_bind(exchange='m3',queue=queue_name,routing_key='lqz.#')



def callback(ch, method, properties, body):
    print("消费者接受到了任务: %r" % body)

channel.basic_consume(queue=queue_name,on_message_callback=callback,auto_ack=True)

channel.start_consuming()

订阅者2

import pika

credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()

# exchange='m1',exchange(秘书)的名称
# exchange_type='topic' , 模糊匹配
channel.exchange_declare(exchange='m3',exchange_type='topic')

# 随机生成一个队列
result = channel.queue_declare(queue='',exclusive=True)
queue_name = result.method.queue
print(queue_name)
# 让exchange和queque进行绑定.
channel.queue_bind(exchange='m3',queue=queue_name,routing_key='lqz.*')


def callback(ch, method, properties, body):
  	queue_name = result.method.queue # 发送的routing_key是什么
    print("消费者接受到了任务: %r" % body)

channel.basic_consume(queue=queue_name,on_message_callback=callback,auto_ack=True)

channel.start_consuming()

十 基于rabbitmq实现rpc

服务端

import pika
credentials = pika.PlainCredentials("admin","admin")
connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166',credentials=credentials))
channel = connection.channel()

# 起翰监听任务队列
channel.queue_declare(queue='rpc_queue')

def on_request(ch, method, props, body):
    n = int(body)
    response = n + 100
    # props.reply_to  要放结果的队列.
    # props.correlation_id  任务
    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( queue='rpc_queue',on_message_callback=on_request,)
channel.start_consuming()

客户端

import pika
import uuid

class FibonacciRpcClient(object):
    def __init__(self):
        credentials = pika.PlainCredentials("admin", "admin")
        self.connection = pika.BlockingConnection(pika.ConnectionParameters('101.133.225.166', credentials=credentials))
        self.channel = self.connection.channel()

        # 随机生成一个消息队列(用于接收结果)
        result = self.channel.queue_declare(queue='',exclusive=True)
        self.callback_queue = result.method.queue

        # 监听消息队列中是否有值返回,如果有值则执行 on_response 函数(一旦有结果,则执行on_response)
        self.channel.basic_consume(queue=self.callback_queue,on_message_callback=self.on_response, auto_ack=True)

    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())

        # 客户端 给 服务端 发送一个任务:  任务id = corr_id / 任务内容 = '30' / 用于接收结果的队列名称
        self.channel.basic_publish(exchange='',
                                   routing_key='rpc_queue', # 服务端接收任务的队列名称
                                   properties=pika.BasicProperties(
                                         reply_to = self.callback_queue, # 用于接收结果的队列
                                         correlation_id = self.corr_id, # 任务ID
                                         ),
                                   body=str(n))
        while self.response is None:
            self.connection.process_data_events()

        return self.response

fibonacci_rpc = FibonacciRpcClient()

response = fibonacci_rpc.call(50)
print('返回结果:',response)