RabbitMQ高可用集群配置

1、安装RabbitMQ

1）下载和安装erlang

下载erlang

wget http://www.rabbitmq.com/releases/erlang/erlang-18.1-1.el6.x86_64.rpm

安装erlang，root用户使用rpm安装

rpm -ihv erlang-18.1-1.el6.x86_64.rpm

2）下载和安装RabbitMQ

下载RabbitMQ

wget https://github.com/rabbitmq/rabbitmq-server/releases/download/rabbitmq_v3_6_12/rabbitmq-server-3.6.12-1.el6.noarch.rpm

安装RabbitMQ，root用户使用rpm安装

rpm -ihv rabbitmq-server-3.6.12-1.el6.noarch.rpm

一般来说不会有什么问题，如果安装RabbitMQ过程中遇到如下错误，清空rpmdb然后重试。

我遇到的问题如下是

[root@bigdata-arch-client11 yangfan]# rpm -ihv erlang-18.1-1.el6.x86_64.rpm 
rpmdb: Thread/process 72423/139858093815712 failed: Thread died in Berkeley DB library
error: db3 error(-30974) from dbenv->failchk: DB_RUNRECOVERY: Fatal error, run database recovery
error: cannot open Packages index using db3 -  (-30974)
error: cannot open Packages database in /var/lib/rpm
rpmdb: Thread/process 72423/139858093815712 failed: Thread died in Berkeley DB library
error: db3 error(-30974) from dbenv->failchk: DB_RUNRECOVERY: Fatal error, run database recovery
error: cannot open Packages database in /var/lib/rpm

 百度了一下，请按顺序执行，然后重试安装。

rm -f /var/lib/rpm/__db*
rpm --rebuilddb  
yum clean all 

当安装完成之后，可以使用缺省配置启动一下，如果打印如下，那么安装就成功了。

[root@bigdata-arch-client11 yangfan]# rabbitmq-server 

              RabbitMQ 3.6.12. Copyright (C) 2007-2017 Pivotal Software, Inc.
  ##  ##      Licensed under the MPL.  See http://www.rabbitmq.com/
  ##  ##
  ##########  Logs: /var/log/rabbitmq/rabbit@bigdata-arch-client11.log
  ######  ##        /var/log/rabbitmq/rabbit@bigdata-arch-client11-sasl.log
  ##########
              Starting broker...
 completed with 0 plugins.

2、配置RabbitMQ

1）创建RabbitMQ账号

rabbitmqctl add_user admin bigdata123

[root@bigdata-arch-client11 yangfan]# rabbitmqctl add_user admin bigdata123
Creating user "admin"

 2）将admin账号赋予管理员权限

rabbitmqctl set_user_tags admin administrator

[root@bigdata-arch-client11 yangfan]#  rabbitmqctl set_user_tags admin administrator
Setting tags for user "admin" to [administrator]

 3）设置权限

rabbitmqctl  set_permissions  -p  '/'  admin '.' '.' '.'

[root@bigdata-arch-client09 ~]#  rabbitmqctl  set_permissions  -p  '/'  admin '.' '.' '.'
Setting permissions for user "admin" in vhost "/"

 4）启用web管理插件

rabbitmq-plugins enable rabbitmq_management

[root@bigdata-arch-client11 yangfan]# rabbitmq-plugins enable rabbitmq_management
The following plugins have been enabled:
  amqp_client
  cowlib
  cowboy
  rabbitmq_web_dispatch
  rabbitmq_management_agent
  rabbitmq_management

Applying plugin configuration to rabbit@bigdata-arch-client11... started 6 plugins.

这样你可以通过web页面观察rabbitmq的status，端口号是15672，例如http://ip:15672 

3、配置RabbitMQ集群

我们这里会展示如何配置一个RabbitMQ集群，集群由以下节点组成。

要保证集群在同一个局域网，IP能通。

 1）安装好RabbitMQ

安装方法同上文。

2）保证相同的Erlang Cookie

 我这里是把client09上的.erlang.cookie以scp的方式拷贝到另外两台机器。

[root@bigdata-arch-client09 ~]# scp /var/lib/rabbitmq/.erlang.cookie root@10.93.18.34:/var/lib/rabbitmq
[root@bigdata-arch-client09 ~]# scp /var/lib/rabbitmq/.erlang.cookie rootr@10.93.21.21:/var/lib/rabbitmq

3）运行各个RabbitMQ节点

rabbitmqctl stop
rabbitmq-server -detached 

运行成功后可以查看一下节点当前的集群状态，当然这个时候还没有组成集群。

[root@bigdata-arch-client09 ~]# rabbitmqctl cluster_status
[root@bigdata-arch-client10 ~]# rabbitmqctl cluster_status
[root@bigdata-arch-client11 ~]# rabbitmqctl cluster_status

4）将节点连接成集群

client10：加入到集群rabbit@bigdata-arch-client09

[root@bigdata-arch-client10 ~]#rabbitmqctl stop_app 
[root@bigdata-arch-client10 ~]#rabbitmqctl join_cluster rabbit@bigdata-arch-client09
[root@bigdata-arch-client10 ~]#rabbitmqctl start_app

client11：加入到集群rabbit@bigdata-arch-client09

[root@bigdata-arch-client11 ~]#rabbitmqctl stop_app 
[root@bigdata-arch-client11 ~]#rabbitmqctl join_cluster rabbit@bigdata-arch-client09
[root@bigdata-arch-client11 ~]#rabbitmqctl start_app

client09：不用加入自己

查看集群状态，我们可以在任意一台机器上查看，我们选择在client09上看。

[root@bigdata-arch-client09 ~]# rabbitmqctl cluster_status
Cluster status of node 'rabbit@bigdata-arch-client09'
[{nodes,[{disc,['rabbit@bigdata-arch-client09',
                'rabbit@bigdata-arch-client11'， 
                'rabbit@bigdata-arch-client10']}]},
 {running_nodes,['rabbit@bigdata-arch-client10', 
            'rabbit@bigdata-arch-client11'，
            'rabbit@bigdata-arch-client09']},
 {cluster_name,<<"rabbit@bigdata-arch-client09.xg01">>},
 {partitions,[]},
 {alarms,[{'rabbit@bigdata-arch-client10',[]},
          {'rabbit@bigdata-arch-client09',[]}, 
          {'rabbit@bigdata-arch-client11', []}]}]    

可以看到，3个实例已经组成了集群。 

5）试一下容错

我们关掉client10上的实例

[root@bigdata-arch-client10 ~]# rabbitmqctl stop

然后我们再看集群情况

[root@bigdata-arch-client09 ~]# rabbitmqctl cluster_status
Cluster status of node 'rabbit@bigdata-arch-client09'
[{nodes,[{disc,['rabbit@bigdata-arch-client09',
                'rabbit@bigdata-arch-client11']}]},
 {running_nodes,['rabbit@bigdata-arch-client11',
                 'rabbit@bigdata-arch-client09']},
 {cluster_name,<<"rabbit@bigdata-arch-client11.xg01">>},
 {partitions,[]},
 {alarms,[{'rabbit@bigdata-arch-client11',[]},
          {'rabbit@bigdata-arch-client09',[]}]}]

可以发现client10已经成功摘除。

4、HA配置

我们使用haproxy来代理配置高可用。

haproxy可以用来做代理，进行负载均衡和backend探活。支持TCP和HTTP模式。

关于haproxy的内容就不展开说了。

这里仅仅给出配置。

########tcp配置#################  
listen rabbitmq
    bind 10.93.21.21:5077  
    mode tcp  
    option  tcplog          #日志类别,采用tcplog  
    maxconn 4086  
    #log 127.0.0.1 local0 debug  
    server rabbit1 10.93.18.34:5672  maxconn 1024 weight 1 check inter 2000 rise 2 fall 3
    server rabbit2 10.93.18.35:5672  maxconn 1024 weight 1 check inter 2000 rise 2 fall 3
    server rabbit3 10.93.21.21:5672  maxconn 1024 weight 1 check inter 2000 rise 2 fall 3

实验一下，下面是实验验证的程序，你可以挂掉一个实例试试。

send.py

# -*- coding:utf-8 -*-
import pika

credentials = pika.PlainCredentials('admin','bigdata123')
connection = pika.BlockingConnection(pika.ConnectionParameters(
    '10.93.21.21',5077, '/', credentials))
channel = connection.channel()
# 声明queue
channel.queue_declare(queue='balance')
# n RabbitMQ a message can never be sent directly to the queue, it always needs to go through an exchange.
channel.basic_publish(exchange='',
                      routing_key='balance',
                      body='Hello World!')
print(" [x] Sent 'Hello World!'")
connection.close()

receive.py

# _*_coding:utf-8_*_
import pika

credentials = pika.PlainCredentials('admin','bigdata123')
connection = pika.BlockingConnection(pika.ConnectionParameters(
    '10.93.21.21',5077,'/',credentials))
channel = connection.channel()

# You may ask why we declare the queue again ‒ we have already declared it in our previous code.
# We could avoid that if we were sure that the queue already exists. For example if send.py program
# was run before. But we're not yet sure which program to run first. In such cases it's a good
# practice to repeat declaring the queue in both programs.
channel.queue_declare(queue='balance')

def callback(ch, method, properties, body):
    print(" [x] Received %r" % body)

channel.basic_consume(callback,
                      queue='balance',
                      no_ack=True)

print(' [*] Waiting for messages. To exit press CTRL+C')
channel.start_consuming()