RabbitMQ如何应对Server出现异常以及server分发任务的负载均衡问题
上一篇文章结尾我留了一个问题，就是在work2中设no_ack=True
出现那样的结果是因为server一次分发多个结果给work2，work2又在执行完了以后没有发送ack确认执行结束，server端是根据connection是否存在来判断work2是否stoped，由于连接存在，所以server认为work2正在执行，其实此时work2已经执行结束，正在等待server发送消息。。。
一：
task是被加载到内存中的，要避免server崩溃导致的task丢失，当然想到的办法就是持久化，将task保存到硬盘上
在定义Queue的时候，设置属性durable=True
channel.queue_declare(=,=)
与此同时需要告知生产者，queue是被持久化在硬盘上的
channel.basic_publish(exchange='', routing_key="task_queue", body=message, properties=pika.BasicProperties( delivery_mode = 2, # make message persistent ))
二：
如何解决server一次分发多个任务的情况，也可以通过设置属性
channel.basic_qos(prefetch_count=1)
new_task.py:
# -*- coding: UTF-8 -*-
import pika
if __name__ == '__main__':
connection = pika.BlockingConnection(pika.ConnectionParameters("localhost"))
channel = connection.channel()
channel.queue_declare(queue="Kadima", durable=True)
message = "You are awsome!"
for i in range(0, 100): # 循环100次发送消息
channel.basic_publish(exchange="", routing_key='Kadima', body=message + " " + str(i),
properties=pika.BasicProperties(delivery_mode=2))
print "sending ", message
work代码：
#-*- coding: UTF-8 -*-
import time
import pika
import sys
__author__ = 'Yue'
var=0
def callback(ch, method, properties, body):
# <pika.adapters.blocking_connection.BlockingChannel object at 0x02973BF0> <Basic.
# Deliver(['consumer_tag=ctag1.8b367697d96c4579ba78914d8a4760a8', 'delivery_tag=50
# ', 'exchange=', 'redelivered=False', 'routing_key=Kadima'])> <BasicProperties> Y
# ou are awsome! 98
# temp=var+1 #这里有趣的是不能写成var+=1或者var=var+1，要知道为什么，就需要清楚“Python全局变量和局部变量”
# global var
# var+=1
# if var==20:
# print var , body
# sys.exit()
print "1 received %r" % (body,)
# time.sleep(0.1)
print "Done"
#设置返回ack的标志，method.delivery_tag是MQ分发给Work时的一个标记
ch.basic_ack(delivery_tag = method.delivery_tag)
if __name__ == '__main__':
connection=pika.BlockingConnection(pika.ConnectionParameters("localhost"))
channel=connection.channel()
channel.basic_qos(prefetch_count=1)
channel.queue_declare(queue="Kadima",durable=True)
channel.basic_consume(callback,queue="Kadima")
print ' [1] Waiting for messages'
channel.start_consuming()
work2.py
import time
import pika
__author__ = 'Yue'
def callback(ch, method, properties, body):
print "2 received %r" % (body,)
# time.sleep(0.1)
print "Done"
ch.basic_ack(delivery_tag = method.delivery_tag)
if __name__ == '__main__':
connection=pika.BlockingConnection(pika.ConnectionParameters("localhost"))
channel=connection.channel()
channel.basic_qos(prefetch_count=1)
channel.queue_declare(queue="Kadima",durable=True)
channel.basic_consume(callback,queue="Kadima")
print ' [2] Waiting for messages'
channel.start_consuming()
3运行结果
可以看出server对任务的分发已经变得随机，而不是原来的依次分发