任务队列
在web开发的场景中撰写常规的代码,一般是在一个视图层(view)将所有业务逻辑完成之后直接返回数据(可以是一个渲染后的html也可以是一组json数据)给用户的浏览器;业务比较简单且单一的逻辑处理响应时间通常都比较短,但涉及到发邮件、数据爬取、密集计算、复杂业务这种情况耗时较长的操作,如果不采取任何措施的话,那么在用户这边最直观的感受就是提交了请求后页面就僵在那里了(如果时间大于10秒钟,可能就会认为出问题了)。
redis的任务队列(列表)就是这种耗时等待比较长场景的解决办法之一,视图层是一个负责塞消息的对象(Producer角色),然后在单独写一个独立的进程来读取这个列表(Consumer)去完成后续的工作;那么视图层就可以直接返回一个页面给用户,告诉用户这个事情的状态是正在处理中,当处理完成之后将状态改成已完成,并提供一个链接让用户可以去查看任务明细结果。
将一个耗时操作拆开要从好几个方面进行考虑,用户的等待体验、将相同功能相同作用的代码抽象出来解耦、简化逻辑层的代码复杂度。
非堵塞读取(rpop)
queue_rpop/producer.py
import redis
# 连接redis
r = redis.StrictRedis('192.168.1.124', decode_responses=True)
# 清空所有键
for number, key in enumerate(r.keys()):
r.delete(key)
# 准备数据
r.rpush('queue:send_mail', *['3330356463@qq.com', 'zhengtong0898@aliyun.com'])
queue_rpop/consumer1.py
import redis
from datetime import datetime as dt
# 连接redis
r = redis.StrictRedis('192.168.1.124', decode_responses=True)
while True:
email = r.rpop('queue:send_mail')
print('[{} {} INFO]: {}'.format(
dt.now(),
'queue:send_mail',
email
))
queue_rpop/consumer2.py
import redis
import time
from datetime import datetime as dt
# 连接redis
r = redis.StrictRedis('192.168.1.124', decode_responses=True)
def send_mail(email):
print('[{} {} INFO]: send mail to {}'.format(
dt.now(),
'queue:send_mail',
email
))
if __name__ == '__main__':
while True:
mail = r.rpop('queue:send_mail')
if not mail:
print('[{} {} INFO]: {}'.format(
dt.now(),
'queue:send_mail',
mail
))
time.sleep(1)
continue
send_mail(mail)
运行
# 运行consumer1.py
python consumer1.py
# 显示结果,这种方式对CPU消耗非常大,整体的IO消耗也很高。
[2017-04-26 18:59:31.822200 queue:send_mail INFO]: None
[2017-04-26 18:59:31.822700 queue:send_mail INFO]: None
[2017-04-26 18:59:31.822700 queue:send_mail INFO]: None
[2017-04-26 18:59:31.823200 queue:send_mail INFO]: None
[2017-04-26 18:59:31.823200 queue:send_mail INFO]: None
[2017-04-26 18:59:31.823700 queue:send_mail INFO]: None
[2017-04-26 18:59:31.824200 queue:send_mail INFO]: None
...
...
...
# 运行consumer2.py (为了降低没有必要的系统消耗)
python consumer2.py
# 再开一个窗口运行 producer.py
python producer.py
# 显示结果
[2017-04-26 19:15:29.695200 queue:send_mail INFO]: None
[2017-04-26 19:15:30.695700 queue:send_mail INFO]: None
[2017-04-26 19:15:31.695700 queue:send_mail INFO]: None
[2017-04-26 19:15:32.696700 queue:send_mail INFO]: None
[2017-04-26 19:15:33.697200 queue:send_mail INFO]: send mail to 3330356463@qq.com
[2017-04-26 19:15:33.697700 queue:send_mail INFO]: send mail to zhengtong0898@aliyun.com
[2017-04-26 19:15:33.698200 queue:send_mail INFO]: None
[2017-04-26 19:15:34.698700 queue:send_mail INFO]: None
[2017-04-26 19:15:35.699200 queue:send_mail INFO]: None
堵塞读取(brpop)
redis内部并没有采用非堵塞的socket模型,因此初步判断它是一个堵塞请求,它的等待机制是由redis内部来负责响应的。堵塞让资源消耗更少,逻辑撰写更容易。
queue_brpop/consumer.py
import redis
from datetime import datetime as dt
# 连接redis
r = redis.StrictRedis('192.168.1.124', decode_responses=True)
def send_mail(email):
print('[{} {} INFO]: send mail to {}'.format(
dt.now(),
'queue:send_mail',
email
))
if __name__ == '__main__':
while True:
queue_name, mail = r.brpop('queue:send_mail')
send_mail(mail)
运行
# 运行queue_brpop/consumer.py
python queue_brpop/consumer.py
# 运行queue_rpop/producer.py
# 显示结果(没有多余的输出,挺好!)
[2017-04-26 19:31:23.947200 queue:send_mail INFO]: send mail to 3330356463@qq.com
[2017-04-26 19:31:23.947700 queue:send_mail INFO]: send mail to zhengtong0898@aliyun.com
优先级(lpush、blpop)
最普遍和常见的新增列表列表元素是在当前列表后面追加元素,取值的话则是从左到右读取,这种行为在消息队列中被称为先进先出(FIFO);那也会有一些场景要求后进先出(LIFO),这就需要利用lpush(从左边开始插入元素)和blpop(从左边开始读取)。
quque_priority/producer.py
import redis
# 连接redis
r = redis.StrictRedis('192.168.1.124', decode_responses=True)
# 清空所有键
for number, key in enumerate(r.keys()):
r.delete(key)
# 准备数据
r.lpush('queue:send_mail', '3330356463@qq.com')
r.lpush('queue:send_mail', 'zhengtong0898@aliyun.com')
r.lpush('queue:send_mail', 'zhengtong0898@a.com')
r.lpush('queue:send_mail', 'zhengtong0898@b.com')
r.lpush('queue:send_mail', 'zhengtong0898@c.com')
r.lpush('queue:send_mail', 'zhengtong0898@d.com')
r.lpush('queue:send_mail', 'zhengtong0898@e.com')
queue_priority/consumer.py
import redis
from datetime import datetime as dt
# 连接redis
r = redis.StrictRedis('192.168.1.124', decode_responses=True)
def send_mail(email):
print('[{} {} INFO]: send mail to {}'.format(
dt.now(),
'queue:send_mail',
email
))
if __name__ == '__main__':
while True:
queue_name, mail = r.blpop('queue:send_mail')
send_mail(mail)
运行
# 运行producer.py,先将数据塞到redis列表中(每次都是从左边插入)
python queue_priority/producer.py
# 运行consumer.py,消费数据(每次都是从左边读取)
python queue_priority/consumer.py
# 显示结果,仔细看就可以看得出来,确实是后进先出(LIFO)
[2017-04-26 20:29:18.735700 queue:send_mail INFO]: send mail to zhengtong0898@e.com
[2017-04-26 20:29:18.735700 queue:send_mail INFO]: send mail to zhengtong0898@d.com
[2017-04-26 20:29:18.736200 queue:send_mail INFO]: send mail to zhengtong0898@c.com
[2017-04-26 20:29:18.736700 queue:send_mail INFO]: send mail to zhengtong0898@b.com
[2017-04-26 20:29:18.736700 queue:send_mail INFO]: send mail to zhengtong0898@a.com
[2017-04-26 20:29:18.737200 queue:send_mail INFO]: send mail to zhengtong0898@aliyun.com
[2017-04-26 20:29:18.737700 queue:send_mail INFO]: send mail to 3330356463@qq.com
发布/订阅
消息队列是将消息放在列表中,由一个或多个consumer去消费列表中不同的元素;而发布/订阅是将消息放在一个频道中,有一个或多个consumer去消费频道中相同的元素;若该频道中没有任何consumer,这次producer生产了一条消息放入到频道中,这条消息将会自动消失,因此发布/订阅模式要求consumer必须时刻运行,否则producer发送的任何消息都是无效的。
publish_subscribe/producer.py
import redis
from datetime import datetime as dt
# 连接redis
r = redis.StrictRedis('192.168.1.124', decode_responses=True)
r.publish('channel1.1', 'hi')
r.publish('channel1.1', 'my')
r.publish('channel1.1', 'name')
r.publish('channel1.1', 'is')
r.publish('channel1.1', 'publisher')
publish_subscribe/consumer.py
import redis
import time
from datetime import datetime as dt
# 连接redis
r = redis.StrictRedis('192.168.1.124', decode_responses=True)
p = r.pubsub()
p.subscribe('channel1.1') # 支持同时订阅多个频道: p.subscribe('channel1.1', 'channel1.2')
while True:
msg = p.get_message(ignore_subscribe_messages=True)
if not msg:
time.sleep(1)
print('sleep 1')
continue
print('debug: ', msg)
运行
# 打开两个窗口运行两次 consumer.py, 都订阅'channel1.1'频道.
python publish_subscribe/consumer.py # 窗口一
python publish_subscribe/consumer.py # 窗口二
# 运行producer.py, 将消息塞到'channel1.1'频道.
python publish_subscribe/producer.py
# 显示结果(两边都同时存在)
[2017-04-27 13:01:17.712700 publish/subscribe INFO]: None
[2017-04-27 13:01:18.712700 publish/subscribe INFO]: None
[2017-04-27 13:01:19.712700 publish/subscribe INFO]: None
[2017-04-27 13:01:19.712700 publish/subscribe INFO]: {'data': 'hi', 'type': 'message', 'pattern': None, 'channel': 'channel1.1'}
[2017-04-27 13:01:19.712700 publish/subscribe INFO]: {'data': 'my', 'type': 'message', 'pattern': None, 'channel': 'channel1.1'}
[2017-04-27 13:01:19.712700 publish/subscribe INFO]: {'data': 'name', 'type': 'message', 'pattern': None, 'channel': 'channel1.1'}
[2017-04-27 13:01:19.712700 publish/subscribe INFO]: {'data': 'is', 'type': 'message', 'pattern': None, 'channel': 'channel1.1'}
[2017-04-27 13:01:19.712700 publish/subscribe INFO]: {'data': 'publisher', 'type': 'message', 'pattern': None, 'channel': 'channel1.1'}
[2017-04-27 13:01:20.713200 publish/subscribe INFO]: None
[2017-04-27 13:01:21.714200 publish/subscribe INFO]: None
主题订阅
除了订阅多个频道之外,redis也支持consumer通过glob通配符(psubscribe)来订阅不同主题的频道。
publish_psubscribe/producer.py
import redis
from datetime import datetime as dt
# 连接redis
r = redis.StrictRedis('192.168.1.124', decode_responses=True)
r.publish('channel1.1', 'hi')
r.publish('channel1.2', 'my')
r.publish('channel1.3', 'name')
r.publish('channel1.4', 'is')
r.publish('channel1.5', 'publisher')
publish_psubscribe/consumer.py
import redis
import time
from datetime import datetime as dt
# 连接redis
r = redis.StrictRedis('192.168.1.124', decode_responses=True)
p = r.pubsub()
p.psubscribe('channel1.*')
while True:
msg = p.get_message(ignore_subscribe_messages=True)
if not msg:
time.sleep(1)
msg = None
print('[{} {} INFO]: {}'.format(
dt.now(),
'publish/psubscribe',
msg
))
运行
# 运行consumer.py
python publish_psubscribe/consumer.py
# 运行producer.py
publish_psubscribe/producer.py
# 显示结果
[2017-04-27 13:31:00.683700 publish/psubscribe INFO]: None
[2017-04-27 13:31:01.683700 publish/psubscribe INFO]: None
[2017-04-27 13:31:02.683700 publish/psubscribe INFO]: None
[2017-04-27 13:31:02.683700 publish/psubscribe INFO]: {'data': 'hi', 'type': 'pmessage', 'pattern': 'channel1.*', 'channel': 'channel1.1'}
[2017-04-27 13:31:02.683700 publish/psubscribe INFO]: {'data': 'my', 'type': 'pmessage', 'pattern': 'channel1.*', 'channel': 'channel1.2'}
[2017-04-27 13:31:02.683700 publish/psubscribe INFO]: {'data': 'name', 'type': 'pmessage', 'pattern': 'channel1.*', 'channel': 'channel1.3'}
[2017-04-27 13:31:02.683700 publish/psubscribe INFO]: {'data': 'is', 'type': 'pmessage', 'pattern': 'channel1.*', 'channel': 'channel1.4'}
[2017-04-27 13:31:02.683700 publish/psubscribe INFO]: {'data': 'publisher', 'type': 'pmessage', 'pattern': 'channel1.*', 'channel': 'channel1.5'}
[2017-04-27 13:31:03.683700 publish/psubscribe INFO]: None
[2017-04-27 13:31:04.683700 publish/psubscribe INFO]: None
参考
- [x] 书籍: Redis 入门指南
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