mutilprocess像线程一样管理进程，这个是mutilprocess的核心，他与threading很是相像，对多核CPU的利用率会比threading好的多。
介绍
Python的multiprocessing模块不但支持多进程，其中managers子模块还支持把多进程分布到多台机器上。一个服务进程可以作为调度者，将任务分布到其他多个机器的多个进程中，依靠网络通信。
想到这，就在想是不是可以使用此模块来实现一个简单的作业调度系统。
实现
Job
首先创建一个Job类，为了测试简单，只包含一个job id属性
job.py
#!/usr/bin/env python # -*- coding: utf-8 -*- class Job: def __init__(self, job_id): self.job_id = job_id
Master
Master用来派发作业和显示运行完成的作业信息
master.py
#!/usr/bin/env python # -*- coding: utf-8 -*- from Queue import Queue from multiprocessing.managers import BaseManager from job import Job
class Master:
def __init__(self):
# 派发出去的作业队列
self.dispatched_job_queue = Queue()
# 完成的作业队列
self.finished_job_queue = Queue()
def get_dispatched_job_queue(self):
return self.dispatched_job_queue
def get_finished_job_queue(self):
return self.finished_job_queue
def start(self):
# 把派发作业队列和完成作业队列注册到网络上
BaseManager.register('get_dispatched_job_queue', callable=self.get_dispatched_job_queue)
BaseManager.register('get_finished_job_queue', callable=self.get_finished_job_queue)
# 监听端口和启动服务
manager = BaseManager(address=('0.0.0.0', 8888), authkey='jobs')
manager.start()
# 使用上面注册的方法获取队列
dispatched_jobs = manager.get_dispatched_job_queue()
finished_jobs = manager.get_finished_job_queue()
# 这里一次派发10个作业，等到10个作业都运行完后，继续再派发10个作业
job_id = 0
while True:
for i in range(0, 10):
job_id = job_id + 1
job = Job(job_id)
print('Dispatch job: %s' % job.job_id)
dispatched_jobs.put(job)
while not dispatched_jobs.empty():
job = finished_jobs.get(60)
print('Finished Job: %s' % job.job_id)
manager.shutdown()
if __name__ == "__main__":
master = Master()
master.start()
Slave
Slave用来运行master派发的作业并将结果返回
slave.py
#!/usr/bin/env python # -*- coding: utf-8 -*- import time from Queue import Queue from multiprocessing.managers import BaseManager from job import Job
class Slave:
def __init__(self): # 派发出去的作业队列 self.dispatched_job_queue = Queue() # 完成的作业队列 self.finished_job_queue = Queue()
def start(self):
# 把派发作业队列和完成作业队列注册到网络上
BaseManager.register('get_dispatched_job_queue')
BaseManager.register('get_finished_job_queue')
# 连接master
server = '127.0.0.1'
print('Connect to server %s...' % server)
manager = BaseManager(address=(server, 8888), authkey='jobs')
manager.connect()
# 使用上面注册的方法获取队列
dispatched_jobs = manager.get_dispatched_job_queue()
finished_jobs = manager.get_finished_job_queue()
# 运行作业并返回结果，这里只是模拟作业运行，所以返回的是接收到的作业
while True:
job = dispatched_jobs.get(timeout=1)
print('Run job: %s ' % job.job_id)
time.sleep(1)
finished_jobs.put(job)
if __name__ == "__main__":
slave = Slave()
slave.start()
测试
分别打开三个linux终端，第一个终端运行master，第二个和第三个终端用了运行slave，运行结果如下
master
$ python master.py Dispatch job: 1 Dispatch job: 2 Dispatch job: 3 Dispatch job: 4 Dispatch job: 5 Dispatch job: 6 Dispatch job: 7 Dispatch job: 8 Dispatch job: 9 Dispatch job: 10 Finished Job: 1 Finished Job: 2 Finished Job: 3 Finished Job: 4 Finished Job: 5 Finished Job: 6 Finished Job: 7 Finished Job: 8 Finished Job: 9 Dispatch job: 11 Dispatch job: 12 Dispatch job: 13 Dispatch job: 14 Dispatch job: 15 Dispatch job: 16 Dispatch job: 17 Dispatch job: 18 Dispatch job: 19 Dispatch job: 20 Finished Job: 10 Finished Job: 11 Finished Job: 12 Finished Job: 13 Finished Job: 14 Finished Job: 15 Finished Job: 16 Finished Job: 17 Finished Job: 18 Dispatch job: 21 Dispatch job: 22 Dispatch job: 23 Dispatch job: 24 Dispatch job: 25 Dispatch job: 26 Dispatch job: 27 Dispatch job: 28 Dispatch job: 29 Dispatch job: 30
slave1
$ python slave.py Connect to server 127.0.0.1... Run job: 1 Run job: 2 Run job: 3 Run job: 5 Run job: 7 Run job: 9 Run job: 11 Run job: 13 Run job: 15 Run job: 17 Run job: 19 Run job: 21 Run job: 23
slave2
$ python slave.py Connect to server 127.0.0.1... Run job: 4 Run job: 6 Run job: 8 Run job: 10 Run job: 12 Run job: 14 Run job: 16 Run job: 18 Run job: 20 Run job: 22 Run job: 24
以上内容是小编给大家介绍的Python使用multiprocessing实现一个最简单的分布式作业调度系统，希望对大家有所帮助！
