时间:2021-07-01 10:21:17 帮助过:57人阅读
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!