【发布时间】:2019-03-06 14:05:51
【问题描述】:
代码:
import multiprocessing
print(f'num cpus {multiprocessing.cpu_count():d}')
import sys; print(f'Python {sys.version} on {sys.platform}')
def _process(m):
print(m) #; return m
raise ValueError(m)
args_list = [[i] for i in range(1, 20)]
if __name__ == '__main__':
with multiprocessing.Pool(2) as p:
print([r for r in p.starmap(_process, args_list)])
打印:
num cpus 8
Python 3.7.1 (v3.7.1:260ec2c36a, Oct 20 2018, 03:13:28)
[Clang 6.0 (clang-600.0.57)] on darwin
1
7
4
10
13
16
19
multiprocessing.pool.RemoteTraceback:
"""
Traceback (most recent call last):
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/multiprocessing/pool.py", line 121, in worker
result = (True, func(*args, **kwds))
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/multiprocessing/pool.py", line 47, in starmapstar
return list(itertools.starmap(args[0], args[1]))
File "/Users/ubik-mac13/Library/Preferences/PyCharm2018.3/scratches/multiprocess_error.py", line 8, in _process
raise ValueError(m)
ValueError: 1
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/Users/ubik-mac13/Library/Preferences/PyCharm2018.3/scratches/multiprocess_error.py", line 18, in <module>
print([r for r in p.starmap(_process, args_list)])
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/multiprocessing/pool.py", line 298, in starmap
return self._map_async(func, iterable, starmapstar, chunksize).get()
File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/multiprocessing/pool.py", line 683, in get
raise self._value
ValueError: 1
Process finished with exit code 1
将池中的进程数增加到 3 或 4 会打印所有奇数(可能是乱序):
1
3
5
9
11
7
13
15
17
19
从 5 开始,它会打印 1-19 的所有范围。那么这里会发生什么?进程是否在多次失败后崩溃?
这当然是一个玩具示例,但它来自我遇到的一个真实代码问题 - 让一个多处理池稳定运行了几天,cpu 使用率下降,好像某些进程被杀死(注意 cpu 利用率下降03/04 和 03/06,还有很多任务要运行):
当代码终止时,它向我展示了一个(只有一个在这里,而进程更多)multiprocessing.pool.RemoteTraceback - 额外的问题是这个回溯是随机的吗?在这个玩具示例中,它通常是ValueError: 1,但有时也会出现其他数字。多处理是否保留第一个崩溃进程的第一个回溯?
【问题讨论】:
标签: python python-3.x parallel-processing multiprocessing python-multiprocessing