multiprocessing.Pool示例 [英] multiprocessing.Pool example

问题描述

我正在尝试学习如何使用多重处理，并找到了

I'm trying to learn how to use multiprocessing, and found the following example.

我想对值求和如下:

from multiprocessing import Pool
from time import time

N = 10
K = 50
w = 0

def CostlyFunction(z):
    r = 0
    for k in xrange(1, K+2):
        r += z ** (1 / k**1.5)
    print r
    w += r
    return r

currtime = time()

po = Pool()

for i in xrange(N):
    po.apply_async(CostlyFunction,(i,))
po.close()
po.join()

print w
print '2: parallel: time elapsed:', time() - currtime

我无法获得所有r个值的总和.

I can't get the sum of all r values.

推荐答案

如果要像这样使用apply_async，则必须使用某种共享内存.另外，您需要放置启动多重处理的部分，以便仅在初始脚本调用时才完成，而不是在合并的进程中调用.这是使用地图的一种方法.

If you're going to use apply_async like that, then you have to use some sort of shared memory. Also, you need to put the part that starts the multiprocessing so that it is only done when called by the initial script, not the pooled processes. Here's a way to do it with map.

from multiprocessing import Pool
from time import time

K = 50
def CostlyFunction((z,)):
    r = 0
    for k in xrange(1, K+2):
        r += z ** (1 / k**1.5)
    return r

if __name__ == "__main__":
    currtime = time()
    N = 10
    po = Pool()
    res = po.map_async(CostlyFunction,((i,) for i in xrange(N)))
    w = sum(res.get())
    print w
    print '2: parallel: time elapsed:', time() - currtime

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