python multiprocessing .join() 死锁依赖于worker函数

I am using the multiprocessing python library to spawn 4 Process() objects to parallelize a cpu intensive task. The task (inspiration and code from this great article) is to compute the prime factors for every integer in a list.

ma​​in.py:

import random
import multiprocessing
import sys

num_inputs  = 4000
num_procs   = 4
proc_inputs = num_inputs/num_procs
input_list  = [int(1000*random.random()) for i in xrange(num_inputs)]

output_queue = multiprocessing.Queue()
procs        = []
for p_i in xrange(num_procs):
  print "Process [%d]"%p_i
  proc_list = input_list[proc_inputs * p_i:proc_inputs * (p_i + 1)]
  print " - num inputs: [%d]"%len(proc_list)

  # Using target=worker1 HANGS on join
  p = multiprocessing.Process(target=worker1, args=(p_i, proc_list, output_queue))
  # Using target=worker2 RETURNS with success
  #p = multiprocessing.Process(target=worker2, args=(p_i, proc_list, output_queue))

  procs.append(p)
  p.start()

for p in jobs:
  print "joining ", p, output_queue.qsize(), output_queue.full()
  p.join()
  print "joined  ", p, output_queue.qsize(), output_queue.full()

print "Processing complete."
ret_vals = []
while output_queue.empty() == False:
    ret_vals.append(output_queue.get())
print len(ret_vals)
print sys.getsizeof(ret_vals)

观察:

• 如果每个进程的目标是函数 worker1，对于大于 4000 个元素的输入列表，主线程会卡在 .join() 上，等待产生的进程终止并且永不返回.
• 如果每个进程的目标是函数 worker2，对于相同的输入列表，代码工作正常，主线程返回.

def worker1(proc_num, proc_list, output_queue):
    '''worker function which deadlocks'''  
    for num in proc_list:
        output_queue.put(factorize_naive(num))

def worker2(proc_num, proc_list, output_queue):
    '''worker function that works'''
    workers_stuff = []

    for num in proc_list:
        workers_stuff.append(factorize_naive(num))
    output_queue.put(workers_stuff)