New submission from olarn <[email protected]>:
Multiprocessing's pool apparently attempts to repopulate the pool in an event
of sub-process worker crash. However the pool seems to hangs after about ~
4*(number of worker) process re-spawns.
I've tracked the issue down to queue.get() stalling at multiprocessing.pool,
line 102
Is this a known issue? Are there any known workaround?
To reproduce this issue:
import multiprocessing
import multiprocessing.util
import logging
multiprocessing.util._logger = multiprocessing.util.log_to_stderr(logging.DEBUG)
import time
import ctypes
def crash_py_interpreter():
print("attempting to crash the interpreter in ",
multiprocessing.current_process())
i = ctypes.c_char('a'.encode())
j = ctypes.pointer(i)
c = 0
while True:
j[c] = 'a'.encode()
c += 1
j
def test_fn(x):
print("test_fn in ", multiprocessing.current_process().name, x)
exit(0)
time.sleep(0.1)
if __name__ == '__main__':
# pool = multiprocessing.Pool(processes=multiprocessing.cpu_count())
pool = multiprocessing.Pool(processes=1)
args_queue = [n for n in range(20)]
# subprocess quits
pool.map(test_fn, args_queue)
# subprocess crashes
# pool.map(test_fn,queue)
----------
components: Library (Lib)
messages: 305124
nosy: olarn
priority: normal
severity: normal
status: open
title: Multiprocessing.Pool hangs after re-spawning several worker process.
type: behavior
versions: Python 2.7, Python 3.6
_______________________________________
Python tracker <[email protected]>
<https://bugs.python.org/issue31886>
_______________________________________
_______________________________________________
Python-bugs-list mailing list
Unsubscribe:
https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
