ProcessPoolExecutor(max_workers=64) crashes on Windows

[diogocp]

BPO	26903
PRs	bpo-26903: Limit ProcessPoolExecutor to 61 workers on Windows #13132 [3.7] bpo-26903: Limit ProcessPoolExecutor to 61 workers on Windows (GH-13132) #13206 [3.7] bpo-26903: Limit ProcessPoolExecutor to 61 workers on Windows (GH-13132) #13643

^{Note: these values reflect the state of the issue at the time it was migrated and might not reflect the current state.}

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GitHub fields:

assignee = 'https://github.com/brianquinlan'
closed_at = <Date 2019-05-09.17:37:35.091>
created_at = <Date 2016-05-01.20:45:38.281>
labels = ['type-bug', 'build']
title = 'ProcessPoolExecutor(max_workers=64) crashes on Windows'
updated_at = <Date 2021-11-04.13:56:41.517>
user = 'https://github.com/diogocp'

bugs.python.org fields:

activity = <Date 2021-11-04.13:56:41.517>
actor = 'eryksun'
assignee = 'bquinlan'
closed = True
closed_date = <Date 2019-05-09.17:37:35.091>
closer = 'bquinlan'
components = ['Cross-Build']
creation = <Date 2016-05-01.20:45:38.281>
creator = 'diogocp'
dependencies = []
files = []
hgrepos = []
issue_num = 26903
keywords = ['patch']
message_count = 12.0
messages = ['264608', '265007', '265086', '265206', '340390', '341545', '341571', '341918', '343858', '365886', '365901', '366314']
nosy_count = 0.0
nosy_names = []
pr_nums = ['13132', '13206', '13643']
priority = 'normal'
resolution = 'fixed'
stage = 'resolved'
status = 'closed'
superseder = None
type = 'behavior'
url = 'https://bugs.python.org/issue26903'
versions = ['Python 3.6']

[diogocp]

I'm using Python 3.5.1 x86-64 on Windows Server 2008 R2. Trying to run the ProcessPoolExecutor example [1] generates this exception:

Exception in thread Thread-1:
Traceback (most recent call last):
 File "C:\Program Files\Python35\lib\threading.py", line 914, in _bootstrap_inner
 self.run()
 File "C:\Program Files\Python35\lib\threading.py", line 862, in run
 self._target(*self._args, **self._kwargs)
 File "C:\Program Files\Python35\lib\concurrent\futures\process.py", line 270, in _queue_management_worker
 ready = wait([reader] + sentinels)
 File "C:\Program Files\Python35\lib\multiprocessing\connection.py", line 859, in wait
 ready_handles = _exhaustive_wait(waithandle_to_obj.keys(), timeout)
 File "C:\Program Files\Python35\lib\multiprocessing\connection.py", line 791, in _exhaustive_wait
 res = _winapi.WaitForMultipleObjects(L, False, timeout)
ValueError: need at most 63 handles, got a sequence of length 64

The problem seems to be related to the value of the Windows constant MAXIMUM_WAIT_OBJECTS (see [2]), which is 64. This machine has 64 logical cores, so ProcessPoolExecutor defaults to 64 workers.

Lowering max_workers to 63 or 62 still results in the same exception, but max_workers=61 works fine.

[1] https://docs.python.org/3.5/library/concurrent.futures.html#processpoolexecutor-example
[2] https://hg.python.org/cpython/file/80d1faa9735d/Modules/_winapi.c#l1339

[terryjreedy]

The example runs fine, in about 1 second, on my 6 core (which I guess is 12 logical cores) Pentium. I am guessing that the default number of workers needs to be changed, at least on Windows, to min(#logical_cores, 60)

[tim-one]

Just noting that the multiprocessing module can be used instead. In the example, add

 import multiprocessing as mp

and change

 with concurrent.futures.ProcessPoolExecutor() as executor:

to

 with mp.Pool() as executor:

That's all it takes. On my 4-core Win10 box (8 logical cores), that continued to work fine even when passing 1024 to mp.Pool() (although it obviously burned time and RAM to create over a thousand processes).

Some quick Googling strongly suggests there's no reasonably general way to overcome the Windows-defined MAXIMUM_WAIT_OBJECTS=64 for implementations that call the Windows WaitForMultipleObjects().

[zooba]

Some quick Googling strongly suggests there's no reasonably general way to overcome the Windows-defined MAXIMUM_WAIT_OBJECTS=64 for implementations that call the Windows WaitForMultipleObjects().

The recommended way to deal with this is to spin up threads to do the wait (which sounds horribly inefficient, but threads on Windows are cheap, especially if they are waiting on kernel objects), and then wait on each thread.

Personally I think it'd be fine to make the _winapi module do that transparently for WaitForMultipleObjects, as it's complicated to get right (you need to ensure you map back to the original handle, timeouts and cancellation get complicated, there are real race conditions (mainly for auto-reset events), etc.), but in all circumstances it's better than just failing immediately. Handling it within multiprocessing isn't a bad idea, but won't help other users.

I'd love to write the code to do it, but I doubt I'll get time (especially since I'm missing the PyCon US sprints this year). Happy to help someone else through it. We're going to see Python being used on more and more multicore systems over time, where this will become a genuine issue.

[rbtcollins]

This is now showing up in end user tools like black: psf/black#564

[brianquinlan]

If no one has short-term plans to improve multiprocessing.connection.wait, then I'll update the docs to list this limitation, ensure that ProcessPoolExecutor never defaults to >60 processes on windows and raises a ValueError if the user explicitly passes a larger number.

[brianquinlan]

BTW, the 61 process limit comes from:

63 - <the result queue reader> - <the thread wakeup reader>

[zooba]

New changeset 3988986 by Steve Dower (Brian Quinlan) in branch 'master':
bpo-26903: Limit ProcessPoolExecutor to 61 workers on Windows (GH-13132)
3988986