multiprocessing.Pool shouldn't hang forever if a worker process dies unexpectedly #66587
Comments
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This is essentially a dupe of bpo-9205, but it was suggested I open a new issue, since that one ended up being used to fix this same problem in concurrent.futures, and was subsequently closed. Right now, should a worker process in a Pool unexpectedly get terminated while a blocking Pool method is running (e.g. apply, map), the method will hang forever. This isn't a normal occurrence, but it does occasionally happen (either because someone sends a SIGTERM, or because of a bug in the interpreter or a C-extension). It would be preferable for multiprocessing to follow the lead of concurrent.futures.ProcessPoolExecutor when this happens, and abort all running tasks and close down the Pool. Attached is a patch that implements this behavior. Should a process in a Pool unexpectedly exit (meaning, *not* because of hitting the maxtasksperchild limit), the Pool will be closed/terminated and all cached/running tasks will raise a BrokenProcessPool exception. These changes also prevent the Pool from going into a bad state if the "initializer" function raises an exception (previously, the pool would end up infinitely starting new processes, which would immediately die because of the exception). One concern with the patch: The way timings are altered with these changes, the Pool seems to be particularly susceptible to bpo-6721 in certain cases. If processes in the Pool are being restarted due to maxtasksperchild just as the worker is being closed or joined, there is a chance the worker will be forked while some of the debug logging inside of Pool is running (and holding locks on either sys.stdout or sys.stderr). When this happens, the worker deadlocks on startup, which will hang the whole program. I believe the current implementation is susceptible to this as well, but I could reproduce it much more consistently with this patch. I think its rare enough in practice that it shouldn't prevent the patch from being accepted, but thought I should point it out. (I do think bpo-6721 should be addressed, or at the very least internal I/O locks should always reset after forking.) |
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This problem also happens simply by calling sys.exit from one of the child processes. The following script exhibits the problem: import multiprocessing
import sys
def test(value):
if value:
sys.exit(123)
if __name__ == '__main__':
pool = multiprocessing.Pool(4)
cases = [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0]
pool.map(test, cases) |
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We use multiprocessing to parallelize many tasks that run either python code or call subprocess.run that are memory hungry. At times the OOM Killer kicks in. When one of the workers is killed, the queue never returns an error for the task being run by the worker. Are there any plans to merge the patch proposed in this issue? |
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Oscar, the patch posted here needs updating for the latest git master. If you want to avoid this issue, you can also use concurrent.futures where the issue is fixed. |
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Hi Antoine, I may take a stab at it. Before I start, should I branch from master or from 3.7.1 (as 3.7 is still accepting bugfixes). Best, |
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You should start from master. Bugfixes can backported afterwards if appropriate. Thanks! |
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I tried to reuse as much as I could from the patch, but it didn't solve the issue at first. I have changed the responsibility of identifying and prescribing a solution when a worker got killed. In the proposed patch, the thread handling results (i.e. tasks queued by one worker as done) was responsible. In the PR, the responsibility is reassigned to the thread handling workers (since, basically, one or more workers suddenly die). The patch defined a new BROKEN state that was assigned to the results handler thread. I transferred this behavior to the worker handler thread. But, I'm guessing that the BROKEN state should be assigned to the Pool object instead, to be fully semantic. Although that would require passing the reference to the object around and complicate unnecessarily the implementation. Happy to reconsider though. I added three tests, one that was present with the patch, a variation of it adding some wait before killing the worker, and the one that Francis Bolduc posted here (https://bugs.python.org/issue22393#msg294968). Please let me know whether any conversation about this bug should take place in GitHub, with the PR instead of here. Thanks a lot for the guidance, Antoine. |
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Just a bump to note that the PR (10441) is ready for another round of review. |
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I just marked bpo-38084 as duplicate of this issue. I manually merged the nosy lists. |
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Somewhat related bpo-43806 with asyncio.StreamReader |
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I'm running into this as well - and I can't use My use case:I'm writing Python C extensions to speed up processing of data that takes a long time to load into memory. To avoid reloading the data every time I change my processing code, I use a Jupyter notebook - where I can keep this data available in memory and work interactively with it. Now - another roadblock: Python C extensions can't be unloaded once they have been loaded by CPython (meaning I can't use Importantly, using a forked subprocess means that it will have access to the data without having to reload it, and that the C extension import won't propagate up to the parent - essentially allowing me to hot reload the c extension by paying a small price of the fork-syscall and rerunning the import on every invocation of the C extension. So all of this works great - except when the C code segfaults or otherwise exits unexpectedly, which inevitably happens every now and then when working iteratively on C-code - execution will just hang, waiting for a result until I trigger a KeyboardInterrupt. This makes rerunning tests/benchmarks inconvenient - and harder to debug. data = load_data_for_5_minutes()import multiprocessing as mp
from functools import wraps
import traceback
import sys
def forked(fn):
@wraps(fn)
def call(*args, **kwargs):
ctx = mp.get_context('fork')
q = ctx.Queue(1)
def target():
try:
q.put((fn(*args, **kwargs), None))
except BaseException:
ex_type, ex_value, tb = sys.exc_info()
error = ex_type, ex_value, ''.join(traceback.format_tb(tb.tb_next))
q.put((None, error))
ctx.Process(target=target).start()
result, error = q.get()
if error:
ex_type, ex_value, trace = error
raise ex_type(f'{ex_value}\n {trace}')
return result
return call
@forked
def aggregate_data(data):
import mycextension
return mycextension.aggregate(data)
processed_data = aggregate_data(data) |
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Actually, I managed to solve it for my particular use case a bit more quickly than I expected: def forked(fn):
@wraps(fn)
def call(*args, **kwargs):
ctx = mp.get_context('fork')
q = ctx.Queue(1)
def target():
try:
q.put((fn(*args, **kwargs), None))
except BaseException:
ex_type, ex_value, tb = sys.exc_info()
error = ex_type, ex_value, ''.join(traceback.format_tb(tb.tb_next))
q.put((None, error))
p = ctx.Process(target=target) #
p.start() #
p.join() # The join succeeds regardless of whether the process exited normally
if q.empty(): #
raise SystemExit(p.exitcode) # If the queue is empty, it means the process did not exit normally
result, error = q.get()
if error:
ex_type, ex_value, trace = error
raise ex_type(f'{ex_value}\n {trace}')
return result
return callThis solution sadly doesn't help with multiprocessing.Pool though, since this uses workers that live longer than a single task - and so join can't be used to wait for a single result. I'll leave my solution here in case someone finds it useful - although it doesn't actually solve this issue. |
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What is the current status of this issue. Did we solve the parent processing hanging issue? |
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Ditto. In short, should the community continue to prefer We'd all like to believe that this issue has been quietly resolved; it's been nearly a decade and |
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To my knowledge, noone has been working actively on making |
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I have a solution to this but I'm not really willing to go through the whole process to make it into a pull request. I'm happy to share it in a gist if someone's interested in writing the unit tests and developing it into a PR. Basically, any solution that can report error from a processing pool when a worker dies should account for the partially executed tasks, whether it's a |
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Here's my solution: dobos@281291a |
Prior to this commit, `core.run` would wait for results indefinitely when a child process terminated with a non-zero exit code (e.g., segfault). This was due to the fact that `multiprocessing.Pool` does not raise an exception ( python/cpython#66587 ). This commit replaces `multiprocessing.Pool` with `concurrent.futures.ProcessPoolExecutor`. In contrast to the former, the latter raises an exception in case a child process terminates with a non-zero exit code.
Prior to this commit, `core.run` would wait for results indefinitely when a child process terminated with a non-zero exit code (e.g., segfault). This was due to the fact that `multiprocessing.Pool` does not raise an exception ( python/cpython#66587 ). This commit replaces `multiprocessing.Pool` with `concurrent.futures.ProcessPoolExecutor`. In contrast to the former, the latter raises an exception in case a child process terminates with a non-zero exit code.
Prior to this commit, `core.run` would wait for results indefinitely when a child process terminated with a non-zero exit code (e.g., segfault). This was due to the fact that `multiprocessing.Pool` does not raise an exception ( python/cpython#66587 ). This commit replaces `multiprocessing.Pool` with `concurrent.futures.ProcessPoolExecutor`. In contrast to the former, the latter raises an exception in case a child process terminates with a non-zero exit code.
Revert from `concurrent.futures.ProcessPoolExecutor` to `multiprocessing`. The former introduced a significant performance regression (about x2 slowdown). See https://stackoverflow.com/questions/18671528/processpoolexecutor-from-concurrent-futures-way-slower-than-multiprocessing-pool?rq=3. Unfortunately, `multiprocessing` cannot catch segfaults. Catching segfaults was the reason to replace `multiprocessing` with `ProcessPoolExecutor`. See python/cpython#66587. As a workaround, to avoid indefinite waiting for results in case of a segfault, we use a timeout.
…here a sub-process crashes. References python/cpython#66587
…here a sub-process crashes. References python/cpython#66587
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