Fix #2177: Remove parallel hangs

This commit is contained in:
Daniel Rings 2015-12-16 15:10:52 +00:00 committed by Georg Brandl
parent d044268d60
commit 8d373b9ab1
3 changed files with 53 additions and 57 deletions

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@ -55,6 +55,7 @@ Release 1.3.3 (released Dec 2, 2015)
Bugs fixed
----------
* #2177: Fix parallel hangs
* #2012: Fix exception occurred if ``numfig_format`` is invalid
* #2142: Provide non-minified JS code in ``sphinx/search/non-minified-js/*.js`` for
source distribution on PyPI.

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@ -14,9 +14,8 @@ from os import path
try:
import multiprocessing
import threading
except ImportError:
multiprocessing = threading = None
multiprocessing = None
from docutils import nodes

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@ -14,11 +14,10 @@ import traceback
try:
import multiprocessing
import threading
except ImportError:
multiprocessing = threading = None
multiprocessing = None
from six.moves import queue
from math import sqrt
from sphinx.errors import SphinxParallelError
@ -49,17 +48,22 @@ class ParallelTasks(object):
def __init__(self, nproc):
self.nproc = nproc
# list of threads to join when waiting for completion
# main task performed by each task, returning result
self._task_func = 0
# (optional) function performed by each task on the result of main task
self._result_func = 0
# task arguments
self._args = {}
# list of subprocesses (both started and waiting)
self._procs = {}
# list of receiving pipe connections of running subprocesses
self._precvs = {}
# list of receiving pipe connections of waiting subprocesses
self._precvsWaiting = {}
# number of working subprocesses
self._pworking = 0
# task number of each subprocess
self._taskid = 0
self._threads = {}
self._nthreads = 0
# queue of result objects to process
self.result_queue = queue.Queue()
self._nprocessed = 0
# maps tasks to result functions
self._result_funcs = {}
# allow only "nproc" worker processes at once
self._semaphore = threading.Semaphore(self.nproc)
def _process(self, pipe, func, arg):
try:
@ -71,55 +75,44 @@ class ParallelTasks(object):
except BaseException as err:
pipe.send((True, (err, traceback.format_exc())))
def _process_thread(self, tid, func, arg):
precv, psend = multiprocessing.Pipe(False)
proc = multiprocessing.Process(target=self._process,
args=(psend, func, arg))
proc.start()
result = precv.recv()
self.result_queue.put((tid, arg) + result)
proc.join()
self._semaphore.release()
def _result_func_wrapper(self, arg, result):
result_func = self._result_func(arg, result)
if result_func:
result_func(result)
def add_task(self, task_func, arg=None, result_func=None):
self._task_func = task_func # dummy code after first call
self._result_func = result_func or (lambda *x: None) # dummy code after first call
tid = self._taskid
self._taskid += 1
self._semaphore.acquire()
thread = threading.Thread(target=self._process_thread,
args=(tid, task_func, arg))
thread.setDaemon(True)
thread.start()
self._nthreads += 1
self._threads[tid] = thread
self._result_funcs[tid] = result_func or (lambda *x: None)
# try processing results already in parallel
try:
tid, arg, exc, result = self.result_queue.get(False)
except queue.Empty:
pass
self._args[tid] = arg
precv, psend = multiprocessing.Pipe(False)
proc = multiprocessing.Process(target=self._process,
args=(psend, self._task_func, arg))
self._procs[tid] = proc
if self._pworking < self.nproc:
self._precvs[tid] = precv
self._pworking += 1
proc.start()
else:
del self._threads[tid]
if exc:
raise SphinxParallelError(*result)
result_func = self._result_funcs.pop(tid)(arg, result)
if result_func:
result_func(result)
self._nprocessed += 1
self._precvsWaiting[tid] = precv
def join(self):
while self._nprocessed < self._nthreads:
tid, arg, exc, result = self.result_queue.get()
del self._threads[tid]
if exc:
raise SphinxParallelError(*result)
result_func = self._result_funcs.pop(tid)(arg, result)
if result_func:
result_func(result)
self._nprocessed += 1
# there shouldn't be any threads left...
for t in self._threads.values():
t.join()
while self._pworking:
for tid, pipe in self._precvs.items():
if pipe.poll():
exc, result = pipe.recv()
if exc:
raise SphinxParallelError(*result)
self._result_func_wrapper(self._args[tid], result)
self._procs[tid].join()
if len(self._precvsWaiting) > 0:
newtid, newprecv = self._precvsWaiting.popitem()
self._precvs[newtid] = newprecv
self._procs[newtid].start()
break
else:
self._pworking -= 1
def make_chunks(arguments, nproc, maxbatch=10):
@ -128,6 +121,9 @@ def make_chunks(arguments, nproc, maxbatch=10):
chunksize = min(nargs // nproc, maxbatch)
if chunksize == 0:
chunksize = 1
if chunksize == maxbatch:
# try to improve batch size vs. number of batches
chunksize = int(sqrt(nargs/nproc * maxbatch))
nchunks, rest = divmod(nargs, chunksize)
if rest:
nchunks += 1