mirror of
https://github.com/facebook/sapling.git
synced 2024-10-08 07:49:11 +03:00
65ed20fe71
Summary: This diff adds the `callsite` parameter to worker.worker and checks whether the passed-in callsite is enabled in the worker.enablecallsites config flag. This change essentially enabled parallization for lfs prefetch, which is called during initial repo clone(when mercurial cache is clean). Since blobstore.py seems to be thread-safe, we could also anticipate similar improvements for the more generalized `hg udpate` case by batching files to download. Details see T37718264 Reviewed By: ikostia Differential Revision: D13284680 fbshipit-source-id: c3b825033a28344e19ba5ca1621b59fe7b46b322
359 lines
12 KiB
Python
359 lines
12 KiB
Python
# worker.py - master-slave parallelism support
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#
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# Copyright 2013 Facebook, Inc.
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#
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# This software may be used and distributed according to the terms of the
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# GNU General Public License version 2 or any later version.
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from __future__ import absolute_import
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import errno
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import os
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import signal
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import sys
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import threading
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import time
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from . import encoding, error, pycompat, scmutil, util
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from .i18n import _
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def countcpus():
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"""try to count the number of CPUs on the system"""
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# posix
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try:
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n = int(os.sysconf(r"SC_NPROCESSORS_ONLN"))
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if n > 0:
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return n
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except (AttributeError, ValueError):
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pass
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# windows
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try:
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n = int(encoding.environ["NUMBER_OF_PROCESSORS"])
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if n > 0:
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return n
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except (KeyError, ValueError):
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pass
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return 1
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def _numworkers(ui):
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s = ui.config("worker", "numcpus")
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if s:
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try:
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n = int(s)
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if n >= 1:
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return n
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except ValueError:
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raise error.Abort(_("number of cpus must be an integer"))
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return min(max(countcpus(), 4), 32)
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if pycompat.isposix or pycompat.iswindows:
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_startupcost = 0.01
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else:
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_startupcost = 1e30
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def worthwhile(ui, costperop, nops):
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"""try to determine whether the benefit of multiple processes can
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outweigh the cost of starting them"""
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linear = costperop * nops
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workers = _numworkers(ui)
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benefit = linear - (_startupcost * workers + linear / workers)
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return benefit >= 0.15
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def worker(ui, costperarg, func, staticargs, args, preferthreads=False, callsite=None):
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"""run a function, possibly in parallel in multiple worker
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processes.
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returns a progress iterator
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costperarg - cost of a single task
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func - function to run
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staticargs - arguments to pass to every invocation of the function
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args - arguments to split into chunks, to pass to individual
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workers
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preferthreads - use threads instead of processes
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callsite - where this worker function is being called
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"""
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workerenabled = ui.configbool("worker", "enabled")
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callsiteenabled = callsite in ui.configlist("worker", "_enabledcallsites")
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enabled = workerenabled or callsiteenabled
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if enabled and worthwhile(ui, costperarg, len(args)):
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if preferthreads:
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return _windowsworker(ui, func, staticargs, args)
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else:
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return _platformworker(ui, func, staticargs, args)
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return func(*staticargs + (args,))
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def _posixworker(ui, func, staticargs, args):
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rfd, wfd = os.pipe()
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workers = _numworkers(ui)
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oldhandler = signal.getsignal(signal.SIGINT)
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signal.signal(signal.SIGINT, signal.SIG_IGN)
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pids, problem = set(), [0]
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def killworkers():
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# unregister SIGCHLD handler as all children will be killed. This
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# function shouldn't be interrupted by another SIGCHLD; otherwise pids
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# could be updated while iterating, which would cause inconsistency.
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signal.signal(signal.SIGCHLD, oldchldhandler)
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# if one worker bails, there's no good reason to wait for the rest
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for p in pids:
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try:
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os.kill(p, signal.SIGTERM)
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except OSError as err:
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if err.errno != errno.ESRCH:
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raise
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def waitforworkers(blocking=True):
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for pid in pids.copy():
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p = st = 0
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while True:
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try:
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p, st = os.waitpid(pid, (0 if blocking else os.WNOHANG))
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break
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except OSError as e:
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if e.errno == errno.EINTR:
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continue
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elif e.errno == errno.ECHILD:
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# child would already be reaped, but pids yet been
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# updated (maybe interrupted just after waitpid)
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pids.discard(pid)
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break
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else:
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raise
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if not p:
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# skip subsequent steps, because child process should
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# be still running in this case
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continue
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pids.discard(p)
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st = _exitstatus(st)
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if st and not problem[0]:
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problem[0] = st
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def sigchldhandler(signum, frame):
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waitforworkers(blocking=False)
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if problem[0]:
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killworkers()
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oldchldhandler = signal.signal(signal.SIGCHLD, sigchldhandler)
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ui.flush()
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parentpid = os.getpid()
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for pargs in partition(args, workers):
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# make sure we use os._exit in all worker code paths. otherwise the
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# worker may do some clean-ups which could cause surprises like
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# deadlock. see sshpeer.cleanup for example.
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# override error handling *before* fork. this is necessary because
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# exception (signal) may arrive after fork, before "pid =" assignment
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# completes, and other exception handler (dispatch.py) can lead to
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# unexpected code path without os._exit.
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ret = -1
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try:
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pid = os.fork()
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if pid == 0:
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signal.signal(signal.SIGINT, oldhandler)
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signal.signal(signal.SIGCHLD, oldchldhandler)
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def workerfunc():
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os.close(rfd)
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for i, item in func(*(staticargs + (pargs,))):
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os.write(wfd, "%d %s\n" % (i, item))
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return 0
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ret = scmutil.callcatch(ui, workerfunc)
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except: # parent re-raises, child never returns
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if os.getpid() == parentpid:
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raise
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exctype = sys.exc_info()[0]
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force = not issubclass(exctype, KeyboardInterrupt)
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ui.traceback(force=force)
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finally:
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if os.getpid() != parentpid:
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try:
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ui.flush()
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except: # never returns, no re-raises
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pass
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finally:
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os._exit(ret & 255)
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pids.add(pid)
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os.close(wfd)
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fp = os.fdopen(rfd, pycompat.sysstr("rb"), 0)
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def cleanup():
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signal.signal(signal.SIGINT, oldhandler)
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waitforworkers()
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signal.signal(signal.SIGCHLD, oldchldhandler)
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status = problem[0]
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if status:
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if status < 0:
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os.kill(os.getpid(), -status)
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sys.exit(status)
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try:
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for line in util.iterfile(fp):
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l = line.split(" ", 1)
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yield int(l[0]), l[1][:-1]
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except: # re-raises
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killworkers()
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cleanup()
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raise
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cleanup()
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def _posixexitstatus(code):
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"""convert a posix exit status into the same form returned by
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os.spawnv
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returns None if the process was stopped instead of exiting"""
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if os.WIFEXITED(code):
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return os.WEXITSTATUS(code)
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elif os.WIFSIGNALED(code):
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return -os.WTERMSIG(code)
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def _windowsworker(ui, func, staticargs, args):
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class Worker(threading.Thread):
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def __init__(
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self,
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taskqueue,
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resultqueue,
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func,
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staticargs,
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group=None,
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target=None,
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name=None,
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verbose=None,
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):
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threading.Thread.__init__(
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self, group=group, target=target, name=name, verbose=verbose
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)
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self._taskqueue = taskqueue
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self._resultqueue = resultqueue
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self._func = func
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self._staticargs = staticargs
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self._interrupted = False
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self.daemon = True
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self.exception = None
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def interrupt(self):
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self._interrupted = True
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def run(self):
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try:
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while not self._taskqueue.empty():
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try:
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args = self._taskqueue.get_nowait()
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for res in self._func(*self._staticargs + (args,)):
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self._resultqueue.put(res)
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# threading doesn't provide a native way to
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# interrupt execution. handle it manually at every
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# iteration.
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if self._interrupted:
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return
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except util.empty:
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break
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except Exception as e:
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# store the exception such that the main thread can resurface
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# it as if the func was running without workers.
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self.exception = e
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raise
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threads = []
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def trykillworkers():
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# Allow up to 1 second to clean worker threads nicely
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cleanupend = time.time() + 1
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for t in threads:
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t.interrupt()
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for t in threads:
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remainingtime = cleanupend - time.time()
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t.join(remainingtime)
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if t.is_alive():
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# pass over the workers joining failure. it is more
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# important to surface the inital exception than the
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# fact that one of workers may be processing a large
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# task and does not get to handle the interruption.
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ui.warn(
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_("failed to kill worker threads while " "handling an exception\n")
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)
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return
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workers = _numworkers(ui)
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resultqueue = util.queue()
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taskqueue = util.queue()
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# partition work to more pieces than workers to minimize the chance
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# of uneven distribution of large tasks between the workers
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for pargs in partition(args, workers * 20):
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taskqueue.put(pargs)
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for _i in range(workers):
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t = Worker(taskqueue, resultqueue, func, staticargs)
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threads.append(t)
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t.start()
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try:
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while len(threads) > 0:
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while not resultqueue.empty():
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yield resultqueue.get()
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threads[0].join(0.05)
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finishedthreads = [_t for _t in threads if not _t.is_alive()]
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for t in finishedthreads:
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if t.exception is not None:
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raise t.exception
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threads.remove(t)
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except (Exception, KeyboardInterrupt): # re-raises
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trykillworkers()
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raise
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while not resultqueue.empty():
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yield resultqueue.get()
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if pycompat.iswindows:
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_platformworker = _windowsworker
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else:
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_platformworker = _posixworker
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_exitstatus = _posixexitstatus
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def partition(lst, nslices):
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"""partition a list into N slices of roughly equal size
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The current strategy takes every Nth element from the input. If
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we ever write workers that need to preserve grouping in input
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we should consider allowing callers to specify a partition strategy.
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mpm is not a fan of this partitioning strategy when files are involved.
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In his words:
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Single-threaded Mercurial makes a point of creating and visiting
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files in a fixed order (alphabetical). When creating files in order,
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a typical filesystem is likely to allocate them on nearby regions on
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disk. Thus, when revisiting in the same order, locality is maximized
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and various forms of OS and disk-level caching and read-ahead get a
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chance to work.
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This effect can be quite significant on spinning disks. I discovered it
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circa Mercurial v0.4 when revlogs were named by hashes of filenames.
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Tarring a repo and copying it to another disk effectively randomized
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the revlog ordering on disk by sorting the revlogs by hash and suddenly
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performance of my kernel checkout benchmark dropped by ~10x because the
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"working set" of sectors visited no longer fit in the drive's cache and
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the workload switched from streaming to random I/O.
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What we should really be doing is have workers read filenames from a
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ordered queue. This preserves locality and also keeps any worker from
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getting more than one file out of balance.
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"""
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for i in range(nslices):
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yield lst[i::nslices]
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