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30913031d4
The home of 'Abort' is 'error' not 'util' however, a lot of code seems to be confused about that and gives all the credit to 'util' instead of the hardworking 'error'. In a spirit of equity, we break the cycle of injustice and give back to 'error' the respect it deserves. And screw that 'util' poser. For great justice.
185 lines
5.7 KiB
Python
185 lines
5.7 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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from .i18n import _
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from . import error
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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('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(os.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 os.name == 'posix':
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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):
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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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'''
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if worthwhile(ui, costperarg, len(args)):
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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 = [], [0]
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for pargs in partition(args, workers):
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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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try:
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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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os._exit(0)
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except KeyboardInterrupt:
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os._exit(255)
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# other exceptions are allowed to propagate, we rely
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# on lock.py's pid checks to avoid release callbacks
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pids.append(pid)
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pids.reverse()
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os.close(wfd)
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fp = os.fdopen(rfd, 'rb', 0)
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def killworkers():
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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():
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for _pid in pids:
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st = _exitstatus(os.wait()[1])
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if st and not problem[0]:
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problem[0] = st
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killworkers()
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t = threading.Thread(target=waitforworkers)
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t.start()
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def cleanup():
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signal.signal(signal.SIGINT, oldhandler)
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t.join()
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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 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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if os.name != 'nt':
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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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