Mercurial > hg
view mercurial/worker.py @ 27072:e18a9ceade3b
perf: support obtaining contexts from perfrevset
Previously, perfrevset called repo.revs(), which only returns integer
revisions. Many revset consumers call repo.set(), which returns
changectx instances. Or they obtain a context manually later.
Since obtaining changectx instances when evaluating revsets is common,
this patch adds support for benchmarking this use case.
While we added an if conditional for every benchmark loop, it
doesn't appear to matter since revset evaluation dwarfs the cost
of a single if.
author | Gregory Szorc <gregory.szorc@gmail.com> |
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date | Sat, 21 Nov 2015 15:39:18 -0800 |
parents | 56b2bcea2529 |
children | f8efc8a3a991 |
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# worker.py - master-slave parallelism support # # Copyright 2013 Facebook, Inc. # # This software may be used and distributed according to the terms of the # GNU General Public License version 2 or any later version. from __future__ import absolute_import import errno import os import signal import sys import threading from .i18n import _ from . import error def countcpus(): '''try to count the number of CPUs on the system''' # posix try: n = int(os.sysconf('SC_NPROCESSORS_ONLN')) if n > 0: return n except (AttributeError, ValueError): pass # windows try: n = int(os.environ['NUMBER_OF_PROCESSORS']) if n > 0: return n except (KeyError, ValueError): pass return 1 def _numworkers(ui): s = ui.config('worker', 'numcpus') if s: try: n = int(s) if n >= 1: return n except ValueError: raise error.Abort(_('number of cpus must be an integer')) return min(max(countcpus(), 4), 32) if os.name == 'posix': _startupcost = 0.01 else: _startupcost = 1e30 def worthwhile(ui, costperop, nops): '''try to determine whether the benefit of multiple processes can outweigh the cost of starting them''' linear = costperop * nops workers = _numworkers(ui) benefit = linear - (_startupcost * workers + linear / workers) return benefit >= 0.15 def worker(ui, costperarg, func, staticargs, args): '''run a function, possibly in parallel in multiple worker processes. returns a progress iterator costperarg - cost of a single task func - function to run staticargs - arguments to pass to every invocation of the function args - arguments to split into chunks, to pass to individual workers ''' if worthwhile(ui, costperarg, len(args)): return _platformworker(ui, func, staticargs, args) return func(*staticargs + (args,)) def _posixworker(ui, func, staticargs, args): rfd, wfd = os.pipe() workers = _numworkers(ui) oldhandler = signal.getsignal(signal.SIGINT) signal.signal(signal.SIGINT, signal.SIG_IGN) pids, problem = [], [0] for pargs in partition(args, workers): pid = os.fork() if pid == 0: signal.signal(signal.SIGINT, oldhandler) try: os.close(rfd) for i, item in func(*(staticargs + (pargs,))): os.write(wfd, '%d %s\n' % (i, item)) os._exit(0) except KeyboardInterrupt: os._exit(255) # other exceptions are allowed to propagate, we rely # on lock.py's pid checks to avoid release callbacks pids.append(pid) pids.reverse() os.close(wfd) fp = os.fdopen(rfd, 'rb', 0) def killworkers(): # if one worker bails, there's no good reason to wait for the rest for p in pids: try: os.kill(p, signal.SIGTERM) except OSError as err: if err.errno != errno.ESRCH: raise def waitforworkers(): for _pid in pids: st = _exitstatus(os.wait()[1]) if st and not problem[0]: problem[0] = st killworkers() t = threading.Thread(target=waitforworkers) t.start() def cleanup(): signal.signal(signal.SIGINT, oldhandler) t.join() status = problem[0] if status: if status < 0: os.kill(os.getpid(), -status) sys.exit(status) try: for line in fp: l = line.split(' ', 1) yield int(l[0]), l[1][:-1] except: # re-raises killworkers() cleanup() raise cleanup() def _posixexitstatus(code): '''convert a posix exit status into the same form returned by os.spawnv returns None if the process was stopped instead of exiting''' if os.WIFEXITED(code): return os.WEXITSTATUS(code) elif os.WIFSIGNALED(code): return -os.WTERMSIG(code) if os.name != 'nt': _platformworker = _posixworker _exitstatus = _posixexitstatus def partition(lst, nslices): '''partition a list into N slices of equal size''' n = len(lst) chunk, slop = n / nslices, n % nslices end = 0 for i in xrange(nslices): start = end end = start + chunk if slop: end += 1 slop -= 1 yield lst[start:end]