Mercurial > hg
view mercurial/worker.py @ 24120:a450e0a2ba0a
revlog: in addgroup, reject ill-formed deltas based on censored nodes
To ensure interoperability when clones disagree about which file nodes are
censored, a restriction is made on deltas based on censored nodes. Any such
delta must replace the full text of the base in a single patch.
If the recipient of a delta considers the base to be censored and the delta
is not in the expected form, the recipient must reject it, as it can't know
if the source has also censored the base.
For background and broader design of the censorship feature, see:
http://mercurial.selenic.com/wiki/CensorPlan
author | Mike Edgar <adgar@google.com> |
---|---|
date | Fri, 06 Feb 2015 00:55:29 +0000 |
parents | b3e51675f98e |
children | 328739ea70c3 |
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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 i18n import _ import errno, os, signal, sys, threading import util 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 util.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, 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]