Mercurial > hg
view mercurial/worker.py @ 24528:b538ae24aa97
manifestv2: implement slow readdelta() without revdiff
For manifest v2, revlog.revdiff() usually does not provide enough
information to produce a manifest. As a simple workaround, implement
readdelta() by reading both the old and the new manifest and use
manifest.diff() to find the difference. This is several times slower
than the current readdelta() for v1 manifests, but there seems to be
no other simple option, and this is still much faster than returning
the full manifest (at least for verify).
author | Martin von Zweigbergk <martinvonz@google.com> |
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date | Fri, 27 Mar 2015 20:41:30 -0700 |
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]