view mercurial/worker.py @ 25527:262e6ad93885

phases: really fix native phase computation For some reason (probably rebase issue, leprechaun or badly resolved .rej) 1635579f9baf contains only half of the emailed patches and do not fix the bug. This patch adds the other half and enable the sweet native computation for real. As expected this provide massive speedup along the board. revset #0: not public() plain first 0) 0.011960 0.010523 1) 0.000465 3% 0.000492 4% revset #1: (tip~1000::) - public() plain first 0) 0.025700 0.025169 1) 0.002864 11% 0.001899 7% revset #2: not public() and branch("default") plain first 0) 0.022842 0.020863 1) 0.011418 49% 0.010948 52% However, it has a less impact (even bad) on first result time in simple situation. This comes from the overhead of building the set and filtering it. This is especially true on my Mercurial repository (used here) where about 1/3 of the changesets are non public and hidden. This could be mitigated by a caching of the set and a better usage of smartset in '_notpublic'. (But this won't happen in this patch because the win is massive everywhere else). revset #0: not public() last 0) 0.000081 1) 0.000493 x6.1 <-- bad impact revset #1: (tip~1000::) - public() last 0) 0.013966 1) 0.002737 19% revset #2: not public() and branch("default") last 0) 0.011021 1) 0.011038 The effect mostly disappear when the number of non-public changesets is small and/or the repo get bigger. Result for Mozilla central: Mozilla revset #0: not public() plain first last 0) 0.092787 0.084094 0.000080 1) 0.000054 0% 0.000083 0% 0.000083 revset #1: (tip~1000::) - public() plain first last 0) 0.215607 0.183996 0.124962 1) 0.031620 14% 0.006616 3% 0.031168 24% revset #2: not public() and branch("default") plain first last 0) 0.092626 0.082687 0.000162 1) 0.000139 0% 0.000165 0% 0.000167
author Pierre-Yves David <pierre-yves.david@fb.com>
date Wed, 10 Jun 2015 19:26:16 -0700
parents b3e51675f98e
children 328739ea70c3
line wrap: on
line source

# 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]