view mercurial/worker.py @ 21204:1d7a2771aa36 stable

revset: inline spanset containment check (fix perf regression) Calling a function is super expensive in python. We inline the trivial range comparison to get back to more sensible performance on common revset operation. Benchmark result below: Revision mapping: 0) 3f83fc5cfe71 2.9.2 release 1) bcfd44abad93 current @ 2) This revision revset #0: public() 0) wall 0.010890 comb 0.010000 user 0.010000 sys 0.000000 (best of 201) 1) wall 0.012109 comb 0.010000 user 0.010000 sys 0.000000 (best of 199) 2) wall 0.012211 comb 0.020000 user 0.020000 sys 0.000000 (best of 197) revset #1: :10000 and public() 0) wall 0.007141 comb 0.010000 user 0.010000 sys 0.000000 (best of 361) 1) wall 0.014139 comb 0.010000 user 0.010000 sys 0.000000 (best of 186) 2) wall 0.008334 comb 0.010000 user 0.010000 sys 0.000000 (best of 308) revset #2: draft() 0) wall 0.009610 comb 0.010000 user 0.010000 sys 0.000000 (best of 279) 1) wall 0.010942 comb 0.010000 user 0.010000 sys 0.000000 (best of 243) 2) wall 0.011036 comb 0.010000 user 0.010000 sys 0.000000 (best of 239) revset #3: :10000 and draft() 0) wall 0.006852 comb 0.010000 user 0.010000 sys 0.000000 (best of 383) 1) wall 0.014641 comb 0.010000 user 0.010000 sys 0.000000 (best of 183) 2) wall 0.008314 comb 0.010000 user 0.010000 sys 0.000000 (best of 299) We can see this changeset gains back the regression for `and` operation on spanset. We are still a bit slowerfor the `public()` and `draft()`. Predicates not touched by this changeset.
author Pierre-Yves David <pierre-yves.david@fb.com>
date Mon, 28 Apr 2014 15:15:36 -0700
parents 1e5b38a919dd
children b3e51675f98e
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 _ 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]