mercurial/worker.py

workers: implemented worker on windows

This change implements thread based worker on windows.
The handling of exception from within threads will happen in separate diff.

The worker is for now used in mercurial/merge.py and in lfs extension

After multiple tests and milions of files materiealized, thousands lfs fetched
it seems that neither merge.py nor lfs/blobstore.py is thread unsafe. I also
looked through the code and besides the backgroundfilecloser (handled in base
of this) things look good.

The performance boost of this on windows is

~50% for sparse --enable-profile
* Speedup of hg up/rebase - not exactly measured

Test Plan:
Ran 10s of hg sparse --enable-profile and --disable-profile operations on large profiles and verified that workers are running. Used sysinternals suite to see that all threads are spawned and run as they should

Run various other operations on the repo including update and rebase

Ran tests on CentOS and all tests that pass on @ pass here

Differential Revision: https://phab.mercurial-scm.org/D1458

# 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 (
    encoding,
    error,
    pycompat,
    scmutil,
    util,
)

def countcpus():
    '''try to count the number of CPUs on the system'''

    # posix
    try:
        n = int(os.sysconf(r'SC_NPROCESSORS_ONLN'))
        if n > 0:
            return n
    except (AttributeError, ValueError):
        pass

    # windows
    try:
        n = int(encoding.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 pycompat.isposix or pycompat.iswindows:
    _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 = set(), [0]
    def killworkers():
        # unregister SIGCHLD handler as all children will be killed. This
        # function shouldn't be interrupted by another SIGCHLD; otherwise pids
        # could be updated while iterating, which would cause inconsistency.
        signal.signal(signal.SIGCHLD, oldchldhandler)
        # 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(blocking=True):
        for pid in pids.copy():
            p = st = 0
            while True:
                try:
                    p, st = os.waitpid(pid, (0 if blocking else os.WNOHANG))
                    break
                except OSError as e:
                    if e.errno == errno.EINTR:
                        continue
                    elif e.errno == errno.ECHILD:
                        # child would already be reaped, but pids yet been
                        # updated (maybe interrupted just after waitpid)
                        pids.discard(pid)
                        break
                    else:
                        raise
            if not p:
                # skip subsequent steps, because child process should
                # be still running in this case
                continue
            pids.discard(p)
            st = _exitstatus(st)
            if st and not problem[0]:
                problem[0] = st
    def sigchldhandler(signum, frame):
        waitforworkers(blocking=False)
        if problem[0]:
            killworkers()
    oldchldhandler = signal.signal(signal.SIGCHLD, sigchldhandler)
    ui.flush()
    parentpid = os.getpid()
    for pargs in partition(args, workers):
        # make sure we use os._exit in all worker code paths. otherwise the
        # worker may do some clean-ups which could cause surprises like
        # deadlock. see sshpeer.cleanup for example.
        # override error handling *before* fork. this is necessary because
        # exception (signal) may arrive after fork, before "pid =" assignment
        # completes, and other exception handler (dispatch.py) can lead to
        # unexpected code path without os._exit.
        ret = -1
        try:
            pid = os.fork()
            if pid == 0:
                signal.signal(signal.SIGINT, oldhandler)
                signal.signal(signal.SIGCHLD, oldchldhandler)

                def workerfunc():
                    os.close(rfd)
                    for i, item in func(*(staticargs + (pargs,))):
                        os.write(wfd, '%d %s\n' % (i, item))
                    return 0

                ret = scmutil.callcatch(ui, workerfunc)
        except: # parent re-raises, child never returns
            if os.getpid() == parentpid:
                raise
            exctype = sys.exc_info()[0]
            force = not issubclass(exctype, KeyboardInterrupt)
            ui.traceback(force=force)
        finally:
            if os.getpid() != parentpid:
                try:
                    ui.flush()
                except: # never returns, no re-raises
                    pass
                finally:
                    os._exit(ret & 255)
        pids.add(pid)
    os.close(wfd)
    fp = os.fdopen(rfd, pycompat.sysstr('rb'), 0)
    def cleanup():
        signal.signal(signal.SIGINT, oldhandler)
        waitforworkers()
        signal.signal(signal.SIGCHLD, oldchldhandler)
        status = problem[0]
        if status:
            if status < 0:
                os.kill(os.getpid(), -status)
            sys.exit(status)
    try:
        for line in util.iterfile(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)

def _windowsworker(ui, func, staticargs, args):
    class Worker(threading.Thread):
        def __init__(self, taskqueue, resultqueue, func, staticargs,
                     group=None, target=None, name=None, verbose=None):
            threading.Thread.__init__(self, group=group, target=target,
                                      name=name, verbose=verbose)
            self._taskqueue = taskqueue
            self._resultqueue = resultqueue
            self._func = func
            self._staticargs = staticargs

        def run(self):
            while not self._taskqueue.empty():
                try:
                    args = self._taskqueue.get_nowait()
                    for res in self._func(*self._staticargs + (args,)):
                        self._resultqueue.put(res)
                except util.empty:
                    break

    workers = _numworkers(ui)
    threads = []
    resultqueue = util.queue()
    taskqueue = util.queue()
    # partition work to more pieces than workers to minimize the chance
    # of uneven distribution of large tasks between the workers
    for pargs in partition(args, workers * 20):
        taskqueue.put(pargs)
    for _i in range(workers):
        t = Worker(taskqueue, resultqueue, func, staticargs)
        threads.append(t)
        t.start()
    while any(t.is_alive() for t in threads):
        while not resultqueue.empty():
            yield resultqueue.get()
        t = threads[0]
        t.join(0.05)
        if not t.is_alive():
            threads.remove(t)
    while not resultqueue.empty():
        yield resultqueue.get()

if pycompat.iswindows:
    _platformworker = _windowsworker
else:
    _platformworker = _posixworker
    _exitstatus = _posixexitstatus

def partition(lst, nslices):
    '''partition a list into N slices of roughly equal size

    The current strategy takes every Nth element from the input. If
    we ever write workers that need to preserve grouping in input
    we should consider allowing callers to specify a partition strategy.

    mpm is not a fan of this partitioning strategy when files are involved.
    In his words:

        Single-threaded Mercurial makes a point of creating and visiting
        files in a fixed order (alphabetical). When creating files in order,
        a typical filesystem is likely to allocate them on nearby regions on
        disk. Thus, when revisiting in the same order, locality is maximized
        and various forms of OS and disk-level caching and read-ahead get a
        chance to work.

        This effect can be quite significant on spinning disks. I discovered it
        circa Mercurial v0.4 when revlogs were named by hashes of filenames.
        Tarring a repo and copying it to another disk effectively randomized
        the revlog ordering on disk by sorting the revlogs by hash and suddenly
        performance of my kernel checkout benchmark dropped by ~10x because the
        "working set" of sectors visited no longer fit in the drive's cache and
        the workload switched from streaming to random I/O.

        What we should really be doing is have workers read filenames from a
        ordered queue. This preserves locality and also keeps any worker from
        getting more than one file out of balance.
    '''
    for i in range(nslices):
        yield lst[i::nslices]