mercurial/worker.py
author Anton Shestakov <av6@dwimlabs.net>
Thu, 31 Mar 2016 18:09:09 +0800
changeset 28709 94494031f659
parent 28292 3eb7faf6d958
child 30396 78a58dcf8853
permissions -rw-r--r--
hgweb: add parents to json-log (issue5074) Entries prepared in webutil.changelistentry() skip showing parents in the trivial case when there's only one parent and it's the previous revision. This doesn't work well for the json-log template, which is supposed to just dump raw data in an easy-to-parse format, so let's provide all parents as another keyword: allparents. Using a lambda function here means that the performance of templates that don't use allparents won't be affected (see 41957e50e109).
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# worker.py - master-slave parallelism support
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#
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# Copyright 2013 Facebook, Inc.
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#
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# This software may be used and distributed according to the terms of the
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# GNU General Public License version 2 or any later version.
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from __future__ import absolute_import
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import errno
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import os
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import signal
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import sys
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import threading
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from .i18n import _
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from . import error
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def countcpus():
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    '''try to count the number of CPUs on the system'''
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    # posix
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    try:
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        n = int(os.sysconf('SC_NPROCESSORS_ONLN'))
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        if n > 0:
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            return n
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    except (AttributeError, ValueError):
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        pass
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    # windows
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    try:
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        n = int(os.environ['NUMBER_OF_PROCESSORS'])
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        if n > 0:
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            return n
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    except (KeyError, ValueError):
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        pass
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    return 1
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def _numworkers(ui):
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    s = ui.config('worker', 'numcpus')
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    if s:
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        try:
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            n = int(s)
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            if n >= 1:
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                return n
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        except ValueError:
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            raise error.Abort(_('number of cpus must be an integer'))
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    return min(max(countcpus(), 4), 32)
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if os.name == 'posix':
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    _startupcost = 0.01
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else:
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    _startupcost = 1e30
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def worthwhile(ui, costperop, nops):
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    '''try to determine whether the benefit of multiple processes can
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    outweigh the cost of starting them'''
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    linear = costperop * nops
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    workers = _numworkers(ui)
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    benefit = linear - (_startupcost * workers + linear / workers)
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    return benefit >= 0.15
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def worker(ui, costperarg, func, staticargs, args):
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    '''run a function, possibly in parallel in multiple worker
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    processes.
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    returns a progress iterator
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    costperarg - cost of a single task
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    func - function to run
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    staticargs - arguments to pass to every invocation of the function
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    args - arguments to split into chunks, to pass to individual
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    workers
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    '''
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    if worthwhile(ui, costperarg, len(args)):
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        return _platformworker(ui, func, staticargs, args)
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    return func(*staticargs + (args,))
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def _posixworker(ui, func, staticargs, args):
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    rfd, wfd = os.pipe()
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    workers = _numworkers(ui)
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    oldhandler = signal.getsignal(signal.SIGINT)
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    signal.signal(signal.SIGINT, signal.SIG_IGN)
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    pids, problem = [], [0]
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    for pargs in partition(args, workers):
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        pid = os.fork()
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        if pid == 0:
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            signal.signal(signal.SIGINT, oldhandler)
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            try:
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                os.close(rfd)
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                for i, item in func(*(staticargs + (pargs,))):
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                    os.write(wfd, '%d %s\n' % (i, item))
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                os._exit(0)
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            except KeyboardInterrupt:
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                os._exit(255)
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                # other exceptions are allowed to propagate, we rely
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                # on lock.py's pid checks to avoid release callbacks
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        pids.append(pid)
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    pids.reverse()
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    os.close(wfd)
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    fp = os.fdopen(rfd, 'rb', 0)
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    def killworkers():
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        # if one worker bails, there's no good reason to wait for the rest
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        for p in pids:
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            try:
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                os.kill(p, signal.SIGTERM)
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            except OSError as err:
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                if err.errno != errno.ESRCH:
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                    raise
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    def waitforworkers():
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        for _pid in pids:
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            st = _exitstatus(os.wait()[1])
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            if st and not problem[0]:
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                problem[0] = st
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                killworkers()
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    t = threading.Thread(target=waitforworkers)
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    t.start()
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    def cleanup():
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        signal.signal(signal.SIGINT, oldhandler)
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        t.join()
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        status = problem[0]
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        if status:
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            if status < 0:
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                os.kill(os.getpid(), -status)
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            sys.exit(status)
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    try:
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        for line in fp:
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            l = line.split(' ', 1)
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            yield int(l[0]), l[1][:-1]
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    except: # re-raises
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        killworkers()
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        cleanup()
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        raise
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    cleanup()
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def _posixexitstatus(code):
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    '''convert a posix exit status into the same form returned by
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    os.spawnv
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    returns None if the process was stopped instead of exiting'''
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    if os.WIFEXITED(code):
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        return os.WEXITSTATUS(code)
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    elif os.WIFSIGNALED(code):
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        return -os.WTERMSIG(code)
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if os.name != 'nt':
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    _platformworker = _posixworker
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    _exitstatus = _posixexitstatus
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def partition(lst, nslices):
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    '''partition a list into N slices of roughly equal size
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    The current strategy takes every Nth element from the input. If
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    we ever write workers that need to preserve grouping in input
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    we should consider allowing callers to specify a partition strategy.
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    mpm is not a fan of this partitioning strategy when files are involved.
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    In his words:
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        Single-threaded Mercurial makes a point of creating and visiting
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        files in a fixed order (alphabetical). When creating files in order,
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        a typical filesystem is likely to allocate them on nearby regions on
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        disk. Thus, when revisiting in the same order, locality is maximized
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        and various forms of OS and disk-level caching and read-ahead get a
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        chance to work.
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        This effect can be quite significant on spinning disks. I discovered it
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        circa Mercurial v0.4 when revlogs were named by hashes of filenames.
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        Tarring a repo and copying it to another disk effectively randomized
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        the revlog ordering on disk by sorting the revlogs by hash and suddenly
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        performance of my kernel checkout benchmark dropped by ~10x because the
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        "working set" of sectors visited no longer fit in the drive's cache and
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        the workload switched from streaming to random I/O.
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        What we should really be doing is have workers read filenames from a
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        ordered queue. This preserves locality and also keeps any worker from
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        getting more than one file out of balance.
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    '''
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    for i in range(nslices):
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        yield lst[i::nslices]