view mercurial/worker.py @ 39506:b66ea3fc3a86

sparse-revlog: set max delta chain length to on thousand The new snapshot system used in the sparse-revlog case gave us some small size benefit so far. However its most important property is to gracefully handle harder limit on delta chainlength. Long delta chain has a very detrimental impact on read (and write) performance in revlog. Being able to shorter them provide a great boost. However, shorting delta used to result significantly lower compression ratio. The intermediate snapshots effectively suppress most of this effect (even all in some case). # Effect on the test repository The repository we use for test is not "realistic" but can still show this in action using an unreasonably low chain limit. Limiting the chain length show a sizeable increase but stay under control: +6% for limit=15; +15% for limit=10. Without the snapshot system the increase is significantly bigger: +45% for limit=15; +80% for limit=10. Even slightly larger than without delta chain limit, the resulting size is still smaller than before we started doing snapshots. Here is a table for comparison. *Since the repository is not branchy, the initial sparse-revlog version does not bring much benefit compare to the non-sparse one): chain length limit | none | limit=15 | limit=10 | without sparse-revlog | 62 818 987 | 112 664 615 | 131 222 574 | without snapshot | 74 365 490 | 108 211 410 | 133 857 764 | with snapshot | 59 230 936 | 63 002 924 | 68 415 329 | # Effect On Real Life Repositories The series provides significant benefits on all kind of repositories. Using `hg debugupgraderepo -o redeltaparent --run`, we recomputed delta chain for various repositories with different settings: - delta chain length: unlimited or 1000 limit - sparse-revlog: enabled or disabled - this series: applied or not applied We can observe multiple types of effect: - On very branchy repositories: * The delta chain limit as low impact on the repo size. * Intermediate snapshot greatly reduces manifest size: - pypy: -80% - netbeans: -95% * The delta chain limit is effective, without a size impact: - netbeans average: 613 -> 282 - private #1 average: 1 068 -> 307 - On more linear repository: * Intermediate snapshot limit the impact of delta chain limit: - mozilla: without the series: +360% with the series: +25% * The delta chain limit provides large improvement: - mozilla's average chain length: unlimited: 15 338 limited: 469 * Despite the chain length limit, the manifest size is reduced: - mercurial: -25% - mozilla: -30% It is clear that the use of chains of intermediate snapshots provide large benefits both in storage size and delta chains quality. We should now switch our effort toward making sure the write performance are acceptable. Then, `sparse-revlog` will be a suitable format for all new repository. # Raw Statistic * no-sparse: general delta repository not using sparse-revlog * no-snapshot: sparse-revlog repository not using this series * snapshot: sparse-revlog repository using this series mercurial Manifest Size: limit | none | 1000 ------------|-------------|------------ no-sparse | 8 021 373 | 8 199 366 no-snapshot | 8 103 561 | 8 259 719 snapshot | 6 137 116 | 6 126 433 Manifest Chain length data limit || none || 1000 || value || average | max || average | max || ------------||---------|---------||---------|---------|| no-sparse || 307 | 1456 || 279 | 1000 || no-snapshot || 312 | 1456 || 283 | 1000 || snapshot || 248 | 1208 || 241 | 1000 || Full Store Size limit | none | 1000 ------------|-------------|------------ no-sparse | 51 013 198 | 51 201 574 no-snapshot | 50 930 795 | 51 141 006 snapshot | 48 072 037 | 48 093 572 pypy Manifest Size: limit | none | 1000 ------------|-------------|------------ no-sparse | 193 987 784 | 193 987 784 no-snapshot | 163 171 745 | 163 312 229 snapshot | 34 605 900 | 34 600 750 Manifest Chain length data limit || none || 1000 || value || average | max || average | max || ------------||---------|---------||---------|---------|| no-sparse || 101 | 692 || 101 | 692 || no-snapshot || 151 | 1307 || 148 | 1000 || snapshot || 128 | 1309 || 125 | 1000 || Full Store Size limit | none | 1000 ------------|-------------|------------ no-sparse | 495 931 473 | 495 931 473 no-snapshot | 465 441 017 | 465 581 501 snapshot | 355 467 301 | 355 472 451 Mozilla Manifest Size: limit | none | 1000 ------------|----------------|--------------- no-sparse | 416 757 148 | 1 869 009 668 no-snapshot | 401 592 370 | 1 843 493 795 snapshot | 224 359 521 | 284 615 500 Manifest Chain length data limit || none || 1000 || value || average | max || average | max || ------------||---------|---------||---------|---------|| no-sparse || 15 333 | 58 980 || 468 | 1 000 || no-snapshot || 15 336 | 58 980 || 469 | 1 000 || snapshot || 15 338 | 58 983 || 469 | 1 000 || Full Store Size limit | none | 1000 ------------|----------------|--------------- no-sparse | 2 712 477 887 | 4 164 995 451 no-snapshot | 2 698 887 835 | 4 141 054 304 snapshot | 2 518 130 385 | 2 578 587 596 Netbeans Manifest Size: limit | none | 1000 ------------|----------------|--------------- no-sparse | 4 766 794 101 | 4 870 642 687 no-snapshot | 4 334 806 082 | 4 428 681 309 snapshot | 232 659 666 | 240 330 665 Manifest Chain length data limit || none || 1000 || value || average | max || average | max || ------------||---------|---------||---------|---------|| no-sparse || 597 | 6802 || 254 | 1 000 || no-snapshot || 648 | 6 802 || 305 | 1 000 || snapshot || 613 | 6 804 || 282 | 1 000 || Full Store Size limit | none | 1000 ------------|----------------|--------------- no-sparse | 5 807 347 998 | 5 911 196 584 no-snapshot | 5 375 398 602 | 5 469 273 829 snapshot | 1 282 519 928 | 1 290 190 927 Private repo #1 Manifest Size: limit | none | 1000 ------------|-----------------|--------------- no-sparse | 41 389 010 840 | 41 398 162 091 no-snapshot | 9 737 319 435 | 10 223 773 150 snapshot | 744 215 807 | 747 961 822 Manifest Chain length data limit || none || 1000 || value || average | max || average | max || ------------||---------|---------||---------|---------|| no-sparse || 245 | 8 885 || 81 | 1 000 || no-snapshot || 1 225 | 8 885 || 336 | 1 000 || snapshot || 1 068 | 7 909 || 307 | 1 000 || Full Store Size limit | none | 1000 ------------|----------------|--------------- no-sparse | 49 646 065 126 | 49 655 216 377 no-snapshot | 17 924 862 856 | 18 411 316 571 snapshot | 9 009 024 710 | 9 012 770 725 Private repo #2 We currently have less data available for that repository. * Before is a sparse-revlog repository without this series * After is a sparse-revlog repository with this series + 1000 chain limit Manifest Size: Before: 1 531 485 040 bytes After: 1 091 422 451 bytes Manifest Chain: Before: 2 218 avg; 6 575 Max After: 442 avg; 1 000 Max Full Store Size Before: 15 203 955 615 after: 8 207 180 693
author Boris Feld <boris.feld@octobus.net>
date Fri, 07 Sep 2018 11:18:45 -0400
parents c08ea1e219c0
children 909c31805f54 03f7d0822ec1
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 __future__ import absolute_import

import errno
import os
import signal
import sys
import threading
import time

try:
    import selectors
    selectors.BaseSelector
except ImportError:
    from .thirdparty import selectors2 as selectors

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:
    _STARTUP_COST = 0.01
    # The Windows worker is thread based. If tasks are CPU bound, threads
    # in the presence of the GIL result in excessive context switching and
    # this overhead can slow down execution.
    _DISALLOW_THREAD_UNSAFE = pycompat.iswindows
else:
    _STARTUP_COST = 1e30
    _DISALLOW_THREAD_UNSAFE = False

def worthwhile(ui, costperop, nops, threadsafe=True):
    '''try to determine whether the benefit of multiple processes can
    outweigh the cost of starting them'''

    if not threadsafe and _DISALLOW_THREAD_UNSAFE:
        return False

    linear = costperop * nops
    workers = _numworkers(ui)
    benefit = linear - (_STARTUP_COST * workers + linear / workers)
    return benefit >= 0.15

def worker(ui, costperarg, func, staticargs, args, threadsafe=True):
    '''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

    threadsafe - whether work items are thread safe and can be executed using
    a thread-based worker. Should be disabled for CPU heavy tasks that don't
    release the GIL.
    '''
    enabled = ui.configbool('worker', 'enabled')
    if enabled and worthwhile(ui, costperarg, len(args), threadsafe=threadsafe):
        return _platformworker(ui, func, staticargs, args)
    return func(*staticargs + (args,))

def _posixworker(ui, func, staticargs, args):
    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()
    pipes = []
    for pargs in partition(args, workers):
        # Every worker gets its own pipe to send results on, so we don't have to
        # implement atomic writes larger than PIPE_BUF. Each forked process has
        # its own pipe's descriptors in the local variables, and the parent
        # process has the full list of pipe descriptors (and it doesn't really
        # care what order they're in).
        rfd, wfd = os.pipe()
        pipes.append((rfd, wfd))
        # 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():
                    for r, w in pipes[:-1]:
                        os.close(r)
                        os.close(w)
                    os.close(rfd)
                    for result in func(*(staticargs + (pargs,))):
                        os.write(wfd, util.pickle.dumps(result))
                    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)
    selector = selectors.DefaultSelector()
    for rfd, wfd in pipes:
        os.close(wfd)
        selector.register(os.fdopen(rfd, r'rb', 0), selectors.EVENT_READ)
    def cleanup():
        signal.signal(signal.SIGINT, oldhandler)
        waitforworkers()
        signal.signal(signal.SIGCHLD, oldchldhandler)
        selector.close()
        status = problem[0]
        if status:
            if status < 0:
                os.kill(os.getpid(), -status)
            sys.exit(status)
    try:
        openpipes = len(pipes)
        while openpipes > 0:
            for key, events in selector.select():
                try:
                    yield util.pickle.load(key.fileobj)
                except EOFError:
                    selector.unregister(key.fileobj)
                    key.fileobj.close()
                    openpipes -= 1
                except IOError as e:
                    if e.errno == errno.EINTR:
                        continue
                    raise
    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
            self._interrupted = False
            self.daemon = True
            self.exception = None

        def interrupt(self):
            self._interrupted = True

        def run(self):
            try:
                while not self._taskqueue.empty():
                    try:
                        args = self._taskqueue.get_nowait()
                        for res in self._func(*self._staticargs + (args,)):
                            self._resultqueue.put(res)
                            # threading doesn't provide a native way to
                            # interrupt execution. handle it manually at every
                            # iteration.
                            if self._interrupted:
                                return
                    except pycompat.queue.Empty:
                        break
            except Exception as e:
                # store the exception such that the main thread can resurface
                # it as if the func was running without workers.
                self.exception = e
                raise

    threads = []
    def trykillworkers():
        # Allow up to 1 second to clean worker threads nicely
        cleanupend = time.time() + 1
        for t in threads:
            t.interrupt()
        for t in threads:
            remainingtime = cleanupend - time.time()
            t.join(remainingtime)
            if t.is_alive():
                # pass over the workers joining failure. it is more
                # important to surface the inital exception than the
                # fact that one of workers may be processing a large
                # task and does not get to handle the interruption.
                ui.warn(_("failed to kill worker threads while "
                          "handling an exception\n"))
                return

    workers = _numworkers(ui)
    resultqueue = pycompat.queue.Queue()
    taskqueue = pycompat.queue.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()
    try:
        while len(threads) > 0:
            while not resultqueue.empty():
                yield resultqueue.get()
            threads[0].join(0.05)
            finishedthreads = [_t for _t in threads if not _t.is_alive()]
            for t in finishedthreads:
                if t.exception is not None:
                    raise t.exception
                threads.remove(t)
    except (Exception, KeyboardInterrupt): # re-raises
        trykillworkers()
        raise
    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]