util: make nogc effective for CPython
279cd80059d4 made `util.nogc` a no-op. It was to optimize PyPy. But it slows
down CPython if many objects (like 300k+) are created.
For example, running `hg log -r .` without extensions in `hg-committed` with
14k+ obsmarkers have the following times:
before | after
hg | chg | hg | chg
-----------------------------
1.262 | 0.860 | 1.077 | 0.619 (seconds, best of 20 runs)
Therefore let's re-enable nogc for CPython.
Differential Revision: https://phab.mercurial-scm.org/D402
# 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
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.osname == '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 = 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)
if pycompat.osname != 'nt':
_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]