##// END OF EJS Templates
streamclone: clear caches after writing changes into files for visibility...
streamclone: clear caches after writing changes into files for visibility Before this patch, streamclone-ed changes are invisible via @filecache properties to in-process procedures before closing transaction (e.g. pretxnclose python hook), if corresponded property is cached before consumev1(). Strictly speaking, caching should occur inside (store) lock for transaction. repo.invalidate() after closing transaction is too late to force @filecache properties to be reloaded from changed files at next access. For visibility of streamclone-ed changes to in-process procedures before closing transaction, this patch clears caches just after writing changes into files. BTW, regardless of changing in this patch, clearing cached properties in consumev1() causes inconsistency, if (1) transaction is started and (2) any @filecache property is changed before consumev1(). This patch also adds the comment to fix this (potential) inconsistency in the future.

File last commit:

r28292:3eb7faf6 default
r29919:519a0226 default
Show More
worker.py
184 lines | 5.7 KiB | text/x-python | PythonLexer
# 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 error
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 error.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 as err:
if err.errno != errno.ESRCH:
raise
def waitforworkers():
for _pid 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 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]