Mercurial > hg
view mercurial/worker.py @ 29861:2f6d5c60f6fc stable
annotate: pre-calculate the "needed" dictionary (issue5360)
The "needed" dict is used as a reference counter to free items in the giant
"hist" dict. However, currently it is not very accurate and can lead to
dropping "hist" items unnecessarily, for example, with the following DAG,
-3-
/ \
0--1--2--4--
The current algorithm will visit and calculate rev 1 twice, undesired. And
it tries to be smart by clearing rev 1's parents: "pcache[1] = []" at the
time hist[1] being accessed (note: hist[1] needs to be used twice, by rev 2
and rev 3). It can result in incorrect results if p1 of rev 4 deletes chunks
belonging to rev 0.
However, simply removing "needed" is not okay, because it will consume 10x
memory:
# without any change
% HGRCPATH= lrun ./hg annotate mercurial/commands.py -r d130a38 3>&2 [1]
MEMORY 49074176
CPUTIME 9.213
REALTIME 9.270
# with "needed" removed
MEMORY 637673472
CPUTIME 8.164
REALTIME 8.249
This patch moves "needed" (and "pcache") calculation to a separate DFS to
address the issue. It improves perf and fixes issue5360 by correctly reusing
hist, while maintaining low memory usage. Some additional attempt has been
made to further reduce memory usage, like changing "pcache[f] = []" to "del
pcache[f]". Therefore the result can be both faster and lower memory usage:
# with this patch applied
MEMORY 47575040
CPUTIME 7.870
REALTIME 7.926
[1]: lrun is a lightweight sandbox built on Linux cgroup and namespace. It's
used to measure CPU and memory usage here. Source code is available at
github.com/quark-zju/lrun.
author | Jun Wu <quark@fb.com> |
---|---|
date | Fri, 02 Sep 2016 15:20:59 +0100 |
parents | 3eb7faf6d958 |
children | 78a58dcf8853 |
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# 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]