nodemap: only use persistent nodemap for non-inlined revlog
Revlog are inlined while they are small (to avoid having too many file to deal
with). The persistent nodemap will only provides a significant boost for large
enough revlog index. So it does not make sens to add an extra file to store
nodemap for small revlog.
We could consider inclining the nodemap data inside the revlog itself, but the
benefit is unclear so let it be an adventure for another time.
Differential Revision: https://phab.mercurial-scm.org/D7837
# profiling.py - profiling functions
#
# Copyright 2016 Gregory Szorc <gregory.szorc@gmail.com>
#
# 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, print_function
import contextlib
from .i18n import _
from .pycompat import (
getattr,
open,
)
from . import (
encoding,
error,
extensions,
pycompat,
util,
)
def _loadprofiler(ui, profiler):
"""load profiler extension. return profile method, or None on failure"""
extname = profiler
extensions.loadall(ui, whitelist=[extname])
try:
mod = extensions.find(extname)
except KeyError:
return None
else:
return getattr(mod, 'profile', None)
@contextlib.contextmanager
def lsprofile(ui, fp):
format = ui.config(b'profiling', b'format')
field = ui.config(b'profiling', b'sort')
limit = ui.configint(b'profiling', b'limit')
climit = ui.configint(b'profiling', b'nested')
if format not in [b'text', b'kcachegrind']:
ui.warn(_(b"unrecognized profiling format '%s' - Ignored\n") % format)
format = b'text'
try:
from . import lsprof
except ImportError:
raise error.Abort(
_(
b'lsprof not available - install from '
b'http://codespeak.net/svn/user/arigo/hack/misc/lsprof/'
)
)
p = lsprof.Profiler()
p.enable(subcalls=True)
try:
yield
finally:
p.disable()
if format == b'kcachegrind':
from . import lsprofcalltree
calltree = lsprofcalltree.KCacheGrind(p)
calltree.output(fp)
else:
# format == 'text'
stats = lsprof.Stats(p.getstats())
stats.sort(pycompat.sysstr(field))
stats.pprint(limit=limit, file=fp, climit=climit)
@contextlib.contextmanager
def flameprofile(ui, fp):
try:
from flamegraph import flamegraph # pytype: disable=import-error
except ImportError:
raise error.Abort(
_(
b'flamegraph not available - install from '
b'https://github.com/evanhempel/python-flamegraph'
)
)
# developer config: profiling.freq
freq = ui.configint(b'profiling', b'freq')
filter_ = None
collapse_recursion = True
thread = flamegraph.ProfileThread(
fp, 1.0 / freq, filter_, collapse_recursion
)
start_time = util.timer()
try:
thread.start()
yield
finally:
thread.stop()
thread.join()
print(
b'Collected %d stack frames (%d unique) in %2.2f seconds.'
% (
util.timer() - start_time,
thread.num_frames(),
thread.num_frames(unique=True),
)
)
@contextlib.contextmanager
def statprofile(ui, fp):
from . import statprof
freq = ui.configint(b'profiling', b'freq')
if freq > 0:
# Cannot reset when profiler is already active. So silently no-op.
if statprof.state.profile_level == 0:
statprof.reset(freq)
else:
ui.warn(_(b"invalid sampling frequency '%s' - ignoring\n") % freq)
track = ui.config(
b'profiling', b'time-track', pycompat.iswindows and b'cpu' or b'real'
)
statprof.start(mechanism=b'thread', track=track)
try:
yield
finally:
data = statprof.stop()
profformat = ui.config(b'profiling', b'statformat')
formats = {
b'byline': statprof.DisplayFormats.ByLine,
b'bymethod': statprof.DisplayFormats.ByMethod,
b'hotpath': statprof.DisplayFormats.Hotpath,
b'json': statprof.DisplayFormats.Json,
b'chrome': statprof.DisplayFormats.Chrome,
}
if profformat in formats:
displayformat = formats[profformat]
else:
ui.warn(_(b'unknown profiler output format: %s\n') % profformat)
displayformat = statprof.DisplayFormats.Hotpath
kwargs = {}
def fraction(s):
if isinstance(s, (float, int)):
return float(s)
if s.endswith(b'%'):
v = float(s[:-1]) / 100
else:
v = float(s)
if 0 <= v <= 1:
return v
raise ValueError(s)
if profformat == b'chrome':
showmin = ui.configwith(fraction, b'profiling', b'showmin', 0.005)
showmax = ui.configwith(fraction, b'profiling', b'showmax')
kwargs.update(minthreshold=showmin, maxthreshold=showmax)
elif profformat == b'hotpath':
# inconsistent config: profiling.showmin
limit = ui.configwith(fraction, b'profiling', b'showmin', 0.05)
kwargs['limit'] = limit
showtime = ui.configbool(b'profiling', b'showtime')
kwargs['showtime'] = showtime
statprof.display(fp, data=data, format=displayformat, **kwargs)
class profile(object):
"""Start profiling.
Profiling is active when the context manager is active. When the context
manager exits, profiling results will be written to the configured output.
"""
def __init__(self, ui, enabled=True):
self._ui = ui
self._output = None
self._fp = None
self._fpdoclose = True
self._flushfp = None
self._profiler = None
self._enabled = enabled
self._entered = False
self._started = False
def __enter__(self):
self._entered = True
if self._enabled:
self.start()
return self
def start(self):
"""Start profiling.
The profiling will stop at the context exit.
If the profiler was already started, this has no effect."""
if not self._entered:
raise error.ProgrammingError(b'use a context manager to start')
if self._started:
return
self._started = True
profiler = encoding.environ.get(b'HGPROF')
proffn = None
if profiler is None:
profiler = self._ui.config(b'profiling', b'type')
if profiler not in (b'ls', b'stat', b'flame'):
# try load profiler from extension with the same name
proffn = _loadprofiler(self._ui, profiler)
if proffn is None:
self._ui.warn(
_(b"unrecognized profiler '%s' - ignored\n") % profiler
)
profiler = b'stat'
self._output = self._ui.config(b'profiling', b'output')
try:
if self._output == b'blackbox':
self._fp = util.stringio()
elif self._output:
path = self._ui.expandpath(self._output)
self._fp = open(path, b'wb')
elif pycompat.iswindows:
# parse escape sequence by win32print()
class uifp(object):
def __init__(self, ui):
self._ui = ui
def write(self, data):
self._ui.write_err(data)
def flush(self):
self._ui.flush()
self._fpdoclose = False
self._fp = uifp(self._ui)
else:
self._fpdoclose = False
self._fp = self._ui.ferr
# Ensure we've flushed fout before writing to ferr.
self._flushfp = self._ui.fout
if proffn is not None:
pass
elif profiler == b'ls':
proffn = lsprofile
elif profiler == b'flame':
proffn = flameprofile
else:
proffn = statprofile
self._profiler = proffn(self._ui, self._fp)
self._profiler.__enter__()
except: # re-raises
self._closefp()
raise
def __exit__(self, exception_type, exception_value, traceback):
propagate = None
if self._profiler is not None:
self._uiflush()
propagate = self._profiler.__exit__(
exception_type, exception_value, traceback
)
if self._output == b'blackbox':
val = b'Profile:\n%s' % self._fp.getvalue()
# ui.log treats the input as a format string,
# so we need to escape any % signs.
val = val.replace(b'%', b'%%')
self._ui.log(b'profile', val)
self._closefp()
return propagate
def _closefp(self):
if self._fpdoclose and self._fp is not None:
self._fp.close()
def _uiflush(self):
if self._flushfp:
self._flushfp.flush()