view mercurial/profiling.py @ 40393:229d23cdb203

exchangev2: support fetching shallow files history This commit teaches the exchangev2 client code to handle fetching shallow files data. Only shallow fetching of files data is supported: shallow fetching of changeset and manifest data is explicitly not yet supported. Previously, we would fetch file revisions for changesets that were received by the current pull operation. In the new model, we calculate the set of "relevant" changesets given the pull depth and only fetch files data for those changesets. We also teach the "filesdata" command invocation to vary parameters as needed. The implementation here is far from complete or optimal. Subsequent pulls will end up re-fetching a lot of files data. But the application of this data should mostly be a no-op on the client, so it isn't a big deal. Depending on the order file revisions are fetched in, revisions could get inserted with the wrong revision number relationships. I think the best way to deal with this is to remove revision numbers from storage and to either dynamically derive them (by reconstructing a DAG from nodes/parents) or remove revision numbers from the file storage interface completely. A missing API that we'll likely want to write pretty soon is "ensure files for revision(s) are present." We can kind of cajole exchangev2.pull() to do this. But it isn't very efficient. For example, in simple cases like widening the store to obtain data for a single revision, it is probably more efficient to walk the manifest and find exactly which file revisions are missing and to make explicit requests for just their data. In more advanced cases, asking the server for all files data may be more efficient, even though it requires sending data the client already has. There is tons of room for future experimentation here. And TBH I'm not sure what the final state will be. Anyway, this commit gets us pretty close to being able to have shallow and narrow checkouts with exchangev2/sqlite storage. Close enough that a minimal extension should be able to provide fill in the gaps until the code in core stabilizes and there is a user-facing way to trigger the narrow/shallow bits from `hg clone` without also implying using of the narrow extension... Differential Revision: https://phab.mercurial-scm.org/D5169
author Gregory Szorc <gregory.szorc@gmail.com>
date Fri, 19 Oct 2018 12:30:49 +0200
parents b8f6a99ad89b
children 89703e6151e7
line wrap: on
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# 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 . 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('profiling', 'format')
    field = ui.config('profiling', 'sort')
    limit = ui.configint('profiling', 'limit')
    climit = ui.configint('profiling', 'nested')

    if format not in ['text', 'kcachegrind']:
        ui.warn(_("unrecognized profiling format '%s'"
                    " - Ignored\n") % format)
        format = 'text'

    try:
        from . import lsprof
    except ImportError:
        raise error.Abort(_(
            'lsprof not available - install from '
            'http://codespeak.net/svn/user/arigo/hack/misc/lsprof/'))
    p = lsprof.Profiler()
    p.enable(subcalls=True)
    try:
        yield
    finally:
        p.disable()

        if format == '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
    except ImportError:
        raise error.Abort(_(
            'flamegraph not available - install from '
            'https://github.com/evanhempel/python-flamegraph'))
    # developer config: profiling.freq
    freq = ui.configint('profiling', '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('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('profiling', '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(_("invalid sampling frequency '%s' - ignoring\n") % freq)

    track = ui.config('profiling', 'time-track')
    statprof.start(mechanism='thread', track=track)

    try:
        yield
    finally:
        data = statprof.stop()

        profformat = ui.config('profiling', 'statformat')

        formats = {
            'byline': statprof.DisplayFormats.ByLine,
            'bymethod': statprof.DisplayFormats.ByMethod,
            'hotpath': statprof.DisplayFormats.Hotpath,
            'json': statprof.DisplayFormats.Json,
            'chrome': statprof.DisplayFormats.Chrome,
        }

        if profformat in formats:
            displayformat = formats[profformat]
        else:
            ui.warn(_('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('%'):
                v = float(s[:-1]) / 100
            else:
                v = float(s)
            if 0 <= v <= 1:
                return v
            raise ValueError(s)

        if profformat == 'chrome':
            showmin = ui.configwith(fraction, 'profiling', 'showmin', 0.005)
            showmax = ui.configwith(fraction, 'profiling', 'showmax')
            kwargs.update(minthreshold=showmin, maxthreshold=showmax)
        elif profformat == 'hotpath':
            # inconsistent config: profiling.showmin
            limit = ui.configwith(fraction, 'profiling', 'showmin', 0.05)
            kwargs[r'limit'] = limit

        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._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()
        if self._started:
            return
        self._started = True
        profiler = encoding.environ.get('HGPROF')
        proffn = None
        if profiler is None:
            profiler = self._ui.config('profiling', 'type')
        if profiler not in ('ls', 'stat', 'flame'):
            # try load profiler from extension with the same name
            proffn = _loadprofiler(self._ui, profiler)
            if proffn is None:
                self._ui.warn(_("unrecognized profiler '%s' - ignored\n")
                              % profiler)
                profiler = 'stat'

        self._output = self._ui.config('profiling', 'output')

        try:
            if self._output == 'blackbox':
                self._fp = util.stringio()
            elif self._output:
                path = self._ui.expandpath(self._output)
                self._fp = open(path, '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

            if proffn is not None:
                pass
            elif profiler == 'ls':
                proffn = lsprofile
            elif profiler == '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:
            propagate = self._profiler.__exit__(exception_type, exception_value,
                                                traceback)
            if self._output == 'blackbox':
                val = '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('%', '%%')
                self._ui.log('profile', val)
        self._closefp()
        return propagate

    def _closefp(self):
        if self._fpdoclose and self._fp is not None:
            self._fp.close()