view contrib/benchmarks/__init__.py @ 42044:bb271ec2fbfb

compression: introduce a `storage.revlog.zstd.level` configuration This option control the zstd compression level used when compressing revlog chunk. The usage of zstd for revlog compression has not graduated from experimental yet, but we intend to fix that soon. The option name for the compression level is more straight forward to pick, so this changesets comes first. Having a dedicated option for each compression engine is useful because they don't support the same range of values. I ran the same measurement as for the zlib compression level (in the parent changesets). The variation in repository size is stay mostly in the same (small) range. The "read/write" performance see smallish variation, but are overall much better than zlib. Write performance show the same tend of having better write performance for when reaching high-end compression. Again, we don't intend to change the default zstd compression level (currently: 3) in this series. However this is worth investigating in the future. The Performance comparison of zlib vs zstd is quite impressive. The repository size stay in the same range, but the performance are much better in all situations. Comparison summary ================== We are looking at: - performance range for zlib - performance range for zstd - comparison of default zstd (level-3) to default zlib (level 6) - comparison of the slowest zstd time to the fastest zlib time Read performance: ----------------- | zlib | zstd | cmp | f2s mercurial | 0.170159 - 0.189219 | 0.144127 - 0.149624 | 80% | 88% pypy | 2.679217 - 2.768691 | 1.532317 - 1.705044 | 60% | 63% netbeans | 122.477027 - 141.620281 | 72.996346 - 89.731560 | 58% | 73% mozilla | 147.867662 - 170.572118 | 91.700995 - 105.853099 | 56% | 71% Write performance: ------------------ | zlib | zstd | cmp | f2s mercurial | 53.250304 - 56.2936129 | 40.877025 - 45.677286 | 75% | 86% pypy | 460.721984 - 476.589918 | 270.545409 - 301.002219 | 63% | 65% netbeans | 520.560316 - 715.930400 | 370.356311 - 428.329652 | 55% | 82% mozilla | 739.803002 - 987.056093 | 505.152906 - 591.930683 | 57% | 80% Raw data -------- repo alg lvl .hg/store size 00manifest.d read write mercurial zlib 1 49,402,813 5,963,475 0.170159 53.250304 mercurial zlib 6 47,197,397 5,875,730 0.182820 56.264320 mercurial zlib 9 47,121,596 5,849,781 0.189219 56.293612 mercurial zstd 1 49,737,084 5,966,355 0.144127 40.877025 mercurial zstd 3 48,961,867 5,895,208 0.146376 42.268142 mercurial zstd 5 48,200,592 5,938,676 0.149624 43.162875 mercurial zstd 10 47,833,520 5,913,353 0.145185 44.012489 mercurial zstd 15 47,314,604 5,728,679 0.147686 45.677286 mercurial zstd 20 47,330,502 5,830,539 0.145789 45.025407 mercurial zstd 22 47,330,076 5,830,539 0.143996 44.690460 pypy zlib 1 370,830,572 28,462,425 2.679217 460.721984 pypy zlib 6 340,112,317 27,648,747 2.768691 467.537158 pypy zlib 9 338,360,736 27,639,003 2.763495 476.589918 pypy zstd 1 362,377,479 27,916,214 1.532317 270.545409 pypy zstd 3 354,137,693 27,905,988 1.686718 294.951509 pypy zstd 5 342,640,043 27,655,774 1.705044 301.002219 pypy zstd 10 334,224,327 27,164,493 1.567287 285.186239 pypy zstd 15 329,000,363 26,645,965 1.637729 299.561332 pypy zstd 20 324,534,039 26,199,547 1.526813 302.149827 pypy zstd 22 324,530,595 26,198,932 1.525718 307.821218 netbeans zlib 1 1,281,847,810 165,495,457 122.477027 520.560316 netbeans zlib 6 1,205,284,353 159,161,207 139.876147 715.930400 netbeans zlib 9 1,197,135,671 155,034,586 141.620281 678.297064 netbeans zstd 1 1,259,581,737 160,840,613 72.996346 370.356311 netbeans zstd 3 1,232,978,122 157,691,551 81.622317 396.733087 netbeans zstd 5 1,208,034,075 160,246,880 83.080549 364.342626 netbeans zstd 10 1,188,624,176 156,083,417 79.323935 403.594602 netbeans zstd 15 1,176,973,589 153,859,477 89.731560 428.329652 netbeans zstd 20 1,162,958,258 151,147,535 82.842667 392.335349 netbeans zstd 22 1,162,707,029 151,150,220 82.565695 402.840655 mozilla zlib 1 2,775,497,186 298,527,987 147.867662 751.263721 mozilla zlib 6 2,596,856,420 286,597,671 170.572118 987.056093 mozilla zlib 9 2,587,542,494 287,018,264 163.622338 739.803002 mozilla zstd 1 2,723,159,348 286,617,532 91.700995 570.042751 mozilla zstd 3 2,665,055,001 286,152,013 95.240155 561.412805 mozilla zstd 5 2,607,819,817 288,060,030 101.978048 505.152906 mozilla zstd 10 2,558,761,085 283,967,648 104.113481 497.771202 mozilla zstd 15 2,526,216,060 275,581,300 105.853099 591.930683 mozilla zstd 20 2,485,114,806 266,478,859 95.268795 576.515389 mozilla zstd 22 2,484,869,080 266,456,505 94.429282 572.785537
author Pierre-Yves David <pierre-yves.david@octobus.net>
date Wed, 27 Mar 2019 18:35:59 +0100
parents be0e7af80543
children 2372284d9457
line wrap: on
line source

# __init__.py - asv benchmark suite
#
# Copyright 2016 Logilab SA <contact@logilab.fr>
#
# This software may be used and distributed according to the terms of the
# GNU General Public License version 2 or any later version.

# "historical portability" policy of contrib/benchmarks:
#
# We have to make this code work correctly with current mercurial stable branch
# and if possible with reasonable cost with early Mercurial versions.

'''ASV (https://asv.readthedocs.io) benchmark suite

Benchmark are parameterized against reference repositories found in the
directory pointed by the REPOS_DIR environment variable.

Invocation example:

    $ export REPOS_DIR=~/hgperf/repos
    # run suite on given revision
    $ asv --config contrib/asv.conf.json run REV
    # run suite on new changesets found in stable and default branch
    $ asv --config contrib/asv.conf.json run NEW
    # display a comparative result table of benchmark results between two given
    # revisions
    $ asv --config contrib/asv.conf.json compare REV1 REV2
    # compute regression detection and generate ASV static website
    $ asv --config contrib/asv.conf.json publish
    # serve the static website
    $ asv --config contrib/asv.conf.json preview
'''

from __future__ import absolute_import

import functools
import os
import re

from mercurial import (
    extensions,
    hg,
    ui as uimod,
    util,
)

basedir = os.path.abspath(os.path.join(os.path.dirname(__file__),
                          os.path.pardir, os.path.pardir))
reposdir = os.environ['REPOS_DIR']
reposnames = [name for name in os.listdir(reposdir)
              if os.path.isdir(os.path.join(reposdir, name, ".hg"))]
if not reposnames:
    raise ValueError("No repositories found in $REPO_DIR")
outputre = re.compile((r'! wall (\d+.\d+) comb \d+.\d+ user \d+.\d+ sys '
                       r'\d+.\d+ \(best of \d+\)'))

def runperfcommand(reponame, command, *args, **kwargs):
    os.environ["HGRCPATH"] = os.environ.get("ASVHGRCPATH", "")
    # for "historical portability"
    # ui.load() has been available since d83ca85
    if util.safehasattr(uimod.ui, "load"):
        ui = uimod.ui.load()
    else:
        ui = uimod.ui()
    repo = hg.repository(ui, os.path.join(reposdir, reponame))
    perfext = extensions.load(ui, 'perfext',
                              os.path.join(basedir, 'contrib', 'perf.py'))
    cmd = getattr(perfext, command)
    ui.pushbuffer()
    cmd(ui, repo, *args, **kwargs)
    output = ui.popbuffer()
    match = outputre.search(output)
    if not match:
        raise ValueError("Invalid output {0}".format(output))
    return float(match.group(1))

def perfbench(repos=reposnames, name=None, params=None):
    """decorator to declare ASV benchmark based on contrib/perf.py extension

    An ASV benchmark is a python function with the given attributes:

    __name__: should start with track_, time_ or mem_ to be collected by ASV
    params and param_name: parameter matrix to display multiple graphs on the
    same page.
    pretty_name: If defined it's displayed in web-ui instead of __name__
    (useful for revsets)
    the module name is prepended to the benchmark name and displayed as
    "category" in webui.

    Benchmarks are automatically parameterized with repositories found in the
    REPOS_DIR environment variable.

    `params` is the param matrix in the form of a list of tuple
    (param_name, [value0, value1])

    For example [(x, [a, b]), (y, [c, d])] declare benchmarks for
    (a, c), (a, d), (b, c) and (b, d).
    """
    params = list(params or [])
    params.insert(0, ("repo", repos))

    def decorator(func):
        @functools.wraps(func)
        def wrapped(repo, *args):
            def perf(command, *a, **kw):
                return runperfcommand(repo, command, *a, **kw)
            return func(perf, *args)

        wrapped.params = [p[1] for p in params]
        wrapped.param_names = [p[0] for p in params]
        wrapped.pretty_name = name
        return wrapped
    return decorator