view mercurial/setdiscovery.py @ 42043:1fac9b931d46

compression: introduce a `storage.revlog.zlib.level` configuration This option control the zlib compression level used when compression revlog chunk. This is also a good excuse to pave the way for a similar configuration option for the zstd compression engine. Having a dedicated option for each compression algorithm is useful because they don't support the same range of values. Using a higher zlib compression impact CPU consumption at compression time, but does not directly affected decompression time. However dealing with small compressed chunk can directly help decompression and indirectly help other revlog logic. I ran some basic test on repositories using different level. I am using the mercurial, pypy, netbeans and mozilla-central clone from our benchmark suite. All tested repository use sparse-revlog and got all their delta recomputed. The different compression level has a small effect on the repository size (about 10% variation in the total range). My quick analysis is that revlog mostly store small delta, that are not affected by the compression level much. So the variation probably mostly comes from better compression of the snapshots revisions, and snapshot revision only represent a small portion of the repository content. I also made some basic timings measurements. The "read" timings are gathered using simple run of `hg perfrevlogrevisions`, the "write" timings using `hg perfrevlogwrite` (restricted to the last 5000 revisions for netbeans and mozilla central). The timings are gathered on a generic machine, (not one of our performance locked machine), so small variation might not be meaningful. However large trend remains relevant. Keep in mind that these numbers are not pure compression/decompression time. They also involve the full revlog logic. In particular the difference in chunk size has an impact on the delta chain structure, affecting performance when writing or reading them. On read/write performance, the compression level has a bigger impact. Counter-intuitively, the higher compression levels improve "write" performance for the large repositories in our tested setting. Maybe because the last 5000 delta chain end up having a very different shape in this specific spot? Or maybe because of a more general trend of better delta chains thanks to the smaller chunk and snapshot. This series does not intend to change the default compression level. However, these result call for a deeper analysis of this performance difference in the future. Full data ========= repo level .hg/store size 00manifest.d read write ---------------------------------------------------------------- mercurial 1 49,402,813 5,963,475 0.170159 53.250304 mercurial 6 47,197,397 5,875,730 0.182820 56.264320 mercurial 9 47,121,596 5,849,781 0.189219 56.293612 pypy 1 370,830,572 28,462,425 2.679217 460.721984 pypy 6 340,112,317 27,648,747 2.768691 467.537158 pypy 9 338,360,736 27,639,003 2.763495 476.589918 netbeans 1 1,281,847,810 165,495,457 122.477027 520.560316 netbeans 6 1,205,284,353 159,161,207 139.876147 715.930400 netbeans 9 1,197,135,671 155,034,586 141.620281 678.297064 mozilla 1 2,775,497,186 298,527,987 147.867662 751.263721 mozilla 6 2,596,856,420 286,597,671 170.572118 987.056093 mozilla 9 2,587,542,494 287,018,264 163.622338 739.803002
author Pierre-Yves David <pierre-yves.david@octobus.net>
date Wed, 27 Mar 2019 18:35:27 +0100
parents 0d467e4de4ae
children 362726923ba3
line wrap: on
line source

# setdiscovery.py - improved discovery of common nodeset for mercurial
#
# Copyright 2010 Benoit Boissinot <bboissin@gmail.com>
# and Peter Arrenbrecht <peter@arrenbrecht.ch>
#
# This software may be used and distributed according to the terms of the
# GNU General Public License version 2 or any later version.
"""
Algorithm works in the following way. You have two repository: local and
remote. They both contains a DAG of changelists.

The goal of the discovery protocol is to find one set of node *common*,
the set of nodes shared by local and remote.

One of the issue with the original protocol was latency, it could
potentially require lots of roundtrips to discover that the local repo was a
subset of remote (which is a very common case, you usually have few changes
compared to upstream, while upstream probably had lots of development).

The new protocol only requires one interface for the remote repo: `known()`,
which given a set of changelists tells you if they are present in the DAG.

The algorithm then works as follow:

 - We will be using three sets, `common`, `missing`, `unknown`. Originally
 all nodes are in `unknown`.
 - Take a sample from `unknown`, call `remote.known(sample)`
   - For each node that remote knows, move it and all its ancestors to `common`
   - For each node that remote doesn't know, move it and all its descendants
   to `missing`
 - Iterate until `unknown` is empty

There are a couple optimizations, first is instead of starting with a random
sample of missing, start by sending all heads, in the case where the local
repo is a subset, you computed the answer in one round trip.

Then you can do something similar to the bisecting strategy used when
finding faulty changesets. Instead of random samples, you can try picking
nodes that will maximize the number of nodes that will be
classified with it (since all ancestors or descendants will be marked as well).
"""

from __future__ import absolute_import

import collections
import random

from .i18n import _
from .node import (
    nullid,
    nullrev,
)
from . import (
    error,
    util,
)

def _updatesample(revs, heads, sample, parentfn, quicksamplesize=0):
    """update an existing sample to match the expected size

    The sample is updated with revs exponentially distant from each head of the
    <revs> set. (H~1, H~2, H~4, H~8, etc).

    If a target size is specified, the sampling will stop once this size is
    reached. Otherwise sampling will happen until roots of the <revs> set are
    reached.

    :revs:  set of revs we want to discover (if None, assume the whole dag)
    :heads: set of DAG head revs
    :sample: a sample to update
    :parentfn: a callable to resolve parents for a revision
    :quicksamplesize: optional target size of the sample"""
    dist = {}
    visit = collections.deque(heads)
    seen = set()
    factor = 1
    while visit:
        curr = visit.popleft()
        if curr in seen:
            continue
        d = dist.setdefault(curr, 1)
        if d > factor:
            factor *= 2
        if d == factor:
            sample.add(curr)
            if quicksamplesize and (len(sample) >= quicksamplesize):
                return
        seen.add(curr)

        for p in parentfn(curr):
            if p != nullrev and (not revs or p in revs):
                dist.setdefault(p, d + 1)
                visit.append(p)

def _limitsample(sample, desiredlen):
    """return a random subset of sample of at most desiredlen item"""
    if len(sample) > desiredlen:
        sample = set(random.sample(sample, desiredlen))
    return sample

class partialdiscovery(object):
    """an object representing ongoing discovery

    Feed with data from the remote repository, this object keep track of the
    current set of changeset in various states:

    - common:    revs also known remotely
    - undecided: revs we don't have information on yet
    - missing:   revs missing remotely
    (all tracked revisions are known locally)
    """

    def __init__(self, repo, targetheads):
        self._repo = repo
        self._targetheads = targetheads
        self._common = repo.changelog.incrementalmissingrevs()
        self._undecided = None
        self.missing = set()
        self._childrenmap = None

    def addcommons(self, commons):
        """registrer nodes known as common"""
        self._common.addbases(commons)
        if self._undecided is not None:
            self._common.removeancestorsfrom(self._undecided)

    def addmissings(self, missings):
        """registrer some nodes as missing"""
        newmissing = self._repo.revs('%ld::%ld', missings, self.undecided)
        if newmissing:
            self.missing.update(newmissing)
            self.undecided.difference_update(newmissing)

    def addinfo(self, sample):
        """consume an iterable of (rev, known) tuples"""
        common = set()
        missing = set()
        for rev, known in sample:
            if known:
                common.add(rev)
            else:
                missing.add(rev)
        if common:
            self.addcommons(common)
        if missing:
            self.addmissings(missing)

    def hasinfo(self):
        """return True is we have any clue about the remote state"""
        return self._common.hasbases()

    def iscomplete(self):
        """True if all the necessary data have been gathered"""
        return self._undecided is not None and not self._undecided

    @property
    def undecided(self):
        if self._undecided is not None:
            return self._undecided
        self._undecided = set(self._common.missingancestors(self._targetheads))
        return self._undecided

    def commonheads(self):
        """the heads of the known common set"""
        # heads(common) == heads(common.bases) since common represents
        # common.bases and all its ancestors
        return self._common.basesheads()

    def _parentsgetter(self):
        getrev = self._repo.changelog.index.__getitem__
        def getparents(r):
            return getrev(r)[5:7]
        return getparents

    def _childrengetter(self):

        if self._childrenmap is not None:
            # During discovery, the `undecided` set keep shrinking.
            # Therefore, the map computed for an iteration N will be
            # valid for iteration N+1. Instead of computing the same
            # data over and over we cached it the first time.
            return self._childrenmap.__getitem__

        # _updatesample() essentially does interaction over revisions to look
        # up their children. This lookup is expensive and doing it in a loop is
        # quadratic. We precompute the children for all relevant revisions and
        # make the lookup in _updatesample() a simple dict lookup.
        self._childrenmap = children = {}

        parentrevs = self._parentsgetter()
        revs = self.undecided

        for rev in sorted(revs):
            # Always ensure revision has an entry so we don't need to worry
            # about missing keys.
            children[rev] = []
            for prev in parentrevs(rev):
                if prev == nullrev:
                    continue
                c = children.get(prev)
                if c is not None:
                    c.append(rev)
        return children.__getitem__

    def takequicksample(self, headrevs, size):
        """takes a quick sample of size <size>

        It is meant for initial sampling and focuses on querying heads and close
        ancestors of heads.

        :headrevs: set of head revisions in local DAG to consider
        :size: the maximum size of the sample"""
        revs = self.undecided
        if len(revs) <= size:
            return list(revs)
        sample = set(self._repo.revs('heads(%ld)', revs))

        if len(sample) >= size:
            return _limitsample(sample, size)

        _updatesample(None, headrevs, sample, self._parentsgetter(),
                      quicksamplesize=size)
        return sample

    def takefullsample(self, headrevs, size):
        revs = self.undecided
        if len(revs) <= size:
            return list(revs)
        repo = self._repo
        sample = set(repo.revs('heads(%ld)', revs))
        parentrevs = self._parentsgetter()

        # update from heads
        revsheads = sample.copy()
        _updatesample(revs, revsheads, sample, parentrevs)

        # update from roots
        revsroots = set(repo.revs('roots(%ld)', revs))

        childrenrevs = self._childrengetter()

        _updatesample(revs, revsroots, sample, childrenrevs)
        assert sample
        sample = _limitsample(sample, size)
        if len(sample) < size:
            more = size - len(sample)
            sample.update(random.sample(list(revs - sample), more))
        return sample

def findcommonheads(ui, local, remote,
                    initialsamplesize=100,
                    fullsamplesize=200,
                    abortwhenunrelated=True,
                    ancestorsof=None):
    '''Return a tuple (common, anyincoming, remoteheads) used to identify
    missing nodes from or in remote.
    '''
    start = util.timer()

    roundtrips = 0
    cl = local.changelog
    clnode = cl.node
    clrev = cl.rev

    if ancestorsof is not None:
        ownheads = [clrev(n) for n in ancestorsof]
    else:
        ownheads = [rev for rev in cl.headrevs() if rev != nullrev]

    # early exit if we know all the specified remote heads already
    ui.debug("query 1; heads\n")
    roundtrips += 1
    sample = _limitsample(ownheads, initialsamplesize)
    # indices between sample and externalized version must match
    sample = list(sample)

    with remote.commandexecutor() as e:
        fheads = e.callcommand('heads', {})
        fknown = e.callcommand('known', {
            'nodes': [clnode(r) for r in sample],
        })

    srvheadhashes, yesno = fheads.result(), fknown.result()

    if cl.tip() == nullid:
        if srvheadhashes != [nullid]:
            return [nullid], True, srvheadhashes
        return [nullid], False, []

    # start actual discovery (we note this before the next "if" for
    # compatibility reasons)
    ui.status(_("searching for changes\n"))

    knownsrvheads = []  # revnos of remote heads that are known locally
    for node in srvheadhashes:
        if node == nullid:
            continue

        try:
            knownsrvheads.append(clrev(node))
        # Catches unknown and filtered nodes.
        except error.LookupError:
            continue

    if len(knownsrvheads) == len(srvheadhashes):
        ui.debug("all remote heads known locally\n")
        return srvheadhashes, False, srvheadhashes

    if len(sample) == len(ownheads) and all(yesno):
        ui.note(_("all local heads known remotely\n"))
        ownheadhashes = [clnode(r) for r in ownheads]
        return ownheadhashes, True, srvheadhashes

    # full blown discovery

    disco = partialdiscovery(local, ownheads)
    # treat remote heads (and maybe own heads) as a first implicit sample
    # response
    disco.addcommons(knownsrvheads)
    disco.addinfo(zip(sample, yesno))

    full = False
    progress = ui.makeprogress(_('searching'), unit=_('queries'))
    while not disco.iscomplete():

        if full or disco.hasinfo():
            if full:
                ui.note(_("sampling from both directions\n"))
            else:
                ui.debug("taking initial sample\n")
            samplefunc = disco.takefullsample
            targetsize = fullsamplesize
        else:
            # use even cheaper initial sample
            ui.debug("taking quick initial sample\n")
            samplefunc = disco.takequicksample
            targetsize = initialsamplesize
        sample = samplefunc(ownheads, targetsize)

        roundtrips += 1
        progress.update(roundtrips)
        ui.debug("query %i; still undecided: %i, sample size is: %i\n"
                 % (roundtrips, len(disco.undecided), len(sample)))
        # indices between sample and externalized version must match
        sample = list(sample)

        with remote.commandexecutor() as e:
            yesno = e.callcommand('known', {
                'nodes': [clnode(r) for r in sample],
            }).result()

        full = True

        disco.addinfo(zip(sample, yesno))

    result = disco.commonheads()
    elapsed = util.timer() - start
    progress.complete()
    ui.debug("%d total queries in %.4fs\n" % (roundtrips, elapsed))
    msg = ('found %d common and %d unknown server heads,'
           ' %d roundtrips in %.4fs\n')
    missing = set(result) - set(knownsrvheads)
    ui.log('discovery', msg, len(result), len(missing), roundtrips,
           elapsed)

    if not result and srvheadhashes != [nullid]:
        if abortwhenunrelated:
            raise error.Abort(_("repository is unrelated"))
        else:
            ui.warn(_("warning: repository is unrelated\n"))
        return ({nullid}, True, srvheadhashes,)

    anyincoming = (srvheadhashes != [nullid])
    result = {clnode(r) for r in result}
    return result, anyincoming, srvheadhashes