annotate mercurial/setdiscovery.py @ 18820:a45e44d76c81

mercurial: implement diff and join for dicts

Given two dicts, diff returns a dict containing all the keys that are present
in one dict but not the other, or whose values are different between the
dicts. The values are pairs of the values from the dicts, with missing values
being represented as an optional argument, defaulting to None.

Given two dicts, join performs what is known as an outer join in relational
database land: it returns a dict containing all the keys across both dicts.
The values are pairs as above, except they aren't compared to see if they're
the same.

# setdiscovery.py - improved discovery of common nodeset for mercurial
#
# Copyright 2010 Benoit Boissinot <[e-mail]>
# and Peter Arrenbrecht <[e-mail]>
#
# This software may be used and distributed according to the terms of the
# GNU General Public License version 2 or any later version.

from node import nullid
from i18n import _
import random, util, dagutil

def _updatesample(dag, nodes, sample, always, quicksamplesize=0):
    # if nodes is empty we scan the entire graph
    if nodes:
        heads = dag.headsetofconnecteds(nodes)
    else:
        heads = dag.heads()
    dist = {}
    visit = util.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:
            if curr not in always: # need this check for the early exit below
                sample.add(curr)
                if quicksamplesize and (len(sample) >= quicksamplesize):
                    return
        seen.add(curr)
        for p in dag.parents(curr):
            if not nodes or p in nodes:
                dist.setdefault(p, d + 1)
                visit.append(p)

def _setupsample(dag, nodes, size):
    if len(nodes) <= size:
        return set(nodes), None, 0
    always = dag.headsetofconnecteds(nodes)
    desiredlen = size - len(always)
    if desiredlen <= 0:
        # This could be bad if there are very many heads, all unknown to the
        # server. We're counting on long request support here.
        return always, None, desiredlen
    return always, set(), desiredlen

def _takequicksample(dag, nodes, size, initial):
    always, sample, desiredlen = _setupsample(dag, nodes, size)
    if sample is None:
        return always
    if initial:
        fromset = None
    else:
        fromset = nodes
    _updatesample(dag, fromset, sample, always, quicksamplesize=desiredlen)
    sample.update(always)
    return sample

def _takefullsample(dag, nodes, size):
    always, sample, desiredlen = _setupsample(dag, nodes, size)
    if sample is None:
        return always
    # update from heads
    _updatesample(dag, nodes, sample, always)
    # update from roots
    _updatesample(dag.inverse(), nodes, sample, always)
    assert sample
    if len(sample) > desiredlen:
        sample = set(random.sample(sample, desiredlen))
    elif len(sample) < desiredlen:
        more = desiredlen - len(sample)
        sample.update(random.sample(list(nodes - sample - always), more))
    sample.update(always)
    return sample

def findcommonheads(ui, local, remote,
                    initialsamplesize=100,
                    fullsamplesize=200,
                    abortwhenunrelated=True):
    '''Return a tuple (common, anyincoming, remoteheads) used to identify
    missing nodes from or in remote.
    '''
    roundtrips = 0
    cl = local.changelog
    dag = dagutil.revlogdag(cl)

    # early exit if we know all the specified remote heads already
    ui.debug("query 1; heads\n")
    roundtrips += 1
    ownheads = dag.heads()
    sample = ownheads
    if remote.local():
        # stopgap until we have a proper localpeer that supports batch()
        srvheadhashes = remote.heads()
        yesno = remote.known(dag.externalizeall(sample))
    elif remote.capable('batch'):
        batch = remote.batch()
        srvheadhashesref = batch.heads()
        yesnoref = batch.known(dag.externalizeall(sample))
        batch.submit()
        srvheadhashes = srvheadhashesref.value
        yesno = yesnoref.value
    else:
        # compatibility with pre-batch, but post-known remotes during 1.9
        # development
        srvheadhashes = remote.heads()
        sample = []

    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"))

    srvheads = dag.internalizeall(srvheadhashes, filterunknown=True)
    if len(srvheads) == len(srvheadhashes):
        ui.debug("all remote heads known locally\n")
        return (srvheadhashes, False, srvheadhashes,)

    if sample and util.all(yesno):
        ui.note(_("all local heads known remotely\n"))
        ownheadhashes = dag.externalizeall(ownheads)
        return (ownheadhashes, True, srvheadhashes,)

    # full blown discovery

    # own nodes where I don't know if remote knows them
    undecided = dag.nodeset()
    # own nodes I know we both know
    common = set()
    # own nodes I know remote lacks
    missing = set()

    # treat remote heads (and maybe own heads) as a first implicit sample
    # response
    common.update(dag.ancestorset(srvheads))
    undecided.difference_update(common)

    full = False
    while undecided:

        if sample:
            commoninsample = set(n for i, n in enumerate(sample) if yesno[i])
            common.update(dag.ancestorset(commoninsample, common))

            missinginsample = [n for i, n in enumerate(sample) if not yesno[i]]
            missing.update(dag.descendantset(missinginsample, missing))

            undecided.difference_update(missing)
            undecided.difference_update(common)

        if not undecided:
            break

        if full:
            ui.note(_("sampling from both directions\n"))
            sample = _takefullsample(dag, undecided, size=fullsamplesize)
        elif common:
            # use cheapish initial sample
            ui.debug("taking initial sample\n")
            sample = _takefullsample(dag, undecided, size=fullsamplesize)
        else:
            # use even cheaper initial sample
            ui.debug("taking quick initial sample\n")
            sample = _takequicksample(dag, undecided, size=initialsamplesize,
                                      initial=True)

        roundtrips += 1
        ui.progress(_('searching'), roundtrips, unit=_('queries'))
        ui.debug("query %i; still undecided: %i, sample size is: %i\n"
                 % (roundtrips, len(undecided), len(sample)))
        # indices between sample and externalized version must match
        sample = list(sample)
        yesno = remote.known(dag.externalizeall(sample))
        full = True

    result = dag.headsetofconnecteds(common)
    ui.progress(_('searching'), None)
    ui.debug("%d total queries\n" % roundtrips)

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

    anyincoming = (srvheadhashes != [nullid])
    return dag.externalizeall(result), anyincoming, srvheadhashes