ancestor: a new algorithm that is faster for nodes near tip
Instead of walking all the way to the root of the DAG, we generate
a set of candidate GCA revs, then figure out which ones will win
the race to the root (usually without needing to traverse all the
way to the root).
In the common case of nodes that are close to each other in both
revision number and topology, this is usually a big win: it makes
"hg --time debugancestors" up to 9 times faster than the more general
ancestor function when measured on heads of the linux-2.6 hg repo.
Victory is not assured, however. The older function can still win
by a large margin if one node is much closer to the root than the
other, or by a much smaller amount if one is an ancestor of the
other.
For now, we've also got a small paranoid harness function that calls
both ancestor functions on every input and ensures that they give
equivalent answers.
Even without the checker function, the old ancestor function needs
to stay alive for the time being, as its generality is used by
context.filectx.merge.
# 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.
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