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parsers: a C implementation of the new ancestors algorithm...
parsers: a C implementation of the new ancestors algorithm The performance of both the old and new Python ancestor algorithms depends on the number of revs they need to traverse. Although the new algorithm performs far better than the old when revs are numerically and topologically close, both algorithms become slow under other circumstances, taking up to 1.8 seconds to give answers in a Linux kernel repo. This C implementation of the new algorithm is a fairly straightforward transliteration. The only corner case of interest is that it raises an OverflowError if the number of GCA candidates found during the first pass is greater than 24, to avoid the dual perils of fixnum overflow and trying to allocate too much memory. (If this exception is raised, the Python implementation is used instead.) Performance numbers are good: in a Linux kernel repo, time for "hg debugancestors" on two distant revs (24bf01de7537 and c2a8808f5943) is as follows: Old Python: 0.36 sec New Python: 0.42 sec New C: 0.02 sec For a case where the new algorithm should perform well: Old Python: 1.84 sec New Python: 0.07 sec New C: measures as zero when using --time (This commit includes a paranoid cross-check to ensure that the Python and C implementations give identical answers. The above performance numbers were measured with that check disabled.)

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setdiscovery.py
197 lines | 6.7 KiB | text/x-python | PythonLexer
# 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