setdiscovery: simplify by using tiprev directly

tip() uses tiprev() and reads the node from it, so drop a layer of
indirection.

Differential Revision: https://phab.mercurial-scm.org/D10289

mercurial/setdiscovery.py

@@ -1,519 +1,519 b''
 # 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.
 """
 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,
     policy,
     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, randomize=True):
     """return a random subset of sample of at most desiredlen item.
 
     If randomize is False, though, a deterministic subset is returned.
     This is meant for integration tests.
     """
     if len(sample) <= desiredlen:
         return sample
     if randomize:
         return set(random.sample(sample, desiredlen))
     sample = list(sample)
     sample.sort()
     return set(sample[:desiredlen])
 
 
 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, respectsize, randomize=True):
         self._repo = repo
         self._targetheads = targetheads
         self._common = repo.changelog.incrementalmissingrevs()
         self._undecided = None
         self.missing = set()
         self._childrenmap = None
         self._respectsize = respectsize
         self.randomize = randomize
 
     def addcommons(self, commons):
         """register nodes known as common"""
         self._common.addbases(commons)
         if self._undecided is not None:
             self._common.removeancestorsfrom(self._undecided)
 
     def addmissings(self, missings):
         """register some nodes as missing"""
         newmissing = self._repo.revs(b'%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 stats(self):
         return {
             'undecided': len(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(b'heads(%ld)', revs))
 
         if len(sample) >= size:
             return _limitsample(sample, size, randomize=self.randomize)
 
         _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(b'heads(%ld)', revs))
         parentrevs = self._parentsgetter()
 
         # update from heads
         revsheads = sample.copy()
         _updatesample(revs, revsheads, sample, parentrevs)
 
         # update from roots
         revsroots = set(repo.revs(b'roots(%ld)', revs))
         childrenrevs = self._childrengetter()
         _updatesample(revs, revsroots, sample, childrenrevs)
         assert sample
 
         if not self._respectsize:
             size = max(size, min(len(revsroots), len(revsheads)))
 
         sample = _limitsample(sample, size, randomize=self.randomize)
         if len(sample) < size:
             more = size - len(sample)
             takefrom = list(revs - sample)
             if self.randomize:
                 sample.update(random.sample(takefrom, more))
             else:
                 takefrom.sort()
                 sample.update(takefrom[:more])
         return sample
 
 
 partialdiscovery = policy.importrust(
     'discovery', member='PartialDiscovery', default=partialdiscovery
 )
 
 
 def findcommonheads(
     ui,
     local,
     remote,
     abortwhenunrelated=True,
     ancestorsof=None,
     audit=None,
 ):
     """Return a tuple (common, anyincoming, remoteheads) used to identify
     missing nodes from or in remote.
 
     The audit argument is an optional dictionnary that a caller can pass. it
     will be updated with extra data about the discovery, this is useful for
     debug.
     """
 
     samplegrowth = float(ui.config(b'devel', b'discovery.grow-sample.rate'))
 
     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]
 
     initial_head_exchange = ui.configbool(b'devel', b'discovery.exchange-heads')
     initialsamplesize = ui.configint(b'devel', b'discovery.sample-size.initial')
     fullsamplesize = ui.configint(b'devel', b'discovery.sample-size')
     # We also ask remote about all the local heads. That set can be arbitrarily
     # large, so we used to limit it size to `initialsamplesize`. We no longer
     # do as it proved counter productive. The skipped heads could lead to a
     # large "undecided" set, slower to be clarified than if we asked the
     # question for all heads right away.
     #
     # We are already fetching all server heads using the `heads` commands,
     # sending a equivalent number of heads the other way should not have a
     # significant impact.  In addition, it is very likely that we are going to
     # have to issue "known" request for an equivalent amount of revisions in
     # order to decide if theses heads are common or missing.
     #
     # find a detailled analysis below.
     #
     # Case A: local and server both has few heads
     #
     #     Ownheads is below initialsamplesize, limit would not have any effect.
     #
     # Case B: local has few heads and server has many
     #
     #     Ownheads is below initialsamplesize, limit would not have any effect.
     #
     # Case C: local and server both has many heads
     #
     #     We now transfert some more data, but not significantly more than is
     #     already transfered to carry the server heads.
     #
     # Case D: local has many heads, server has few
     #
     #   D.1 local heads are mostly known remotely
     #
     #     All the known head will have be part of a `known` request at some
     #     point for the discovery to finish. Sending them all earlier is
     #     actually helping.
     #
     #     (This case is fairly unlikely, it requires the numerous heads to all
     #     be merged server side in only a few heads)
     #
     #   D.2 local heads are mostly missing remotely
     #
     #     To determine that the heads are missing, we'll have to issue `known`
     #     request for them or one of their ancestors. This amount of `known`
     #     request will likely be in the same order of magnitude than the amount
     #     of local heads.
     #
     #     The only case where we can be more efficient using `known` request on
     #     ancestors are case were all the "missing" local heads are based on a
     #     few changeset, also "missing".  This means we would have a "complex"
     #     graph (with many heads) attached to, but very independant to a the
     #     "simple" graph on the server. This is a fairly usual case and have
     #     not been met in the wild so far.
     if initial_head_exchange:
         if remote.limitedarguments:
             sample = _limitsample(ownheads, initialsamplesize)
             # indices between sample and externalized version must match
             sample = list(sample)
         else:
             sample = ownheads
 
         ui.debug(b"query 1; heads\n")
         roundtrips += 1
         with remote.commandexecutor() as e:
             fheads = e.callcommand(b'heads', {})
             fknown = e.callcommand(
                 b'known',
                 {
                     b'nodes': [clnode(r) for r in sample],
                 },
             )
 
         srvheadhashes, yesno = fheads.result(), fknown.result()
 
         if audit is not None:
             audit[b'total-roundtrips'] = 1
 
-        if cl.tip() == nullid:
+        if cl.tiprev() == nullrev:
             if srvheadhashes != [nullid]:
                 return [nullid], True, srvheadhashes
             return [nullid], False, []
     else:
         # we still need the remote head for the function return
         with remote.commandexecutor() as e:
             fheads = e.callcommand(b'heads', {})
         srvheadhashes = fheads.result()
 
     # start actual discovery (we note this before the next "if" for
     # compatibility reasons)
     ui.status(_(b"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 initial_head_exchange:
         # early exit if we know all the specified remote heads already
         if len(knownsrvheads) == len(srvheadhashes):
             ui.debug(b"all remote heads known locally\n")
             return srvheadhashes, False, srvheadhashes
 
         if len(sample) == len(ownheads) and all(yesno):
             ui.note(_(b"all local changesets known remotely\n"))
             ownheadhashes = [clnode(r) for r in ownheads]
             return ownheadhashes, True, srvheadhashes
 
     # full blown discovery
 
     # if the server has a limit to its arguments size, we can't grow the sample.
     configbool = local.ui.configbool
     grow_sample = configbool(b'devel', b'discovery.grow-sample')
     grow_sample = grow_sample and not remote.limitedarguments
 
     dynamic_sample = configbool(b'devel', b'discovery.grow-sample.dynamic')
     hard_limit_sample = not (dynamic_sample or remote.limitedarguments)
 
     randomize = ui.configbool(b'devel', b'discovery.randomize')
     disco = partialdiscovery(
         local, ownheads, hard_limit_sample, randomize=randomize
     )
     if initial_head_exchange:
         # treat remote heads (and maybe own heads) as a first implicit sample
         # response
         disco.addcommons(knownsrvheads)
         disco.addinfo(zip(sample, yesno))
 
     full = not initial_head_exchange
     progress = ui.makeprogress(_(b'searching'), unit=_(b'queries'))
     while not disco.iscomplete():
 
         if full or disco.hasinfo():
             if full:
                 ui.note(_(b"sampling from both directions\n"))
             else:
                 ui.debug(b"taking initial sample\n")
             samplefunc = disco.takefullsample
             targetsize = fullsamplesize
             if grow_sample:
                 fullsamplesize = int(fullsamplesize * samplegrowth)
         else:
             # use even cheaper initial sample
             ui.debug(b"taking quick initial sample\n")
             samplefunc = disco.takequicksample
             targetsize = initialsamplesize
         sample = samplefunc(ownheads, targetsize)
 
         roundtrips += 1
         progress.update(roundtrips)
         stats = disco.stats()
         ui.debug(
             b"query %i; still undecided: %i, sample size is: %i\n"
             % (roundtrips, stats['undecided'], len(sample))
         )
 
         # indices between sample and externalized version must match
         sample = list(sample)
 
         with remote.commandexecutor() as e:
             yesno = e.callcommand(
                 b'known',
                 {
                     b'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(b"%d total queries in %.4fs\n" % (roundtrips, elapsed))
     msg = (
         b'found %d common and %d unknown server heads,'
         b' %d roundtrips in %.4fs\n'
     )
     missing = set(result) - set(knownsrvheads)
     ui.log(b'discovery', msg, len(result), len(missing), roundtrips, elapsed)
 
     if audit is not None:
         audit[b'total-roundtrips'] = roundtrips
 
     if not result and srvheadhashes != [nullid]:
         if abortwhenunrelated:
             raise error.Abort(_(b"repository is unrelated"))
         else:
             ui.warn(_(b"warning: repository is unrelated\n"))
         return (
             {nullid},
             True,
             srvheadhashes,
         )
 
     anyincoming = srvheadhashes != [nullid]
     result = {clnode(r) for r in result}
     return result, anyincoming, srvheadhashes