Mercurial > hg
view mercurial/setdiscovery.py @ 46446:1dcd9c9975ed
rust: Fold find_root and check_requirements into Repo::find
Differential Revision: https://phab.mercurial-scm.org/D9906
author | Simon Sapin <simon.sapin@octobus.net> |
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date | Thu, 28 Jan 2021 20:31:42 +0100 |
parents | 0600e8467101 |
children | f165105400d0 |
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# 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, 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 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. hard_limit_sample = remote.limitedarguments grow_sample = local.ui.configbool(b'devel', b'discovery.grow-sample') hard_limit_sample = hard_limit_sample and grow_sample 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 not hard_limit_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