copies: filter out copies grafted from another branch
Consider this simple history:
```
@ 3 modify y
|
o 2 copy x to y, modify x
|
| o 1 copy x to y, modify x
|/
o 0 add x
```
If we now rebase commit 3 onto 1, Mercurial will look for copies
between commit 2 and commit 1. It does that by going backwards from 2
to 0 and then forwards from 0 to 1. It will find that x was copied to
y, since that was what happened on the path between them (namely in
commit 1). That leads Mercurial to do a 3-way merge between y@3 and
y@1 with x@2 as base. We want to use y@2 as base instead. That's also
what happened until commit
1d6d1a15. This patch fixes the regression
by adding another filtering step when chaining copies via a
diffbase. The new filtering step removes copies that were the same
between the two branches (same source and destination, but not
necessarily the same contents).
Differential Revision: https://phab.mercurial-scm.org/D10120
# 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