##// END OF EJS Templates
util: lower water mark when removing nodes after cost limit reached...
util: lower water mark when removing nodes after cost limit reached See the inline comment for the reasoning here. This is a pretty common strategy for garbage collectors, other cache-like primtives. The performance impact is substantial: $ hg perflrucachedict --size 4 --gets 1000000 --sets 1000000 --mixed 1000000 --costlimit 100 ! inserts w/ cost limit ! wall 1.659181 comb 1.650000 user 1.650000 sys 0.000000 (best of 7) ! wall 1.722122 comb 1.720000 user 1.720000 sys 0.000000 (best of 6) ! mixed w/ cost limit ! wall 1.139955 comb 1.140000 user 1.140000 sys 0.000000 (best of 9) ! wall 1.182513 comb 1.180000 user 1.180000 sys 0.000000 (best of 9) $ hg perflrucachedict --size 1000 --gets 1000000 --sets 1000000 --mixed 1000000 --costlimit 10000 ! inserts ! wall 0.679546 comb 0.680000 user 0.680000 sys 0.000000 (best of 15) ! sets ! wall 0.825147 comb 0.830000 user 0.830000 sys 0.000000 (best of 13) ! inserts w/ cost limit ! wall 25.105273 comb 25.080000 user 25.080000 sys 0.000000 (best of 3) ! wall 1.724397 comb 1.720000 user 1.720000 sys 0.000000 (best of 6) ! mixed ! wall 0.807096 comb 0.810000 user 0.810000 sys 0.000000 (best of 13) ! mixed w/ cost limit ! wall 12.104470 comb 12.070000 user 12.070000 sys 0.000000 (best of 3) ! wall 1.190563 comb 1.190000 user 1.190000 sys 0.000000 (best of 9) $ hg perflrucachedict --size 1000 --gets 1000000 --sets 1000000 --mixed 1000000 --costlimit 10000 --mixedgetfreq 90 ! inserts ! wall 0.711177 comb 0.710000 user 0.710000 sys 0.000000 (best of 14) ! sets ! wall 0.846992 comb 0.850000 user 0.850000 sys 0.000000 (best of 12) ! inserts w/ cost limit ! wall 25.963028 comb 25.960000 user 25.960000 sys 0.000000 (best of 3) ! wall 2.184311 comb 2.180000 user 2.180000 sys 0.000000 (best of 5) ! mixed ! wall 0.728256 comb 0.730000 user 0.730000 sys 0.000000 (best of 14) ! mixed w/ cost limit ! wall 3.174256 comb 3.170000 user 3.170000 sys 0.000000 (best of 4) ! wall 0.773186 comb 0.770000 user 0.770000 sys 0.000000 (best of 13) $ hg perflrucachedict --size 100000 --gets 1000000 --sets 1000000 --mixed 1000000 --mixedgetfreq 90 --costlimit 5000000 ! gets ! wall 1.191368 comb 1.190000 user 1.190000 sys 0.000000 (best of 9) ! wall 1.195304 comb 1.190000 user 1.190000 sys 0.000000 (best of 9) ! inserts ! wall 0.950995 comb 0.950000 user 0.950000 sys 0.000000 (best of 11) ! inserts w/ cost limit ! wall 1.589732 comb 1.590000 user 1.590000 sys 0.000000 (best of 7) ! sets ! wall 1.094941 comb 1.100000 user 1.090000 sys 0.010000 (best of 9) ! mixed ! wall 0.936420 comb 0.940000 user 0.930000 sys 0.010000 (best of 10) ! mixed w/ cost limit ! wall 0.882780 comb 0.870000 user 0.870000 sys 0.000000 (best of 11) This puts us ~2x slower than caches without cost accounting. And for read-heavy workloads (the prime use cases for caches), performance is nearly identical. In the worst case (pure write workloads with cost accounting enabled), we're looking at ~1.5us per insert on large caches. That seems "fast enough." Differential Revision: https://phab.mercurial-scm.org/D4505

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setdiscovery.py
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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,
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 _takequicksample(repo, headrevs, revs, size):
"""takes a quick sample of size <size>
It is meant for initial sampling and focuses on querying heads and close
ancestors of heads.
:dag: a dag object
:headrevs: set of head revisions in local DAG to consider
:revs: set of revs to discover
:size: the maximum size of the sample"""
sample = set(repo.revs('heads(%ld)', revs))
if len(sample) >= size:
return _limitsample(sample, size)
_updatesample(None, headrevs, sample, repo.changelog.parentrevs,
quicksamplesize=size)
return sample
def _takefullsample(repo, headrevs, revs, size):
sample = set(repo.revs('heads(%ld)', revs))
# update from heads
revsheads = set(repo.revs('heads(%ld)', revs))
_updatesample(revs, revsheads, sample, repo.changelog.parentrevs)
# update from roots
revsroots = set(repo.revs('roots(%ld)', revs))
# _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.
#
# Because this function can be called multiple times during discovery, we
# may still perform redundant work and there is room to optimize this by
# keeping a persistent cache of children across invocations.
children = {}
parentrevs = repo.changelog.parentrevs
for rev in repo.changelog.revs(start=min(revsroots)):
# Always ensure revision has an entry so we don't need to worry about
# missing keys.
children.setdefault(rev, [])
for prev in parentrevs(rev):
if prev == nullrev:
continue
children.setdefault(prev, []).append(rev)
_updatesample(revs, revsroots, sample, children.__getitem__)
assert sample
sample = _limitsample(sample, size)
if len(sample) < size:
more = size - len(sample)
sample.update(random.sample(list(revs - sample), more))
return sample
def _limitsample(sample, desiredlen):
"""return a random subset of sample of at most desiredlen item"""
if len(sample) > desiredlen:
sample = set(random.sample(sample, desiredlen))
return sample
def findcommonheads(ui, local, remote,
initialsamplesize=100,
fullsamplesize=200,
abortwhenunrelated=True,
ancestorsof=None):
'''Return a tuple (common, anyincoming, remoteheads) used to identify
missing nodes from or in remote.
'''
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]
# early exit if we know all the specified remote heads already
ui.debug("query 1; heads\n")
roundtrips += 1
sample = _limitsample(ownheads, initialsamplesize)
# indices between sample and externalized version must match
sample = list(sample)
with remote.commandexecutor() as e:
fheads = e.callcommand('heads', {})
fknown = e.callcommand('known', {
'nodes': [clnode(r) for r in sample],
})
srvheadhashes, yesno = fheads.result(), fknown.result()
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 = []
for node in srvheadhashes:
if node == nullid:
continue
try:
srvheads.append(clrev(node))
# Catches unknown and filtered nodes.
except error.LookupError:
continue
if len(srvheads) == len(srvheadhashes):
ui.debug("all remote heads known locally\n")
return srvheadhashes, False, srvheadhashes
if len(sample) == len(ownheads) and all(yesno):
ui.note(_("all local heads known remotely\n"))
ownheadhashes = [clnode(r) for r in ownheads]
return ownheadhashes, True, srvheadhashes
# full blown discovery
# own nodes I know we both know
# treat remote heads (and maybe own heads) as a first implicit sample
# response
common = cl.incrementalmissingrevs(srvheads)
commoninsample = set(n for i, n in enumerate(sample) if yesno[i])
common.addbases(commoninsample)
# own nodes where I don't know if remote knows them
undecided = set(common.missingancestors(ownheads))
# own nodes I know remote lacks
missing = set()
full = False
progress = ui.makeprogress(_('searching'), unit=_('queries'))
while undecided:
if sample:
missinginsample = [n for i, n in enumerate(sample) if not yesno[i]]
if missing:
missing.update(local.revs('descendants(%ld) - descendants(%ld)',
missinginsample, missing))
else:
missing.update(local.revs('descendants(%ld)', missinginsample))
undecided.difference_update(missing)
if not undecided:
break
if full or common.hasbases():
if full:
ui.note(_("sampling from both directions\n"))
else:
ui.debug("taking initial sample\n")
samplefunc = _takefullsample
targetsize = fullsamplesize
else:
# use even cheaper initial sample
ui.debug("taking quick initial sample\n")
samplefunc = _takequicksample
targetsize = initialsamplesize
if len(undecided) < targetsize:
sample = list(undecided)
else:
sample = samplefunc(local, ownheads, undecided, targetsize)
roundtrips += 1
progress.update(roundtrips)
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)
with remote.commandexecutor() as e:
yesno = e.callcommand('known', {
'nodes': [clnode(r) for r in sample],
}).result()
full = True
if sample:
commoninsample = set(n for i, n in enumerate(sample) if yesno[i])
common.addbases(commoninsample)
common.removeancestorsfrom(undecided)
# heads(common) == heads(common.bases) since common represents common.bases
# and all its ancestors
# The presence of nullrev will confuse heads(). So filter it out.
result = set(local.revs('heads(%ld)', common.bases - {nullrev}))
elapsed = util.timer() - start
progress.complete()
ui.debug("%d total queries in %.4fs\n" % (roundtrips, elapsed))
msg = ('found %d common and %d unknown server heads,'
' %d roundtrips in %.4fs\n')
missing = set(result) - set(srvheads)
ui.log('discovery', msg, len(result), len(missing), roundtrips,
elapsed)
if not result and srvheadhashes != [nullid]:
if abortwhenunrelated:
raise error.Abort(_("repository is unrelated"))
else:
ui.warn(_("warning: repository is unrelated\n"))
return ({nullid}, True, srvheadhashes,)
anyincoming = (srvheadhashes != [nullid])
result = {clnode(r) for r in result}
return result, anyincoming, srvheadhashes