copies: optimize forward copy detection logic for rebases
Forward copy detection (i.e. detecting what files have been moved/copied in
commit X since ancestor Y) previously required diff'ing the manifests of both X
and Y. This was expensive since it required reading both entire manifests and
doing a set difference (they weren't already in a set because of the
lazymanifest work). This cost almost 1 second on very large repositories, and
happens N times for a rebase of N commits.
This patch optimizes it for the case of rebase. In a rebase, we are comparing a
commit against it's immediate parent, and therefore we can know what files
changed by looking at ctx.files(). This lets us drastically decrease the size
of the set comparison, and makes it O(# of changes) instead of O(size of
manifest). This makes it take 1ms instead of 1000ms.
# changelog bisection for mercurial
#
# Copyright 2007 Matt Mackall
# Copyright 2005, 2006 Benoit Boissinot <benoit.boissinot@ens-lyon.org>
#
# Inspired by git bisect, extension skeleton taken from mq.py.
#
# This software may be used and distributed according to the terms of the
# GNU General Public License version 2 or any later version.
from __future__ import absolute_import
import collections
from .i18n import _
from .node import (
hex,
short,
)
from . import (
error,
)
def bisect(changelog, state):
"""find the next node (if any) for testing during a bisect search.
returns a (nodes, number, good) tuple.
'nodes' is the final result of the bisect if 'number' is 0.
Otherwise 'number' indicates the remaining possible candidates for
the search and 'nodes' contains the next bisect target.
'good' is True if bisect is searching for a first good changeset, False
if searching for a first bad one.
"""
clparents = changelog.parentrevs
skip = set([changelog.rev(n) for n in state['skip']])
def buildancestors(bad, good):
# only the earliest bad revision matters
badrev = min([changelog.rev(n) for n in bad])
goodrevs = [changelog.rev(n) for n in good]
goodrev = min(goodrevs)
# build visit array
ancestors = [None] * (len(changelog) + 1) # an extra for [-1]
# set nodes descended from goodrevs
for rev in goodrevs:
ancestors[rev] = []
for rev in changelog.revs(goodrev + 1):
for prev in clparents(rev):
if ancestors[prev] == []:
ancestors[rev] = []
# clear good revs from array
for rev in goodrevs:
ancestors[rev] = None
for rev in changelog.revs(len(changelog), goodrev):
if ancestors[rev] is None:
for prev in clparents(rev):
ancestors[prev] = None
if ancestors[badrev] is None:
return badrev, None
return badrev, ancestors
good = False
badrev, ancestors = buildancestors(state['bad'], state['good'])
if not ancestors: # looking for bad to good transition?
good = True
badrev, ancestors = buildancestors(state['good'], state['bad'])
bad = changelog.node(badrev)
if not ancestors: # now we're confused
if (len(state['bad']) == 1 and len(state['good']) == 1 and
state['bad'] != state['good']):
raise error.Abort(_("starting revisions are not directly related"))
raise error.Abort(_("inconsistent state, %s:%s is good and bad")
% (badrev, short(bad)))
# build children dict
children = {}
visit = collections.deque([badrev])
candidates = []
while visit:
rev = visit.popleft()
if ancestors[rev] == []:
candidates.append(rev)
for prev in clparents(rev):
if prev != -1:
if prev in children:
children[prev].append(rev)
else:
children[prev] = [rev]
visit.append(prev)
candidates.sort()
# have we narrowed it down to one entry?
# or have all other possible candidates besides 'bad' have been skipped?
tot = len(candidates)
unskipped = [c for c in candidates if (c not in skip) and (c != badrev)]
if tot == 1 or not unskipped:
return ([changelog.node(rev) for rev in candidates], 0, good)
perfect = tot // 2
# find the best node to test
best_rev = None
best_len = -1
poison = set()
for rev in candidates:
if rev in poison:
# poison children
poison.update(children.get(rev, []))
continue
a = ancestors[rev] or [rev]
ancestors[rev] = None
x = len(a) # number of ancestors
y = tot - x # number of non-ancestors
value = min(x, y) # how good is this test?
if value > best_len and rev not in skip:
best_len = value
best_rev = rev
if value == perfect: # found a perfect candidate? quit early
break
if y < perfect and rev not in skip: # all downhill from here?
# poison children
poison.update(children.get(rev, []))
continue
for c in children.get(rev, []):
if ancestors[c]:
ancestors[c] = list(set(ancestors[c] + a))
else:
ancestors[c] = a + [c]
assert best_rev is not None
best_node = changelog.node(best_rev)
return ([best_node], tot, good)
def load_state(repo):
state = {'current': [], 'good': [], 'bad': [], 'skip': []}
for l in repo.vfs.tryreadlines("bisect.state"):
kind, node = l[:-1].split()
node = repo.lookup(node)
if kind not in state:
raise error.Abort(_("unknown bisect kind %s") % kind)
state[kind].append(node)
return state
def save_state(repo, state):
f = repo.vfs("bisect.state", "w", atomictemp=True)
with repo.wlock():
for kind in sorted(state):
for node in state[kind]:
f.write("%s %s\n" % (kind, hex(node)))
f.close()
def get(repo, status):
"""
Return a list of revision(s) that match the given status:
- ``good``, ``bad``, ``skip``: csets explicitly marked as good/bad/skip
- ``goods``, ``bads`` : csets topologically good/bad
- ``range`` : csets taking part in the bisection
- ``pruned`` : csets that are goods, bads or skipped
- ``untested`` : csets whose fate is yet unknown
- ``ignored`` : csets ignored due to DAG topology
- ``current`` : the cset currently being bisected
"""
state = load_state(repo)
if status in ('good', 'bad', 'skip', 'current'):
return map(repo.changelog.rev, state[status])
else:
# In the following sets, we do *not* call 'bisect()' with more
# than one level of recursion, because that can be very, very
# time consuming. Instead, we always develop the expression as
# much as possible.
# 'range' is all csets that make the bisection:
# - have a good ancestor and a bad descendant, or conversely
# that's because the bisection can go either way
range = '( bisect(bad)::bisect(good) | bisect(good)::bisect(bad) )'
_t = repo.revs('bisect(good)::bisect(bad)')
# The sets of topologically good or bad csets
if len(_t) == 0:
# Goods are topologically after bads
goods = 'bisect(good)::' # Pruned good csets
bads = '::bisect(bad)' # Pruned bad csets
else:
# Goods are topologically before bads
goods = '::bisect(good)' # Pruned good csets
bads = 'bisect(bad)::' # Pruned bad csets
# 'pruned' is all csets whose fate is already known: good, bad, skip
skips = 'bisect(skip)' # Pruned skipped csets
pruned = '( (%s) | (%s) | (%s) )' % (goods, bads, skips)
# 'untested' is all cset that are- in 'range', but not in 'pruned'
untested = '( (%s) - (%s) )' % (range, pruned)
# 'ignored' is all csets that were not used during the bisection
# due to DAG topology, but may however have had an impact.
# E.g., a branch merged between bads and goods, but whose branch-
# point is out-side of the range.
iba = '::bisect(bad) - ::bisect(good)' # Ignored bads' ancestors
iga = '::bisect(good) - ::bisect(bad)' # Ignored goods' ancestors
ignored = '( ( (%s) | (%s) ) - (%s) )' % (iba, iga, range)
if status == 'range':
return repo.revs(range)
elif status == 'pruned':
return repo.revs(pruned)
elif status == 'untested':
return repo.revs(untested)
elif status == 'ignored':
return repo.revs(ignored)
elif status == "goods":
return repo.revs(goods)
elif status == "bads":
return repo.revs(bads)
else:
raise error.ParseError(_('invalid bisect state'))
def label(repo, node):
rev = repo.changelog.rev(node)
# Try explicit sets
if rev in get(repo, 'good'):
# i18n: bisect changeset status
return _('good')
if rev in get(repo, 'bad'):
# i18n: bisect changeset status
return _('bad')
if rev in get(repo, 'skip'):
# i18n: bisect changeset status
return _('skipped')
if rev in get(repo, 'untested') or rev in get(repo, 'current'):
# i18n: bisect changeset status
return _('untested')
if rev in get(repo, 'ignored'):
# i18n: bisect changeset status
return _('ignored')
# Try implicit sets
if rev in get(repo, 'goods'):
# i18n: bisect changeset status
return _('good (implicit)')
if rev in get(repo, 'bads'):
# i18n: bisect changeset status
return _('bad (implicit)')
return None
def shortlabel(label):
if label:
return label[0].upper()
return None