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strip: make query to get new bookmark target cheaper...
strip: make query to get new bookmark target cheaper The current query to get the new bookmark target for stripped revisions involves multiple walks up the DAG, and is really expensive, taking over 2.5 seconds on a repository with over 400,000 changesets even if just one changeset is being stripped. A slightly simplified version of the current query is max(heads(::<tostrip> - <tostrip>)) We make two observations here. 1. For any set s, max(heads(s)) == max(s). That is because revision numbers define a topological order, so that the element with the highest revision number in s will not have any children in s. 2. For any set s, max(::s - s) == max(parents(s) - s). In other words, the ancestor of s with the highest revision number not in s is a parent of one of the revs in s. Why? Because if it were an ancestor but not a parent of s, it would have a descendant that would be a parent of s. This descendant would have a higher revision number, leading to a contradiction. Combining these two observations, we rewrite the revset query as max(parents(<tostrip>) - <tostrip>) The time complexity is now linear in the number of changesets being stripped. For the above repository, the query now takes 0.1 seconds when one changeset is stripped. This speeds up operations that use repair.strip, like the rebase and strip commands.

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ancestor.py
255 lines | 7.4 KiB | text/x-python | PythonLexer
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 # ancestor.py - generic DAG ancestor algorithm for mercurial
#
# Copyright 2006 Matt Mackall <mpm@selenic.com>
#
Martin Geisler
updated license to be explicit about GPL version 2
r8225 # This software may be used and distributed according to the terms of the
Matt Mackall
Update license to GPLv2+
r10263 # GNU General Public License version 2 or any later version.
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135
import heapq
Siddharth Agarwal
ancestor: faster algorithm for difference of ancestor sets...
r17970 from node import nullrev
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135
def ancestor(a, b, pfunc):
"""
Matt Mackall
ancestor: improve description
r13554 Returns the common ancestor of a and b that is furthest from a
root (as measured by longest path) or None if no ancestor is
found. If there are multiple common ancestors at the same
distance, the first one found is returned.
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135
Sune Foldager
ancestor: improve docstring...
r9915 pfunc must return a list of parent vertices for a given vertex
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 """
if a == b:
return a
Matt Mackall
merge: sort arguments to stabilize the ancestor search
r11418 a, b = sorted([a, b])
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 # find depth from root of all ancestors
Matt Mackall
ancestor: improve description
r13554 # depth is stored as a negative for heapq
Nicolas Dumazet
ancestor: caching the parent list to improve performance...
r7882 parentcache = {}
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 visit = [a, b]
depth = {}
while visit:
vertex = visit[-1]
pl = pfunc(vertex)
Nicolas Dumazet
ancestor: caching the parent list to improve performance...
r7882 parentcache[vertex] = pl
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 if not pl:
depth[vertex] = 0
visit.pop()
else:
for p in pl:
Matt Mackall
backout most of 4f8067c94729
r12401 if p == a or p == b: # did we find a or b as a parent?
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 return p # we're done
if p not in depth:
visit.append(p)
if visit[-1] == vertex:
Matt Mackall
ancestor: improve description
r13554 # -(maximum distance of parents + 1)
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 depth[vertex] = min([depth[p] for p in pl]) - 1
visit.pop()
# traverse ancestors in order of decreasing distance from root
def ancestors(vertex):
h = [(depth[vertex], vertex)]
Benoit Boissinot
ancestor: use set instead of dict
r8465 seen = set()
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 while h:
d, n = heapq.heappop(h)
if n not in seen:
Benoit Boissinot
ancestor: use set instead of dict
r8465 seen.add(n)
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 yield (d, n)
Nicolas Dumazet
ancestor: caching the parent list to improve performance...
r7882 for p in parentcache[n]:
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 heapq.heappush(h, (depth[p], p))
def generations(vertex):
Benoit Boissinot
ancestor: use set instead of dict
r8465 sg, s = None, set()
Thomas Arendsen Hein
white space and line break cleanups
r3673 for g, v in ancestors(vertex):
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 if g != sg:
if sg:
yield sg, s
Benoit Boissinot
ancestor: use set instead of dict
r8465 sg, s = g, set((v,))
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 else:
Benoit Boissinot
ancestor: use set instead of dict
r8465 s.add(v)
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 yield sg, s
x = generations(a)
y = generations(b)
gx = x.next()
gy = y.next()
# increment each ancestor list until it is closer to root than
# the other, or they match
try:
Martin Geisler
check-code: flag 0/1 used as constant Boolean expression
r14494 while True:
Matt Mackall
Abstract ancestor algorithm into generic function...
r3135 if gx[0] == gy[0]:
for v in gx[1]:
if v in gy[1]:
return v
gy = y.next()
gx = x.next()
elif gx[0] > gy[0]:
gy = y.next()
else:
gx = x.next()
except StopIteration:
return None
Siddharth Agarwal
ancestor: faster algorithm for difference of ancestor sets...
r17970
def missingancestors(revs, bases, pfunc):
"""Return all the ancestors of revs that are not ancestors of bases.
This may include elements from revs.
Equivalent to the revset (::revs - ::bases). Revs are returned in
revision number order, which is a topological order.
revs and bases should both be iterables. pfunc must return a list of
parent revs for a given revs.
graph is a dict of child->parent adjacency lists for this graph:
o 13
|
| o 12
| |
| | o 11
| | |\
| | | | o 10
| | | | |
| o---+ | 9
| | | | |
o | | | | 8
/ / / /
| | o | 7
| | | |
o---+ | 6
/ / /
| | o 5
| |/
| o 4
| |
o | 3
| |
| o 2
|/
o 1
|
o 0
>>> graph = {0: [-1], 1: [0], 2: [1], 3: [1], 4: [2], 5: [4], 6: [4],
... 7: [4], 8: [-1], 9: [6, 7], 10: [5], 11: [3, 7], 12: [9],
... 13: [8]}
>>> pfunc = graph.get
Empty revs
>>> missingancestors([], [1], pfunc)
[]
>>> missingancestors([], [], pfunc)
[]
If bases is empty, it's the same as if it were [nullrev]
>>> missingancestors([12], [], pfunc)
[0, 1, 2, 4, 6, 7, 9, 12]
Trivial case: revs == bases
>>> missingancestors([0], [0], pfunc)
[]
>>> missingancestors([4, 5, 6], [6, 5, 4], pfunc)
[]
With nullrev
>>> missingancestors([-1], [12], pfunc)
[]
>>> missingancestors([12], [-1], pfunc)
[0, 1, 2, 4, 6, 7, 9, 12]
9 is a parent of 12. 7 is a parent of 9, so an ancestor of 12. 6 is an
ancestor of 12 but not of 7.
>>> missingancestors([12], [9], pfunc)
[12]
>>> missingancestors([9], [12], pfunc)
[]
>>> missingancestors([12, 9], [7], pfunc)
[6, 9, 12]
>>> missingancestors([7, 6], [12], pfunc)
[]
More complex cases
>>> missingancestors([10], [11, 12], pfunc)
[5, 10]
>>> missingancestors([11], [10], pfunc)
[3, 7, 11]
>>> missingancestors([11], [10, 12], pfunc)
[3, 11]
>>> missingancestors([12], [10], pfunc)
[6, 7, 9, 12]
>>> missingancestors([12], [11], pfunc)
[6, 9, 12]
>>> missingancestors([10, 11, 12], [13], pfunc)
[0, 1, 2, 3, 4, 5, 6, 7, 9, 10, 11, 12]
>>> missingancestors([13], [10, 11, 12], pfunc)
[8, 13]
"""
revsvisit = set(revs)
basesvisit = set(bases)
if not revsvisit:
return []
if not basesvisit:
basesvisit.add(nullrev)
start = max(max(revsvisit), max(basesvisit))
bothvisit = revsvisit.intersection(basesvisit)
revsvisit.difference_update(bothvisit)
basesvisit.difference_update(bothvisit)
# At this point, we hold the invariants that:
# - revsvisit is the set of nodes we know are an ancestor of at least one
# of the nodes in revs
# - basesvisit is the same for bases
# - bothvisit is the set of nodes we know are ancestors of at least one of
# the nodes in revs and one of the nodes in bases
# - a node may be in none or one, but not more, of revsvisit, basesvisit
# and bothvisit at any given time
# Now we walk down in reverse topo order, adding parents of nodes already
# visited to the sets while maintaining the invariants. When a node is
# found in both revsvisit and basesvisit, it is removed from them and
# added to bothvisit instead. When revsvisit becomes empty, there are no
# more ancestors of revs that aren't also ancestors of bases, so exit.
missing = []
for curr in xrange(start, nullrev, -1):
if not revsvisit:
break
if curr in bothvisit:
bothvisit.remove(curr)
# curr's parents might have made it into revsvisit or basesvisit
# through another path
for p in pfunc(curr):
revsvisit.discard(p)
basesvisit.discard(p)
bothvisit.add(p)
continue
# curr will never be in both revsvisit and basesvisit, since if it
# were it'd have been pushed to bothvisit
if curr in revsvisit:
missing.append(curr)
thisvisit = revsvisit
othervisit = basesvisit
elif curr in basesvisit:
thisvisit = basesvisit
othervisit = revsvisit
else:
Siddharth Agarwal
ancestor: fix a comment (followup to 0b03454abae7)
r17976 # not an ancestor of revs or bases: ignore
Siddharth Agarwal
ancestor: faster algorithm for difference of ancestor sets...
r17970 continue
thisvisit.remove(curr)
for p in pfunc(curr):
if p == nullrev:
pass
elif p in othervisit or p in bothvisit:
# p is implicitly in thisvisit. This means p is or should be
# in bothvisit
revsvisit.discard(p)
basesvisit.discard(p)
bothvisit.add(p)
else:
# visit later
thisvisit.add(p)
missing.reverse()
return missing