revset: optimize baseset.__sub__ (issue4313)
dd716807fd23 regressed performance of baseset.__sub__ by introducing
a lazyset. This patch restores that lost performance by eagerly
evaluating baseset.__sub__ if the other set is a baseset.
revsetbenchmark.py results impacted by this change:
revset #6: roots(0::tip)
0) wall 2.923473 comb 2.920000 user 2.920000 sys 0.000000 (best of 4)
1) wall 0.077614 comb 0.080000 user 0.080000 sys 0.000000 (best of 100)
revset #23: roots((0:tip)::)
0) wall 2.875178 comb 2.880000 user 2.880000 sys 0.000000 (best of 4)
1) wall 0.154519 comb 0.150000 user 0.150000 sys 0.000000 (best of 61)
On the author's machine, this slowdown manifested during evaluation of
'roots(%ln::)' in phases.retractboundary after unbundling the Firefox
repository. Using `time hg unbundle firefox.hg` as a benchmark:
Before: 8:00
After: 4:28
Delta: -3:32
For reference, the subset and cs baseset instances impacted by this
change were of lengths 193634 and 193627, respectively.
Explicit test coverage of roots(%ln::), while similar to the existing
roots(0::tip) benchmark, has been added.
# similar.py - mechanisms for finding similar files
#
# Copyright 2005-2007 Matt Mackall <mpm@selenic.com>
#
# This software may be used and distributed according to the terms of the
# GNU General Public License version 2 or any later version.
from i18n import _
import util
import mdiff
import bdiff
def _findexactmatches(repo, added, removed):
'''find renamed files that have no changes
Takes a list of new filectxs and a list of removed filectxs, and yields
(before, after) tuples of exact matches.
'''
numfiles = len(added) + len(removed)
# Get hashes of removed files.
hashes = {}
for i, fctx in enumerate(removed):
repo.ui.progress(_('searching for exact renames'), i, total=numfiles)
h = util.sha1(fctx.data()).digest()
hashes[h] = fctx
# For each added file, see if it corresponds to a removed file.
for i, fctx in enumerate(added):
repo.ui.progress(_('searching for exact renames'), i + len(removed),
total=numfiles)
h = util.sha1(fctx.data()).digest()
if h in hashes:
yield (hashes[h], fctx)
# Done
repo.ui.progress(_('searching for exact renames'), None)
def _findsimilarmatches(repo, added, removed, threshold):
'''find potentially renamed files based on similar file content
Takes a list of new filectxs and a list of removed filectxs, and yields
(before, after, score) tuples of partial matches.
'''
copies = {}
for i, r in enumerate(removed):
repo.ui.progress(_('searching for similar files'), i,
total=len(removed))
# lazily load text
@util.cachefunc
def data():
orig = r.data()
return orig, mdiff.splitnewlines(orig)
def score(text):
orig, lines = data()
# bdiff.blocks() returns blocks of matching lines
# count the number of bytes in each
equal = 0
matches = bdiff.blocks(text, orig)
for x1, x2, y1, y2 in matches:
for line in lines[y1:y2]:
equal += len(line)
lengths = len(text) + len(orig)
return equal * 2.0 / lengths
for a in added:
bestscore = copies.get(a, (None, threshold))[1]
myscore = score(a.data())
if myscore >= bestscore:
copies[a] = (r, myscore)
repo.ui.progress(_('searching'), None)
for dest, v in copies.iteritems():
source, score = v
yield source, dest, score
def findrenames(repo, added, removed, threshold):
'''find renamed files -- yields (before, after, score) tuples'''
parentctx = repo['.']
workingctx = repo[None]
# Zero length files will be frequently unrelated to each other, and
# tracking the deletion/addition of such a file will probably cause more
# harm than good. We strip them out here to avoid matching them later on.
addedfiles = set([workingctx[fp] for fp in added
if workingctx[fp].size() > 0])
removedfiles = set([parentctx[fp] for fp in removed
if fp in parentctx and parentctx[fp].size() > 0])
# Find exact matches.
for (a, b) in _findexactmatches(repo,
sorted(addedfiles), sorted(removedfiles)):
addedfiles.remove(b)
yield (a.path(), b.path(), 1.0)
# If the user requested similar files to be matched, search for them also.
if threshold < 1.0:
for (a, b, score) in _findsimilarmatches(repo,
sorted(addedfiles), sorted(removedfiles), threshold):
yield (a.path(), b.path(), score)