changelog: add class to represent parsed changelog revisions
Currently, changelog entries are parsed into their respective
components at read time. Many operations are only interested
in a subset of fields of a changelog entry. The parsing and
storing of all the fields adds avoidable overhead.
This patch introduces the "changelogrevision" class. It takes
changelog raw text and exposes the parsed results as attributes.
The code for parsing changelog entries has been moved into its
construction function. changelog.read() has been modified to use
the new class internally while maintaining its existing API.
Future patches will make revision parsing lazy.
We implement the construction function of the new class with
__new__ instead of __init__ so we can use a named tuple to
represent the empty revision. This saves overhead and complexity
of coercing later versions of this class to represent an empty
instance.
While we are here, we add a method on changelog to obtain an
instance of the new type.
The overhead of constructing the new class regresses performance
of revsets accessing this data:
author(mpm)
0.896565
0.929984
desc(bug)
0.887169
0.935642 105%
date(2015)
0.878797
0.908094
extra(rebase_source)
0.865446
0.922624 106%
author(mpm) or author(greg)
1.801832
1.902112 105%
author(mpm) or desc(bug)
1.812438
1.860977
date(2015) or branch(default)
0.968276
1.005824
author(mpm) or desc(bug) or date(2015) or extra(rebase_source)
3.656193
3.743381
Once lazy parsing is implemented, these revsets will all be faster
than before. There is no performance change on revsets that do not
access this data. There /could/ be a performance regression on
operations that perform several changelog reads. However, I can't
think of anything outside of revsets and `hg log` (basically the
same as a revset) that would be impacted.
# pvec.py - probabilistic vector clocks for Mercurial
#
# Copyright 2012 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.
'''
A "pvec" is a changeset property based on the theory of vector clocks
that can be compared to discover relatedness without consulting a
graph. This can be useful for tasks like determining how a
disconnected patch relates to a repository.
Currently a pvec consist of 448 bits, of which 24 are 'depth' and the
remainder are a bit vector. It is represented as a 70-character base85
string.
Construction:
- a root changeset has a depth of 0 and a bit vector based on its hash
- a normal commit has a changeset where depth is increased by one and
one bit vector bit is flipped based on its hash
- a merge changeset pvec is constructed by copying changes from one pvec into
the other to balance its depth
Properties:
- for linear changes, difference in depth is always <= hamming distance
- otherwise, changes are probably divergent
- when hamming distance is < 200, we can reliably detect when pvecs are near
Issues:
- hamming distance ceases to work over distances of ~ 200
- detecting divergence is less accurate when the common ancestor is very close
to either revision or total distance is high
- this could probably be improved by modeling the relation between
delta and hdist
Uses:
- a patch pvec can be used to locate the nearest available common ancestor for
resolving conflicts
- ordering of patches can be established without a DAG
- two head pvecs can be compared to determine whether push/pull/merge is needed
and approximately how many changesets are involved
- can be used to find a heuristic divergence measure between changesets on
different branches
'''
from __future__ import absolute_import
from .node import nullrev
from . import (
base85,
util,
)
_size = 448 # 70 chars b85-encoded
_bytes = _size / 8
_depthbits = 24
_depthbytes = _depthbits / 8
_vecbytes = _bytes - _depthbytes
_vecbits = _vecbytes * 8
_radius = (_vecbits - 30) / 2 # high probability vectors are related
def _bin(bs):
'''convert a bytestring to a long'''
v = 0
for b in bs:
v = v * 256 + ord(b)
return v
def _str(v, l):
bs = ""
for p in xrange(l):
bs = chr(v & 255) + bs
v >>= 8
return bs
def _split(b):
'''depth and bitvec'''
return _bin(b[:_depthbytes]), _bin(b[_depthbytes:])
def _join(depth, bitvec):
return _str(depth, _depthbytes) + _str(bitvec, _vecbytes)
def _hweight(x):
c = 0
while x:
if x & 1:
c += 1
x >>= 1
return c
_htab = [_hweight(x) for x in xrange(256)]
def _hamming(a, b):
'''find the hamming distance between two longs'''
d = a ^ b
c = 0
while d:
c += _htab[d & 0xff]
d >>= 8
return c
def _mergevec(x, y, c):
# Ideally, this function would be x ^ y ^ ancestor, but finding
# ancestors is a nuisance. So instead we find the minimal number
# of changes to balance the depth and hamming distance
d1, v1 = x
d2, v2 = y
if d1 < d2:
d1, d2, v1, v2 = d2, d1, v2, v1
hdist = _hamming(v1, v2)
ddist = d1 - d2
v = v1
m = v1 ^ v2 # mask of different bits
i = 1
if hdist > ddist:
# if delta = 10 and hdist = 100, then we need to go up 55 steps
# to the ancestor and down 45
changes = (hdist - ddist + 1) / 2
else:
# must make at least one change
changes = 1
depth = d1 + changes
# copy changes from v2
if m:
while changes:
if m & i:
v ^= i
changes -= 1
i <<= 1
else:
v = _flipbit(v, c)
return depth, v
def _flipbit(v, node):
# converting bit strings to longs is slow
bit = (hash(node) & 0xffffffff) % _vecbits
return v ^ (1<<bit)
def ctxpvec(ctx):
'''construct a pvec for ctx while filling in the cache'''
r = ctx.repo()
if not util.safehasattr(r, "_pveccache"):
r._pveccache = {}
pvc = r._pveccache
if ctx.rev() not in pvc:
cl = r.changelog
for n in xrange(ctx.rev() + 1):
if n not in pvc:
node = cl.node(n)
p1, p2 = cl.parentrevs(n)
if p1 == nullrev:
# start with a 'random' vector at root
pvc[n] = (0, _bin((node * 3)[:_vecbytes]))
elif p2 == nullrev:
d, v = pvc[p1]
pvc[n] = (d + 1, _flipbit(v, node))
else:
pvc[n] = _mergevec(pvc[p1], pvc[p2], node)
bs = _join(*pvc[ctx.rev()])
return pvec(base85.b85encode(bs))
class pvec(object):
def __init__(self, hashorctx):
if isinstance(hashorctx, str):
self._bs = hashorctx
self._depth, self._vec = _split(base85.b85decode(hashorctx))
else:
self._vec = ctxpvec(hashorctx)
def __str__(self):
return self._bs
def __eq__(self, b):
return self._vec == b._vec and self._depth == b._depth
def __lt__(self, b):
delta = b._depth - self._depth
if delta < 0:
return False # always correct
if _hamming(self._vec, b._vec) > delta:
return False
return True
def __gt__(self, b):
return b < self
def __or__(self, b):
delta = abs(b._depth - self._depth)
if _hamming(self._vec, b._vec) <= delta:
return False
return True
def __sub__(self, b):
if self | b:
raise ValueError("concurrent pvecs")
return self._depth - b._depth
def distance(self, b):
d = abs(b._depth - self._depth)
h = _hamming(self._vec, b._vec)
return max(d, h)
def near(self, b):
dist = abs(b.depth - self._depth)
if dist > _radius or _hamming(self._vec, b._vec) > _radius:
return False