Mercurial > hg
view mercurial/pvec.py @ 30451:94ca0e13d1fc
perf: add command for measuring revlog chunk operations
Upcoming commits will teach revlogs to leverage the new compression
engine API so that new compression formats can more easily be
leveraged in revlogs. We want to be sure this refactoring doesn't
regress performance. So this commit introduces "perfrevchunks" to
explicitly test performance of reading, decompressing, and
recompressing revlog chunks.
Here is output when run on the mozilla-unified repo:
$ hg perfrevlogchunks -c
! read
! wall 0.346603 comb 0.350000 user 0.340000 sys 0.010000 (best of 28)
! read w/ reused fd
! wall 0.337707 comb 0.340000 user 0.320000 sys 0.020000 (best of 30)
! read batch
! wall 0.013206 comb 0.020000 user 0.000000 sys 0.020000 (best of 221)
! read batch w/ reused fd
! wall 0.013259 comb 0.030000 user 0.010000 sys 0.020000 (best of 222)
! chunk
! wall 1.909939 comb 1.910000 user 1.900000 sys 0.010000 (best of 6)
! chunk batch
! wall 1.750677 comb 1.760000 user 1.740000 sys 0.020000 (best of 6)
! compress
! wall 5.668004 comb 5.670000 user 5.670000 sys 0.000000 (best of 3)
$ hg perfrevlogchunks -m
! read
! wall 0.365834 comb 0.370000 user 0.350000 sys 0.020000 (best of 26)
! read w/ reused fd
! wall 0.350160 comb 0.350000 user 0.320000 sys 0.030000 (best of 28)
! read batch
! wall 0.024777 comb 0.020000 user 0.000000 sys 0.020000 (best of 119)
! read batch w/ reused fd
! wall 0.024895 comb 0.030000 user 0.000000 sys 0.030000 (best of 118)
! chunk
! wall 2.514061 comb 2.520000 user 2.480000 sys 0.040000 (best of 4)
! chunk batch
! wall 2.380788 comb 2.380000 user 2.360000 sys 0.020000 (best of 5)
! compress
! wall 9.815297 comb 9.820000 user 9.820000 sys 0.000000 (best of 3)
We already see some interesting data, such as how much slower
non-batched chunk reading is and that zlib compression appears to be
>2x slower than decompression.
I didn't have the data when I wrote this commit message, but I ran this
on Mozilla's NFS-based Mercurial server and the time for reading with a
reused file descriptor was faster. So I think it is worth testing both
with and without file descriptor reuse so we can make informed
decisions about recycling file descriptors.
author | Gregory Szorc <gregory.szorc@gmail.com> |
---|---|
date | Thu, 17 Nov 2016 20:17:51 -0800 |
parents | 983e93d88193 |
children | 4462a981e8df |
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# 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