annotate mercurial/pvec.py @ 28960:14e683d6b273

transaction: clear callback instances after usage Prevents double usage and helps reduce reference cycles, which were observed to occur in `hg convert` and other scenarios where there are multiple transactions per process.
author Gregory Szorc <gregory.szorc@gmail.com>
date Sat, 16 Apr 2016 09:02:37 -0700
parents 983e93d88193
children 4462a981e8df
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1 # pvec.py - probabilistic vector clocks for Mercurial
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2 #
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3 # Copyright 2012 Matt Mackall <mpm@selenic.com>
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4 #
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5 # This software may be used and distributed according to the terms of the
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6 # GNU General Public License version 2 or any later version.
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7
0d175ac527c1 pvec: introduce pvecs
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8 '''
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9 A "pvec" is a changeset property based on the theory of vector clocks
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10 that can be compared to discover relatedness without consulting a
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11 graph. This can be useful for tasks like determining how a
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12 disconnected patch relates to a repository.
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13
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14 Currently a pvec consist of 448 bits, of which 24 are 'depth' and the
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15 remainder are a bit vector. It is represented as a 70-character base85
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16 string.
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17
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18 Construction:
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19
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20 - a root changeset has a depth of 0 and a bit vector based on its hash
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21 - a normal commit has a changeset where depth is increased by one and
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22 one bit vector bit is flipped based on its hash
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23 - a merge changeset pvec is constructed by copying changes from one pvec into
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24 the other to balance its depth
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25
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26 Properties:
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27
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28 - for linear changes, difference in depth is always <= hamming distance
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29 - otherwise, changes are probably divergent
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30 - when hamming distance is < 200, we can reliably detect when pvecs are near
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31
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32 Issues:
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33
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34 - hamming distance ceases to work over distances of ~ 200
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35 - detecting divergence is less accurate when the common ancestor is very close
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36 to either revision or total distance is high
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37 - this could probably be improved by modeling the relation between
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38 delta and hdist
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39
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40 Uses:
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41
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42 - a patch pvec can be used to locate the nearest available common ancestor for
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43 resolving conflicts
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44 - ordering of patches can be established without a DAG
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45 - two head pvecs can be compared to determine whether push/pull/merge is needed
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46 and approximately how many changesets are involved
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47 - can be used to find a heuristic divergence measure between changesets on
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48 different branches
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49 '''
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50
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51 from __future__ import absolute_import
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52
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53 from .node import nullrev
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54 from . import (
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55 base85,
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56 util,
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57 )
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58
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59 _size = 448 # 70 chars b85-encoded
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60 _bytes = _size / 8
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61 _depthbits = 24
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62 _depthbytes = _depthbits / 8
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63 _vecbytes = _bytes - _depthbytes
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64 _vecbits = _vecbytes * 8
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65 _radius = (_vecbits - 30) / 2 # high probability vectors are related
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66
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67 def _bin(bs):
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68 '''convert a bytestring to a long'''
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69 v = 0
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70 for b in bs:
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71 v = v * 256 + ord(b)
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72 return v
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73
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74 def _str(v, l):
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75 bs = ""
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76 for p in xrange(l):
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77 bs = chr(v & 255) + bs
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78 v >>= 8
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79 return bs
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80
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81 def _split(b):
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82 '''depth and bitvec'''
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83 return _bin(b[:_depthbytes]), _bin(b[_depthbytes:])
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84
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85 def _join(depth, bitvec):
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86 return _str(depth, _depthbytes) + _str(bitvec, _vecbytes)
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87
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88 def _hweight(x):
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89 c = 0
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90 while x:
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91 if x & 1:
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92 c += 1
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93 x >>= 1
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94 return c
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95 _htab = [_hweight(x) for x in xrange(256)]
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96
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97 def _hamming(a, b):
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98 '''find the hamming distance between two longs'''
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99 d = a ^ b
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100 c = 0
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101 while d:
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102 c += _htab[d & 0xff]
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103 d >>= 8
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104 return c
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105
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106 def _mergevec(x, y, c):
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107 # Ideally, this function would be x ^ y ^ ancestor, but finding
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108 # ancestors is a nuisance. So instead we find the minimal number
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109 # of changes to balance the depth and hamming distance
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110
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111 d1, v1 = x
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112 d2, v2 = y
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113 if d1 < d2:
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114 d1, d2, v1, v2 = d2, d1, v2, v1
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115
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116 hdist = _hamming(v1, v2)
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117 ddist = d1 - d2
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118 v = v1
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119 m = v1 ^ v2 # mask of different bits
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120 i = 1
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121
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122 if hdist > ddist:
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123 # if delta = 10 and hdist = 100, then we need to go up 55 steps
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124 # to the ancestor and down 45
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125 changes = (hdist - ddist + 1) / 2
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126 else:
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127 # must make at least one change
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128 changes = 1
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129 depth = d1 + changes
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130
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131 # copy changes from v2
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132 if m:
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133 while changes:
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134 if m & i:
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135 v ^= i
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136 changes -= 1
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137 i <<= 1
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138 else:
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139 v = _flipbit(v, c)
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140
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141 return depth, v
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142
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143 def _flipbit(v, node):
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144 # converting bit strings to longs is slow
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145 bit = (hash(node) & 0xffffffff) % _vecbits
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146 return v ^ (1<<bit)
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147
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148 def ctxpvec(ctx):
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149 '''construct a pvec for ctx while filling in the cache'''
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150 r = ctx.repo()
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151 if not util.safehasattr(r, "_pveccache"):
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152 r._pveccache = {}
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153 pvc = r._pveccache
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154 if ctx.rev() not in pvc:
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155 cl = r.changelog
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156 for n in xrange(ctx.rev() + 1):
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157 if n not in pvc:
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158 node = cl.node(n)
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159 p1, p2 = cl.parentrevs(n)
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160 if p1 == nullrev:
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161 # start with a 'random' vector at root
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162 pvc[n] = (0, _bin((node * 3)[:_vecbytes]))
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163 elif p2 == nullrev:
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164 d, v = pvc[p1]
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165 pvc[n] = (d + 1, _flipbit(v, node))
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166 else:
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167 pvc[n] = _mergevec(pvc[p1], pvc[p2], node)
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168 bs = _join(*pvc[ctx.rev()])
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169 return pvec(base85.b85encode(bs))
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170
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171 class pvec(object):
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172 def __init__(self, hashorctx):
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173 if isinstance(hashorctx, str):
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174 self._bs = hashorctx
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175 self._depth, self._vec = _split(base85.b85decode(hashorctx))
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176 else:
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177 self._vec = ctxpvec(hashorctx)
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178
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179 def __str__(self):
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180 return self._bs
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181
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182 def __eq__(self, b):
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183 return self._vec == b._vec and self._depth == b._depth
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184
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185 def __lt__(self, b):
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186 delta = b._depth - self._depth
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187 if delta < 0:
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188 return False # always correct
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189 if _hamming(self._vec, b._vec) > delta:
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190 return False
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191 return True
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192
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193 def __gt__(self, b):
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194 return b < self
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195
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196 def __or__(self, b):
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197 delta = abs(b._depth - self._depth)
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198 if _hamming(self._vec, b._vec) <= delta:
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199 return False
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200 return True
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201
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202 def __sub__(self, b):
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203 if self | b:
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204 raise ValueError("concurrent pvecs")
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205 return self._depth - b._depth
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206
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207 def distance(self, b):
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208 d = abs(b._depth - self._depth)
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209 h = _hamming(self._vec, b._vec)
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210 return max(d, h)
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211
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212 def near(self, b):
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213 dist = abs(b.depth - self._depth)
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214 if dist > _radius or _hamming(self._vec, b._vec) > _radius:
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215 return False