1 """Discussion of bloom constants for bup:
3 There are four basic things to consider when building a bloom filter:
4 The size, in bits, of the filter
5 The capacity, in entries, of the filter
6 The probability of a false positive that is tolerable
7 The number of bits readily available to use for addresing filter bits
9 There is one major tunable that is not directly related to the above:
10 k: the number of bits set in the filter per entry
12 Here's a wall of numbers showing the relationship between k; the ratio between
13 the filter size in bits and the entries in the filter; and pfalse_positive:
15 mn|k=3 |k=4 |k=5 |k=6 |k=7 |k=8 |k=9 |k=10 |k=11
16 8|3.05794|2.39687|2.16792|2.15771|2.29297|2.54917|2.92244|3.41909|4.05091
17 9|2.27780|1.65770|1.40703|1.32721|1.34892|1.44631|1.61138|1.84491|2.15259
18 10|1.74106|1.18133|0.94309|0.84362|0.81937|0.84555|0.91270|1.01859|1.16495
19 11|1.36005|0.86373|0.65018|0.55222|0.51259|0.50864|0.53098|0.57616|0.64387
20 12|1.08231|0.64568|0.45945|0.37108|0.32939|0.31424|0.31695|0.33387|0.36380
21 13|0.87517|0.49210|0.33183|0.25527|0.21689|0.19897|0.19384|0.19804|0.21013
22 14|0.71759|0.38147|0.24433|0.17934|0.14601|0.12887|0.12127|0.12012|0.12399
23 15|0.59562|0.30019|0.18303|0.12840|0.10028|0.08523|0.07749|0.07440|0.07468
24 16|0.49977|0.23941|0.13925|0.09351|0.07015|0.05745|0.05049|0.04700|0.04587
25 17|0.42340|0.19323|0.10742|0.06916|0.04990|0.03941|0.03350|0.03024|0.02870
26 18|0.36181|0.15765|0.08392|0.05188|0.03604|0.02748|0.02260|0.01980|0.01827
27 19|0.31160|0.12989|0.06632|0.03942|0.02640|0.01945|0.01549|0.01317|0.01182
28 20|0.27026|0.10797|0.05296|0.03031|0.01959|0.01396|0.01077|0.00889|0.00777
29 21|0.23591|0.09048|0.04269|0.02356|0.01471|0.01014|0.00759|0.00609|0.00518
30 22|0.20714|0.07639|0.03473|0.01850|0.01117|0.00746|0.00542|0.00423|0.00350
31 23|0.18287|0.06493|0.02847|0.01466|0.00856|0.00555|0.00392|0.00297|0.00240
32 24|0.16224|0.05554|0.02352|0.01171|0.00663|0.00417|0.00286|0.00211|0.00166
33 25|0.14459|0.04779|0.01957|0.00944|0.00518|0.00316|0.00211|0.00152|0.00116
34 26|0.12942|0.04135|0.01639|0.00766|0.00408|0.00242|0.00157|0.00110|0.00082
35 27|0.11629|0.03595|0.01381|0.00626|0.00324|0.00187|0.00118|0.00081|0.00059
36 28|0.10489|0.03141|0.01170|0.00515|0.00259|0.00146|0.00090|0.00060|0.00043
37 29|0.09492|0.02756|0.00996|0.00426|0.00209|0.00114|0.00069|0.00045|0.00031
38 30|0.08618|0.02428|0.00853|0.00355|0.00169|0.00090|0.00053|0.00034|0.00023
39 31|0.07848|0.02147|0.00733|0.00297|0.00138|0.00072|0.00041|0.00025|0.00017
40 32|0.07167|0.01906|0.00633|0.00250|0.00113|0.00057|0.00032|0.00019|0.00013
42 Here's a table showing available repository size for a given pfalse_positive
43 and three values of k (assuming we only use the 160 bit SHA1 for addressing the
44 filter and 8192bytes per object):
46 pfalse|obj k=4 |cap k=4 |obj k=5 |cap k=5 |obj k=6 |cap k=6
47 2.500%|139333497228|1038.11 TiB|558711157|4262.63 GiB|13815755|105.41 GiB
48 1.000%|104489450934| 778.50 TiB|436090254|3327.10 GiB|11077519| 84.51 GiB
49 0.125%| 57254889824| 426.58 TiB|261732190|1996.86 GiB| 7063017| 55.89 GiB
51 This eliminates pretty neatly any k>6 as long as we use the raw SHA for
54 filter size scales linearly with repository size for a given k and pfalse.
56 Here's a table of filter sizes for a 1 TiB repository:
58 pfalse| k=3 | k=4 | k=5 | k=6
59 2.500%| 138.78 MiB | 126.26 MiB | 123.00 MiB | 123.37 MiB
60 1.000%| 197.83 MiB | 168.36 MiB | 157.58 MiB | 153.87 MiB
61 0.125%| 421.14 MiB | 307.26 MiB | 262.56 MiB | 241.32 MiB
64 * We want the bloom filter to fit in memory; if it doesn't, the k pagefaults
65 per lookup will be worse than the two required for midx.
66 * We want the pfalse_positive to be low enough that the cost of sometimes
67 faulting on the midx doesn't overcome the benefit of the bloom filter.
68 * We have readily available 160 bits for addressing the filter.
69 * We want to be able to have a single bloom address entire repositories of
72 Based on these parameters, a combination of k=4 and k=5 provides the behavior
73 that bup needs. As such, I've implemented bloom addressing, adding and
74 checking functions in C for these two values. Because k=5 requires less space
75 and gives better overall pfalse_positive perofrmance, it is preferred if a
76 table with k=5 can represent the repository.
78 None of this tells us what max_pfalse_positive to choose.
80 Brandon Low <lostlogic@lostlogicx.com> 2011-02-04
82 import sys, os, math, mmap
83 from bup import _helpers
84 from bup.helpers import *
87 MAX_BITS_EACH = 32 # Kinda arbitrary, but 4 bytes per entry is pretty big
88 MAX_BLOOM_BITS = {4: 37, 5: 29} # 160/k-log2(8)
89 MAX_PFALSE_POSITIVE = 1. # Totally arbitrary, needs benchmarking
94 bloom_contains = _helpers.bloom_contains
95 bloom_add = _helpers.bloom_add
99 """Wrapper which contains data from multiple index files. """
100 def __init__(self, filename, f=None, readwrite=False, expected=-1):
104 assert(filename.endswith('.bloom'))
107 self.rwfile = f = f or open(filename, 'r+b')
110 # Decide if we want to mmap() the pages as writable ('immediate'
111 # write) or else map them privately for later writing back to
112 # the file ('delayed' write). A bloom table's write access
113 # pattern is such that we dirty almost all the pages after adding
114 # very few entries. But the table is so big that dirtying
115 # *all* the pages often exceeds Linux's default
116 # /proc/sys/vm/dirty_ratio or /proc/sys/vm/dirty_background_ratio,
117 # thus causing it to start flushing the table before we're
118 # finished... even though there's more than enough space to
119 # store the bloom table in RAM.
121 # To work around that behaviour, if we calculate that we'll
122 # probably end up touching the whole table anyway (at least
123 # one bit flipped per memory page), let's use a "private" mmap,
124 # which defeats Linux's ability to flush it to disk. Then we'll
125 # flush it as one big lump during close().
126 pages = os.fstat(f.fileno()).st_size / 4096 * 5 # assume k=5
127 self.delaywrite = expected > pages
128 debug1('bloom: delaywrite=%r\n' % self.delaywrite)
130 self.map = mmap_readwrite_private(self.rwfile, close=False)
132 self.map = mmap_readwrite(self.rwfile, close=False)
135 f = f or open(filename, 'rb')
136 self.map = mmap_read(f)
137 got = str(self.map[0:4])
139 log('Warning: invalid BLOM header (%r) in %r\n' % (got, filename))
140 return self._init_failed()
141 ver = struct.unpack('!I', self.map[4:8])[0]
142 if ver < BLOOM_VERSION:
143 log('Warning: ignoring old-style (v%d) bloom %r\n'
145 return self._init_failed()
146 if ver > BLOOM_VERSION:
147 log('Warning: ignoring too-new (v%d) bloom %r\n'
149 return self._init_failed()
151 self.bits, self.k, self.entries = struct.unpack('!HHI', self.map[8:16])
152 idxnamestr = str(self.map[16 + 2**self.bits:])
154 self.idxnames = idxnamestr.split('\0')
158 def _init_failed(self):
165 self.bits = self.entries = 0
168 return self.map and self.bits
174 if self.map and self.rwfile:
175 debug2("bloom: closing with %d entries\n" % self.entries)
176 self.map[12:16] = struct.pack('!I', self.entries)
179 self.rwfile.write(self.map)
182 self.rwfile.seek(16 + 2**self.bits)
184 self.rwfile.write('\0'.join(self.idxnames))
187 def pfalse_positive(self, additional=0):
188 n = self.entries + additional
191 return 100*(1-math.exp(-k*float(n)/m))**k
193 def add_idx(self, ix):
194 """Add the object to the filter, return current pfalse_positive."""
196 raise Exception("Cannot add to closed bloom")
197 self.entries += bloom_add(self.map, ix.shatable, self.bits, self.k)
198 self.idxnames.append(os.path.basename(ix.name))
200 def exists(self, sha):
201 """Return nonempty if the object probably exists in the bloom filter.
203 If this function returns false, the object definitely does not exist.
204 If it returns true, there is a small probability that it exists
205 anyway, so you'll have to check it some other way.
207 global _total_searches, _total_steps
211 found, steps = bloom_contains(self.map, str(sha), self.bits, self.k)
212 _total_steps += steps
216 return int(self.entries)
219 def create(name, expected, delaywrite=None, f=None, k=None):
220 """Create and return a bloom filter for `expected` entries."""
221 bits = int(math.floor(math.log(expected*MAX_BITS_EACH/8,2)))
222 k = k or ((bits <= MAX_BLOOM_BITS[5]) and 5 or 4)
223 if bits > MAX_BLOOM_BITS[k]:
224 log('bloom: warning, max bits exceeded, non-optimal\n')
225 bits = MAX_BLOOM_BITS[k]
226 debug1('bloom: using 2^%d bytes and %d hash functions\n' % (bits, k))
227 f = f or open(name, 'w+b')
229 f.write(struct.pack('!IHHI', BLOOM_VERSION, bits, k, 0))
230 assert(f.tell() == 16)
231 # NOTE: On some systems this will not extend+zerofill, but it does on
232 # darwin, linux, bsd and solaris.
233 f.truncate(16+2**bits)
235 if delaywrite != None and not delaywrite:
236 # tell it to expect very few objects, forcing a direct mmap
238 return ShaBloom(name, f=f, readwrite=True, expected=expected)