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235 lines
7.5 KiB
C++
235 lines
7.5 KiB
C++
/* -*- Mode: C++; tab-width: 2; indent-tabs-mode: nil; c-basic-offset: 2 -*- */
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/* This Source Code Form is subject to the terms of the Mozilla Public
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* License, v. 2.0. If a copy of the MPL was not distributed with this file,
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* You can obtain one at http://mozilla.org/MPL/2.0/. */
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/*
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* A counting Bloom filter implementation. This allows consumers to
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* do fast probabilistic "is item X in set Y?" testing which will
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* never answer "no" when the correct answer is "yes" (but might
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* incorrectly answer "yes" when the correct answer is "no").
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*/
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#ifndef mozilla_BloomFilter_h_
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#define mozilla_BloomFilter_h_
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#include "mozilla/Assertions.h"
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#include "mozilla/Likely.h"
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#include "mozilla/StandardInteger.h"
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#include "mozilla/Util.h"
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#include <string.h>
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namespace mozilla {
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/*
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* This class implements a counting Bloom filter as described at
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* <http://en.wikipedia.org/wiki/Bloom_filter#Counting_filters>, with
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* 8-bit counters. This allows quick probabilistic answers to the
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* question "is object X in set Y?" where the contents of Y might not
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* be time-invariant. The probabilistic nature of the test means that
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* sometimes the answer will be "yes" when it should be "no". If the
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* answer is "no", then X is guaranteed not to be in Y.
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*
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* The filter is parametrized on KeySize, which is the size of the key
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* generated by each of hash functions used by the filter, in bits,
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* and the type of object T being added and removed. T must implement
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* a |uint32_t hash() const| method which returns a uint32_t hash key
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* that will be used to generate the two separate hash functions for
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* the Bloom filter. This hash key MUST be well-distributed for good
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* results! KeySize is not allowed to be larger than 16.
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*
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* The filter uses exactly 2**KeySize bytes of memory. From now on we
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* will refer to the memory used by the filter as M.
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*
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* The expected rate of incorrect "yes" answers depends on M and on
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* the number N of objects in set Y. As long as N is small compared
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* to M, the rate of such answers is expected to be approximately
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* 4*(N/M)**2 for this filter. In practice, if Y has a few hundred
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* elements then using a KeySize of 12 gives a reasonably low
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* incorrect answer rate. A KeySize of 12 has the additional benefit
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* of using exactly one page for the filter in typical hardware
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* configurations.
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*/
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template<unsigned KeySize, class T>
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class BloomFilter
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{
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/*
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* A counting Bloom filter with 8-bit counters. For now we assume
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* that having two hash functions is enough, but we may revisit that
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* decision later.
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*
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* The filter uses an array with 2**KeySize entries.
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*
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* Assuming a well-distributed hash function, a Bloom filter with
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* array size M containing N elements and
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* using k hash function has expected false positive rate exactly
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*
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* $ (1 - (1 - 1/M)^{kN})^k $
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*
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* because each array slot has a
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*
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* $ (1 - 1/M)^{kN} $
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*
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* chance of being 0, and the expected false positive rate is the
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* probability that all of the k hash functions will hit a nonzero
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* slot.
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*
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* For reasonable assumptions (M large, kN large, which should both
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* hold if we're worried about false positives) about M and kN this
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* becomes approximately
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*
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* $$ (1 - \exp(-kN/M))^k $$
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*
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* For our special case of k == 2, that's $(1 - \exp(-2N/M))^2$,
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* or in other words
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*
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* $$ N/M = -0.5 * \ln(1 - \sqrt(r)) $$
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*
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* where r is the false positive rate. This can be used to compute
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* the desired KeySize for a given load N and false positive rate r.
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*
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* If N/M is assumed small, then the false positive rate can
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* further be approximated as 4*N^2/M^2. So increasing KeySize by
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* 1, which doubles M, reduces the false positive rate by about a
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* factor of 4, and a false positive rate of 1% corresponds to
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* about M/N == 20.
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*
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* What this means in practice is that for a few hundred keys using a
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* KeySize of 12 gives false positive rates on the order of 0.25-4%.
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*
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* Similarly, using a KeySize of 10 would lead to a 4% false
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* positive rate for N == 100 and to quite bad false positive
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* rates for larger N.
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*/
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public:
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BloomFilter() {
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MOZ_STATIC_ASSERT(KeySize <= keyShift, "KeySize too big");
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// Should we have a custom operator new using calloc instead and
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// require that we're allocated via the operator?
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clear();
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}
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/*
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* Clear the filter. This should be done before reusing it, because
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* just removing all items doesn't clear counters that hit the upper
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* bound.
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*/
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void clear();
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/*
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* Add an item to the filter.
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*/
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void add(const T* t);
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/*
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* Remove an item from the filter.
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*/
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void remove(const T* t);
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/*
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* Check whether the filter might contain an item. This can
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* sometimes return true even if the item is not in the filter,
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* but will never return false for items that are actually in the
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* filter.
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*/
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bool mightContain(const T* t) const;
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/*
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* Methods for add/remove/contain when we already have a hash computed
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*/
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void add(uint32_t hash);
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void remove(uint32_t hash);
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bool mightContain(uint32_t hash) const;
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private:
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static const size_t arraySize = (1 << KeySize);
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static const uint32_t keyMask = (1 << KeySize) - 1;
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static const uint32_t keyShift = 16;
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static uint32_t hash1(uint32_t hash) { return hash & keyMask; }
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static uint32_t hash2(uint32_t hash) { return (hash >> keyShift) & keyMask; }
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uint8_t& firstSlot(uint32_t hash) { return counters[hash1(hash)]; }
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uint8_t& secondSlot(uint32_t hash) { return counters[hash2(hash)]; }
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const uint8_t& firstSlot(uint32_t hash) const { return counters[hash1(hash)]; }
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const uint8_t& secondSlot(uint32_t hash) const { return counters[hash2(hash)]; }
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static bool full(const uint8_t& slot) { return slot == UINT8_MAX; }
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uint8_t counters[arraySize];
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};
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template<unsigned KeySize, class T>
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inline void
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BloomFilter<KeySize, T>::clear()
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{
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memset(counters, 0, arraySize);
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}
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template<unsigned KeySize, class T>
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inline void
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BloomFilter<KeySize, T>::add(uint32_t hash)
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{
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uint8_t& slot1 = firstSlot(hash);
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if (MOZ_LIKELY(!full(slot1)))
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++slot1;
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uint8_t& slot2 = secondSlot(hash);
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if (MOZ_LIKELY(!full(slot2)))
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++slot2;
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}
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template<unsigned KeySize, class T>
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MOZ_ALWAYS_INLINE void
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BloomFilter<KeySize, T>::add(const T* t)
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{
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uint32_t hash = t->hash();
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return add(hash);
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}
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template<unsigned KeySize, class T>
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inline void
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BloomFilter<KeySize, T>::remove(uint32_t hash)
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{
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// If the slots are full, we don't know whether we bumped them to be
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// there when we added or not, so just leave them full.
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uint8_t& slot1 = firstSlot(hash);
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if (MOZ_LIKELY(!full(slot1)))
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--slot1;
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uint8_t& slot2 = secondSlot(hash);
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if (MOZ_LIKELY(!full(slot2)))
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--slot2;
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}
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template<unsigned KeySize, class T>
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MOZ_ALWAYS_INLINE void
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BloomFilter<KeySize, T>::remove(const T* t)
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{
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uint32_t hash = t->hash();
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remove(hash);
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}
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template<unsigned KeySize, class T>
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MOZ_ALWAYS_INLINE bool
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BloomFilter<KeySize, T>::mightContain(uint32_t hash) const
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{
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// Check that all the slots for this hash contain something
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return firstSlot(hash) && secondSlot(hash);
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}
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template<unsigned KeySize, class T>
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MOZ_ALWAYS_INLINE bool
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BloomFilter<KeySize, T>::mightContain(const T* t) const
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{
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uint32_t hash = t->hash();
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return mightContain(hash);
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}
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} // namespace mozilla
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#endif /* mozilla_BloomFilter_h_ */
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