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/*
* Copyright (C) 2014 Freie Universitรคt Berlin
*
* This file is subject to the terms and conditions of the GNU Lesser
* General Public License v2.1. See the file LICENSE in the top level
* directory for more details.
*/
/*
* bloom.c
*
* Bloom filters
*
* HISTORY
* {x, y, z}
* A Bloom filter is a probibalistic : : :
* data structure with several interesting /|\ /|\ /|\
* properties, such as low memory usage, / | X | X | \
* asymmetric query confidence, and a very / |/ \|/ \| \
* speedy O(k) membership test. / | | \ \
* / /| /|\ |\ \
* Because a Bloom filter can . . . . . . . . .
* accept any input that can be 00000000001000101010101010100010000000000
* hashed effectively (such as " " "
* strings), that membership test \ | /
* tends to draw a crowd. TNSTAAFL, but \ | /
* as caveats go, the Bloom filters' are \ | /
* more interesting than incapacitating. \|/
* :
* Most notably, it can tell you with certainty {w}
* that an item 'i' is *not* a member of set 's',
* but it can only tell you with some finite
* probability whether an item 'i' *is* a member
* of set 's'.
*
* Still, along with the intriguing possibility of using bitwise AND and OR
* to compute the logical union and intersection of two filters, the cheap
* cost of adding elements to the filter set, and the low memory requirements,
* the Bloom filter is a good choice for many applications.
*
* NOTES
*
* Let's look more closely at the probability values.
*
* Assume that a hash function selects each array position with equal
* probability. If m is the number of bits in the array, and k is the number
* of hash functions, then the probability that a certain bit is not set
* to 1 by a certain hash function during the insertion of an element is
*
* 1-(1/m).
*
* The probability that it is not set to 1 by any of the hash functions is
*
* (1-(1/m))^k.
*
* If we have inserted n elements, the probability that a certain bit is
* set 0 is
*
* (1-(1/m))^kn,
*
* Meaning that the probability said bit is set to 1 is therefore
*
* 1-([1-(1/m)]^kn).
*
* Now test membership of an element that is not in the set. Each of the k
* array positions computed by the hash functions is 1 with a probability
* as above. The probability of all of them being 1, which would cause the
* algorithm to erroneously claim that the element is in the set, is often
* given as
*
* (1-[1-(1/m)]^kn)^k ~~ (1 - e^(-kn/m))^k.
*
* This is not strictly correct as it assumes independence for the
* probabilities of each bit being set. However, assuming it is a close
* approximation we have that the probability of false positives descreases
* as m (the number of bits in the array) increases, and increases as n
* (the number of inserted elements) increases. For a given m and n, the
* value of k (the number of hash functions) that minimizes the probability
* is
*
* (m/n)ln(2) ~~ 0.7(m/n),
*
* which gives the false positive probability of
*
* 2^-k ~~ 0.6185^(m/n).
*
* The required number of bits m, given n and a desired false positive
* probability p (and assuming the optimal value of k is used) can be
* computed by substituting the optimal value of k in the probability
* expression above:
*
* p = (1 - e^(-(((m/n)ln(2))*(n/m))))^((m/n)ln(2)),
*
* which simplifies to
*
* ln(p) = -(m/n) * (ln2)^2.
*
* This results in the equation
*
* m = -((n*ln(p)) / ((ln(2))^2))
*
* The classic filter uses
*
* 1.44*log2(1/eta)
*
* bits of space per inserted key, where eta is the false positive rate of
* the Bloom filter.
*
*/
/**
* @defgroup sys_bloom Bloom filter
* @ingroup sys
* @brief Bloom filter library
* @{
*
* @file
* @brief Bloom filter API
*
* @author Christian Mehlis <mehlis@inf.fu-berlin.de>
*/
#ifndef _BLOOM_FILTER_H
#define _BLOOM_FILTER_H
#include <stdlib.h>
#include <stdbool.h>
#include <stdint.h>
#ifdef __cplusplus
extern "C" {
#endif
/**
* @brief hash function to use in thee filter
*/
typedef uint32_t (*hashfp_t)(const uint8_t *, int len);
/**
* @brief bloom_t bloom filter object
*/
typedef struct {
/** number of bits in the bloom array */
size_t m;
/** number of hash functions */
size_t k;
/** the bloom array */
uint8_t *a;
/** the hash functions */
hashfp_t *hash;
} bloom_t;
/**
* @brief Initialize a Bloom Filter.
*
* @note For best results, make 'size' a power of 2.
*
* @param bloom bloom_t to initialize
* @param size size of the bloom filter in bits
* @param bitfield underlying bitfield of the bloom filter
* @param hashes array of hashes
* @param hashes_numof number of elements in hashes
*
* @pre @p bitfield MUST be large enough to hold @p size bits.
*/
void bloom_init(bloom_t *bloom, size_t size, uint8_t *bitfield, hashfp_t *hashes, int hashes_numof);
/**
* @brief Delete a Bloom filter.
*
* @param bloom The condemned
* @return nothing
*
*/
void bloom_del(bloom_t *bloom);
/**
* @brief Add a string to a Bloom filter.
*
* CAVEAT
* Once a string has been added to the filter, it cannot be "removed"!
*
* @param bloom Bloom filter
* @param buf string to add
* @param len the length of the string @p buf
* @return nothing
*
*/
void bloom_add(bloom_t *bloom, const uint8_t *buf, size_t len);
/**
* @brief Determine if a string is in the Bloom filter.
*
* The string 's' is hashed once for each of the 'k' hash functions, as
* though we were planning to add it to the filter. Instead of adding it
* however, we examine the bit that we *would* have set, and consider its
* value.
*
* If the bit is 1 (set), the string we are hashing may be in the filter,
* since it would have set this bit when it was originally hashed. However,
* it may also be that another string just happened to produce a hash value
* that would also set this bit. That would be a false positive. This is why
* we have k > 1, so we can minimize the likelihood of false positives
* occuring.
*
* If every bit corresponding to every one of the k hashes of our query
* string is set, we can say with some probability of being correct that
* the string we are holding is indeed "in" the filter. However, we can
* never be sure.
*
* If, however, as we hash our string and peek at the resulting bit in the
* filter, we find the bit is 0 (not set)... well now, that's different.
* In this case, we can say with absolute certainty that the string we are
* holding is *not* in the filter, because if it were, this bit would have
* to be set.
*
* In this way, the Bloom filter can answer NO with absolute surety, but
* can only speak a qualified YES.
*
* @param bloom Bloom filter
* @param buf string to check
* @param len the length of the string @p buf
*
*
* @return false if string does not exist in the filter
* @return true if string is may be in the filter
*
*/
bool bloom_check(bloom_t *bloom, const uint8_t *buf, size_t len);
#ifdef __cplusplus
}
#endif
/** @} */
#endif /* _BLOOM_FILTER_H */
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