bloom.h

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/*
 * SPDX-FileCopyrightText: 2014 Freie Universität Berlin
 * SPDX-License-Identifier: LGPL-2.1-only
 */
 
#pragma once
 
/*
 * 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 decreases
 * 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.
 *
 */
 
#include <stdlib.h>
#include <stdbool.h>
#include <stdint.h>
 
#ifdef __cplusplus
extern "C" {
#endif
 
typedef uint32_t (*hashfp_t)(const uint8_t *, size_t len);
 
typedef struct {
    size_t m;
    size_t k;
    uint8_t *a;
    hashfp_t *hash;
} bloom_t;
 
void bloom_init(bloom_t *bloom, size_t size, uint8_t *bitfield, hashfp_t *hashes, int hashes_numof);
 
void bloom_del(bloom_t *bloom);
 
void bloom_add(bloom_t *bloom, const uint8_t *buf, size_t len);
 
bool bloom_check(bloom_t *bloom, const uint8_t *buf, size_t len);
 
#ifdef __cplusplus
}
#endif