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312 lines
7.6 KiB
Rust
312 lines
7.6 KiB
Rust
/* 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
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* file, You can obtain one at http://mozilla.org/MPL/2.0/. */
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//! Simple counting bloom filters.
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use fnv::FnvHasher;
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use std::hash::{Hash, Hasher};
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const KEY_SIZE: usize = 12;
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const ARRAY_SIZE: usize = 1 << KEY_SIZE;
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const KEY_MASK: u32 = (1 << KEY_SIZE) - 1;
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const KEY_SHIFT: usize = 16;
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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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pub struct BloomFilter {
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counters: [u8; ARRAY_SIZE],
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}
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impl Clone for BloomFilter {
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#[inline]
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fn clone(&self) -> BloomFilter {
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BloomFilter {
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counters: self.counters,
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}
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}
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}
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impl BloomFilter {
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/// Creates a new bloom filter.
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#[inline]
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pub fn new() -> BloomFilter {
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BloomFilter {
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counters: [0; ARRAY_SIZE],
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}
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}
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#[inline]
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fn first_slot(&self, hash: u32) -> &u8 {
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&self.counters[hash1(hash) as usize]
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}
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#[inline]
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fn first_mut_slot(&mut self, hash: u32) -> &mut u8 {
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&mut self.counters[hash1(hash) as usize]
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}
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#[inline]
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fn second_slot(&self, hash: u32) -> &u8 {
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&self.counters[hash2(hash) as usize]
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}
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#[inline]
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fn second_mut_slot(&mut self, hash: u32) -> &mut u8 {
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&mut self.counters[hash2(hash) as usize]
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}
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#[inline]
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pub fn clear(&mut self) {
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self.counters = [0; ARRAY_SIZE]
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}
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#[inline]
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fn insert_hash(&mut self, hash: u32) {
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{
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let slot1 = self.first_mut_slot(hash);
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if !full(slot1) {
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*slot1 += 1
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}
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}
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{
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let slot2 = self.second_mut_slot(hash);
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if !full(slot2) {
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*slot2 += 1
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}
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}
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}
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/// Inserts an item into the bloom filter.
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#[inline]
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pub fn insert<T: Hash>(&mut self, elem: &T) {
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self.insert_hash(hash(elem))
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}
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#[inline]
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fn remove_hash(&mut self, hash: u32) {
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{
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let slot1 = self.first_mut_slot(hash);
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if !full(slot1) {
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*slot1 -= 1
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}
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}
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{
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let slot2 = self.second_mut_slot(hash);
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if !full(slot2) {
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*slot2 -= 1
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}
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}
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}
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/// Removes an item from the bloom filter.
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#[inline]
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pub fn remove<T: Hash>(&mut self, elem: &T) {
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self.remove_hash(hash(elem))
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}
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#[inline]
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fn might_contain_hash(&self, hash: u32) -> bool {
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*self.first_slot(hash) != 0 && *self.second_slot(hash) != 0
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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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#[inline]
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pub fn might_contain<T: Hash>(&self, elem: &T) -> bool {
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self.might_contain_hash(hash(elem))
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}
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}
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#[inline]
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fn full(slot: &u8) -> bool {
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*slot == 0xff
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}
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#[inline]
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fn hash<T: Hash>(elem: &T) -> u32 {
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let mut hasher = FnvHasher::default();
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elem.hash(&mut hasher);
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let hash: u64 = hasher.finish();
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(hash >> 32) as u32 ^ (hash as u32)
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}
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#[inline]
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fn hash1(hash: u32) -> u32 {
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hash & KEY_MASK
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}
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#[inline]
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fn hash2(hash: u32) -> u32 {
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(hash >> KEY_SHIFT) & KEY_MASK
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}
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#[test]
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fn create_and_insert_some_stuff() {
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let mut bf = BloomFilter::new();
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for i in 0_usize .. 1000 {
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bf.insert(&i);
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}
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for i in 0_usize .. 1000 {
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assert!(bf.might_contain(&i));
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}
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let false_positives =
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(1001_usize .. 2000).filter(|i| bf.might_contain(i)).count();
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assert!(false_positives < 150, "{} is not < 150", false_positives); // 15%.
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for i in 0_usize .. 100 {
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bf.remove(&i);
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}
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for i in 100_usize .. 1000 {
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assert!(bf.might_contain(&i));
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}
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let false_positives = (0_usize .. 100).filter(|i| bf.might_contain(i)).count();
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assert!(false_positives < 20, "{} is not < 20", false_positives); // 20%.
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bf.clear();
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for i in 0_usize .. 2000 {
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assert!(!bf.might_contain(&i));
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}
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}
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#[cfg(feature = "unstable")]
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#[cfg(test)]
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mod bench {
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extern crate test;
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use std::hash::{Hash, Hasher, SipHasher};
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use super::BloomFilter;
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#[bench]
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fn create_insert_1000_remove_100_lookup_100(b: &mut test::Bencher) {
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b.iter(|| {
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let mut bf = BloomFilter::new();
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for i in 0_usize .. 1000 {
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bf.insert(&i);
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}
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for i in 0_usize .. 100 {
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bf.remove(&i);
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}
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for i in 100_usize .. 200 {
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test::black_box(bf.might_contain(&i));
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}
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});
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}
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#[bench]
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fn might_contain(b: &mut test::Bencher) {
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let mut bf = BloomFilter::new();
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for i in 0_usize .. 1000 {
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bf.insert(&i);
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}
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let mut i = 0_usize;
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b.bench_n(1000, |b| {
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b.iter(|| {
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test::black_box(bf.might_contain(&i));
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i += 1;
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});
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});
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}
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#[bench]
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fn insert(b: &mut test::Bencher) {
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let mut bf = BloomFilter::new();
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b.bench_n(1000, |b| {
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let mut i = 0_usize;
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b.iter(|| {
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test::black_box(bf.insert(&i));
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i += 1;
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});
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});
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}
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#[bench]
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fn remove(b: &mut test::Bencher) {
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let mut bf = BloomFilter::new();
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for i in 0_usize .. 1000 {
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bf.insert(&i);
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}
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b.bench_n(1000, |b| {
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let mut i = 0_usize;
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b.iter(|| {
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bf.remove(&i);
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i += 1;
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});
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});
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test::black_box(bf.might_contain(&0_usize));
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}
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#[bench]
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fn hash_a_uint(b: &mut test::Bencher) {
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let mut i = 0_usize;
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b.iter(|| {
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let mut hasher = SipHasher::default();
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i.hash(&mut hasher);
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test::black_box(hasher.finish());
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i += 1;
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})
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}
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}
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