# cython: infer_types=True # cython: cdivision=True # from murmurhash.mrmr cimport hash128_x86 import math from array import array try: import copy_reg except ImportError: import copyreg as copy_reg def calculate_size_and_hash_count(members, error_rate): """Calculate the optimal size in bits and number of hash functions for a given number of members and error rate. """ base = math.log(1 / (2 ** math.log(2))) bit_count = math.ceil((members * math.log(error_rate)) / base) hash_count = math.floor((bit_count / members) * math.log(2)) return (bit_count, hash_count) cdef class BloomFilter: """Bloom filter that allows for basic membership tests. Only integers are supported as keys. """ def __init__(self, key_t size=(2 ** 10), key_t hash_funcs=23, uint32_t seed=0): self.mem = Pool() self.c_bloom = self.mem.alloc(1, sizeof(BloomStruct)) bloom_init(self.mem, self.c_bloom, hash_funcs, size, seed) @classmethod def from_error_rate(cls, members, error_rate=1E-4): params = calculate_size_and_hash_count(members, error_rate) return cls(*params) def add(self, key_t item): bloom_add(self.c_bloom, item) def __contains__(self, item): return bloom_contains(self.c_bloom, item) cdef inline bint contains(self, key_t item) nogil: return bloom_contains(self.c_bloom, item) def to_bytes(self): return bloom_to_bytes(self.c_bloom) def from_bytes(self, bytes byte_string): bloom_from_bytes(self.mem, self.c_bloom, byte_string) return self cdef bytes bloom_to_bytes(const BloomStruct* bloom): py = array("L") py.append(bloom.hcount) py.append(bloom.length) py.append(bloom.seed) for i in range(bloom.length // sizeof(key_t)): py.append(bloom.bitfield[i]) if hasattr(py, "tobytes"): return py.tobytes() else: # Python 2 :( return py.tostring() cdef void bloom_from_bytes(Pool mem, BloomStruct* bloom, bytes data): py = array("L") if hasattr(py, "frombytes"): py.frombytes(data) else: py.fromstring(data) bloom.hcount = py[0] bloom.length = py[1] bloom.seed = py[2] bloom.bitfield = mem.alloc(bloom.length // sizeof(key_t), sizeof(key_t)) for i in range(bloom.length // sizeof(key_t)): bloom.bitfield[i] = py[3+i] cdef void bloom_init(Pool mem, BloomStruct* bloom, key_t hcount, key_t length, uint32_t seed) except *: # size should be a multiple of the container size - round up if length % sizeof(key_t): length = math.ceil(length / sizeof(key_t)) * sizeof(key_t) bloom.length = length bloom.hcount = hcount bloom.bitfield = mem.alloc(length // sizeof(key_t), sizeof(key_t)) bloom.seed = seed # Instead of calling MurmurHash with a different seed for each hash function, this # generates two initial hash values and then combines them to create the correct # number of hashes. This technique is faster than just doing MurmurhHash # repeatedly and has been shown to work as well as full hashing. # For details see "Less Hashing, Same Performance: Building a Better Bloom # Filter", Kirsch & Mitzenmacher. # https://www.semanticscholar.org/paper/Less-hashing%2C-same-performance%3A-Building-a-better-Kirsch-Mitzenmacher/65c43afbfc064705bdc40d3473f32518e9306429 # The choice of seeds is arbitrary. cdef void bloom_add(BloomStruct* bloom, key_t item) nogil: cdef key_t hv cdef key_t[2] keys cdef key_t one = 1 # We want this explicitly typed, because bits hash128_x86(&item, sizeof(key_t), 0, &keys) for hiter in range(bloom.hcount): hv = (keys[0] + (hiter * keys[1])) % bloom.length bloom.bitfield[hv // sizeof(key_t)] |= one << (hv % sizeof(key_t)) cdef bint bloom_contains(const BloomStruct* bloom, key_t item) nogil: cdef key_t hv cdef key_t[2] keys cdef key_t one = 1 # We want this explicitly typed, because bits hash128_x86(&item, sizeof(key_t), 0, &keys) for hiter in range(bloom.hcount): hv = (keys[0] + (hiter * keys[1])) % bloom.length if not (bloom.bitfield[hv // sizeof(key_t)] & one << (hv % sizeof(key_t))): return False return True def pickle_bloom(BloomFilter bloom): return unpickle_bloom, (bloom.to_bytes(),) def unpickle_bloom(byte_string): return BloomFilter().from_bytes(byte_string) copy_reg.pickle(BloomFilter, pickle_bloom, unpickle_bloom)