construct a Bloom filter optimized for nentries
no copying
clear all bits
insert a key
free all bits
resize to nentries, all bits are cleared
get the reserved number of entries
test membership of key
Set the number of bits allocated per entry (default 4).
Use a faster but less good hash function.
Default BloomFilter for 16 entries.
auto filter = BloomFilter!()(16); filter.insert(1); assert(filter.test(1)); assert(!filter.test(2)); filter.insert(2); assert(filter.test(2));
Using 6 bits per entry.
auto filter = BloomFilter!6(16);
Using a better but slower hash function.
auto filter = BloomFilter!(4, CheapHash.no)(16);
A bloom filter is a fast and space-efficient probabilistic data structure to test whether an element is member of a set. False positive matches are possible, false negative matches are not. Elements can only be added not removed.
Asymptotic false-positive rates for different BitsPerEntry settings.