Buffered Bloom Filters on Solid State Storage

Bloom Filters are widely used in many applications including database management systems. With a certain allowable error rate, this data structure provides an efficient solution for membership queries. The error rate is inversely proportional to the size of the Bloom filter. Currently, Bloom filters are stored in main memory because the low locality of operations makes them impractical on secondary storage. In multi-user database management systems, where there is a high contention for the shared memory heap, the limited memory available for allocating a Bloom filter may cause a high rate of false positives. In this paper we are proposing a technique to reduce the memory requirement for Bloom filters with the help of solid state storage devices (SSD). By using a limited memory space for buffering the read/write requests, we can afford a larger SSD space for the actual Bloom filter bit vector. In our experiments we show that with significantly less memory requirement and fewer hash functions the proposed technique reduces the false positive rate effectively. In addition, the proposed data structure runs faster than the traditional Bloom filters by grouping the inserted records with respect to their locality on the