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Published in:
2006 | OriginalPaper | Chapter
Less Hashing, Same Performance: Building a Better Bloom Filter
Authors : Adam Kirsch, Michael Mitzenmacher
Published in: Algorithms – ESA 2006
Publisher: Springer Berlin Heidelberg
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A standard technique from the hashing literature is to use two hash functions
h
1
(
x
) and
h
2
(
x
) to simulate additional hash functions of the form
g
i
(
x
) =
h
1
(
x
) +
ih
2
(
x
). We demonstrate that this technique can be usefully applied to Bloom filters and related data structures. Specifically, only two hash functions are necessary to effectively implement a Bloom filter without any loss in the asymptotic false positive probability. This leads to less computation and potentially less need for randomness in practice.