Bloom Filter
Version 1.0.0 · Updated 2026-07-28
CORE DEFINITION
A Bloom filter is a space-efficient probabilistic data structure conceived by Burton Howard Bloom in 1970, consisting of a bit array mapped by a series of hash functions. It is used to test whether an element is a member of a set, offering far greater space and time efficiency than general algorithms. It produces no false negatives, but has a certain probability of false positives and is difficult to delete elements.
SCAFFOLDING EFFECT
Reduce cognitive load
A Bloom filter is a space-efficient probabilistic data structure conceived by Burton Howard Bloom in 1970, consisting of a bit array mapped by a series of hash functions. It is used to test whether an element is a member of a set, offering far greater space and time efficiency than general algorithms. It produces no false negatives, but has a certain probability of false positives and is difficult to delete elements.
Anchor fast decisions
A Bloom filter is a space-efficient probabilistic data structure that uses multiple hash functions to map elements to a bit array; it can quickly determine whether an element is 'definitely not in the set' or 'possibly in the set', allowing false positives but not false negatives.
MINIMUM ACTION
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Source support: Explicit
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