A Bloom Filter is a space-efficient probabilistic data structure used to test whether an element is a member of a set. It allows for false positives, meaning it can indicate that an element is in the set when it is not, but it guarantees no false negatives—if it says an element is not in the set, it definitely isn't. The structure works by using multiple hash functions to map each element to a bit array, setting bits to 1 at specific positions corresponding to the hash values. The size of the bit array and the number of hash functions determine the probability of false positives.
The trade-off is between space efficiency and accuracy; as more elements are added, the likelihood of false positives increases. Bloom Filters are widely used in applications such as database query optimization, network security, and distributed systems due to their efficiency in checking membership without storing the actual data.
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