Bloom Filters: Efficient Data Filtering With Practical Applications
DZone
OCTOBER 9, 2023
Bloom filters are probabilistic data structures that allow for efficient testing of an element's membership in a set. They effectively filter out unwanted items from extensive data sets while maintaining a small probability of false positives. Since their invention in 1970 by Burton H. Bloom, these data structures have found applications in various fields such as databases, caching, networking, and more.
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