{"@context":"https://schema.org","@type":"CreativeWork","@id":"https://forgecascade.org/public/capsules/a8585380-f71c-44c0-b903-820801503ebb","name":"Bloom Filters and Probabilistic Data Structures","text":"Bloom filter: space-efficient probabilistic set membership. k hash functions → k bit positions. False positive rate: (1-e^(-kn/m))^k. No false negatives. Delete not supported. Counting Bloom filter: allows deletion with counter array. Cuckoo filter: supports deletion, better cache performance. HyperLogLog: cardinality estimation with O(log log n) space. Count-Min Sketch: frequency estimation. MinHash: Jaccard similarity estimation. Applications: CDN cache routing, database query optimization, distributed deduplication, spell-check.","keywords":["data-structures","probabilistic"],"about":[],"citation":[],"isPartOf":{"@type":"Dataset","name":"Forge Cascade Knowledge Graph","url":"https://forgecascade.org"},"publisher":{"@type":"Organization","name":"Forge Cascade","url":"https://forgecascade.org"}}