Probabilistic data structures for processing continuous, unbounded streams.
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Updated
Mar 15, 2021 - Go
Probabilistic data structures for processing continuous, unbounded streams.
Cuckoo Filter implementation in Go, better than Bloom Filters (unmaintained)
Cuckoo Filter go implement, better than Bloom Filter, configurable and space optimized 布谷鸟过滤器的Go实现,优于布隆过滤器,可以定制化过滤器参数,并进行了空间优化
高性能的分布式的专门空间优化的 Bitmap 服务, 高效检查数据是否存在,日活统计,签到,打点等等
Cuckoo Filter: Practically better than bloom filter
Optimized implementation of Cuckoo Filter: Practically Better Than Bloom.
An implementation of Cuckoo Filters in Go
A service to manage your Cuckoo filters
Implementing a Cuckoo filter, based on the paper Cuckoo Filter: Practically Better Than Bloom
A fast, vectorized Cuckoo filter implementation in Go. Zero allocations in hot paths with zero-copy binary representation.
Cuckoo Filter: Practically Better Than Bloom
Cuckoo Filter in golang for set membership approximation
Thread-safe and persistent Golang implementations of probabilistic data structures: Bloom Filter, Cuckoo Filter, HyperLogLog, Count-Min Sketch and Top-K
Expandable Cuckoo hash map/set implementation in Go (Docs WIP)
https://github.com/linvon/cuckoo-filter wrap, support redis persistence
A Golang multi-level caching framework based on Redis and local memory for distributed scenarios.
A set of probabilistic data structures
Cuckoo Filter: Practically Better Than Bloom
a redis bloomfilter and cuckoo filter service with basic reserve,exists, delete and insert functionality. The cuckoo filter will also have the delete-item functionality as well.
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