A Go implementation of Cuckoo Filter, a space-optimized probabilistic data structure supporting dynamic additions and deletions.
Cuckoo Filter is a Go implementation of the Cuckoo Filter probabilistic data structure, designed for approximate set-membership queries. It solves the limitation of Bloom filters by supporting dynamic item addition and deletion while maintaining space efficiency, making it ideal for applications requiring low false positive rates. The implementation allows customization of parameters like bucket size and fingerprint size to optimize performance and storage.
Developers and engineers working on systems that require efficient set-membership testing with dynamic data, such as databases, networking tools, or caching mechanisms where Bloom filters are insufficient due to their lack of deletion support.
Developers choose this implementation for its configurability and space optimization, offering better flexibility and efficiency than standard Bloom filters, especially when deletions are needed or when targeting specific false positive rates.
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
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Supports adding and removing items dynamically, unlike standard Bloom filters, as emphasized in the overview for applications needing deletion capabilities.
Allows customization of bucket size and fingerprint size to optimize for specific false positive rates and space usage, with flexible implementations like TableTypeSingle for arbitrary adjustments.
Implements semi-sorting buckets in TableTypePacked to save approximately 1 bit per item, enhancing compactness as detailed in the implementation notes.
Achieves load factors up to 98% with appropriate bucket sizes, maximizing storage efficiency for dense datasets, as discussed in parameter choosing guidelines.
Choosing optimal bucket and fingerprint sizes requires referencing academic papers and understanding trade-offs, which can be error-prone and time-consuming for developers.
Limited to Go projects, making it unsuitable for cross-platform or polyglot environments without additional integration efforts.
The README provides basic examples but lacks detailed benchmarks, performance comparisons, or troubleshooting guides, relying on external resources for in-depth use.