Implements the Hyper Log Log approximate count-distinct algorithm.
-
Updated
Aug 19, 2019 - C#
Implements the Hyper Log Log approximate count-distinct algorithm.
A SIMD optimized implementation of the HLL and HLL++ algorithms in Rust
Small command line utility taking advantage of HyperLogLog to count distinct lines.
A simple, time-tested, family of random hash functions in Java, based on CRC32, affine transformations, and the Mersenne Twister. 🎲
Implementation and experimental tests of various algorithms.
A streaming data pipeline to perform basic analytics with scalability in mind
A simple, time-tested, family of random hash functions in Python, based on CRC32 and xxHash, affine transformations, and the Mersenne Twister. 🎲
A crate for estimating the cardinality of distinct elements in a stream or dataset.
Hyper Log Log analytical data processor for LieYing
Count unique line on big file
Approximate Privacy-Preserving Neighbourhood Estimations
A header-only bit vector library for C . This can be used for implementing dynamic bit-vectors for building Bloom-Filters and Hyper-Logs .
Implementation of HyperLogLog algorithms for distinct count estimate
Thread-safe and persistent Golang implementations of probabilistic data structures: Bloom Filter, Cuckoo Filter, HyperLogLog, Count-Min Sketch and Top-K
go/golang version of hyperloglog, ported from popular java version java-hll. hyperloglog is an Cardinality estimate algorithm with low memory and low bias
Add a description, image, and links to the hyperloglog topic page so that developers can more easily learn about it.
To associate your repository with the hyperloglog topic, visit your repo's landing page and select "manage topics."