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Implementations of the HyperLogLog algorithm for cardinality estimation.

HyperLogLog is an probabilistic algorithm for estimating the number of distinct elements (cardinality) of a multiset. The original algorithm, described by P. Flajolet et al. in HyperLogLog: the analysis of a near-optimal cardinality estimation algorithm, can estimate cardinalities well beyond 109 with a typical accuracy of 2% while using memory of 1.5 kilobytes. HyperLogLog variants can improve on those results.

All HyperLogLog variants should implement the HyperLogLog trait.

Current implementations:


Implements the original HyperLogLog algorithm for cardinality estimation.

Implements the HyperLogLog++ algorithm for cardinality estimation.



A trait that should be implemented by any HyperLogLog variant.