Loglog counting of large cardinalities

By Marianne Durand, Philippe Flajolet. 2003

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HyperLogLog: the analysis of a near-optimal cardinality estimation algorithm (2007, methodology): “Introduction The purpose of this note is to present and analyse an efficient algorithm for estimating the number of distinct elements, known as the cardinality, of large data ensembles, which are referred to here as multisets and are usually massive streams (read-once sequences).”
HyperLogLog in practice: algorithmic engineering of a state of the art cardinality estimation algorithm (2013, background): “In [1], the authors compare six cardinality estimation algorithms including MinCount and LogLog [4] combined with LinearCounting [16] for small cardinalities.”
Continual Learning in Practice (2019, methodology): “HyperLogLog is an extension of the original LogLog algorithm [16].”
Approximate aggregation techniques for sensor databases (2004, methodology): “An alternative approach for reducing the space overhead is to replace FM sketches with the very recently developed “loglog” sketches of [5].”
Bitmap algorithms for counting active flows on high speed links (2003, background): “Durand and Flajolet have recently proposed [14] a variant of probabilistic counting with better asymptotic memory”