ExaLogLog: Space-Efficient and Practical Approximate Distinct Counting up to the Exa-Scale
Data Structures and Algorithms
2025-02-28 v2 Databases
Abstract
This work introduces ExaLogLog, a new data structure for approximate distinct counting, which has the same practical properties as the popular HyperLogLog algorithm. It is commutative, idempotent, mergeable, reducible, has a constant-time insert operation, and supports distinct counts up to the exa-scale. At the same time, as theoretically derived and experimentally verified, it requires 43% less space to achieve the same estimation error.
Keywords
Cite
@article{arxiv.2402.13726,
title = {ExaLogLog: Space-Efficient and Practical Approximate Distinct Counting up to the Exa-Scale},
author = {Otmar Ertl},
journal= {arXiv preprint arXiv:2402.13726},
year = {2025}
}
Comments
14 pages, accepted at EDBT 2025