UltraLogLog: A Practical and More Space-Efficient Alternative to HyperLogLog for Approximate Distinct Counting

TL;DR

UltraLogLog is a new approximate distinct counting algorithm that improves space efficiency over HyperLogLog while maintaining practical properties, with proven theoretical and experimental validation, and available as open-source software.

Contribution

It introduces UltraLogLog, a space-efficient variant of HyperLogLog, with novel estimators and implementation optimizations for practical use.

Findings

Requires 28% less space than HyperLogLog for same accuracy

Achieves 24% space reduction with a faster estimator

Experimental results confirm theoretical space savings and efficiency

Abstract

Since its invention HyperLogLog has become the standard algorithm for approximate distinct counting. Due to its space efficiency and suitability for distributed systems, it is widely used and also implemented in numerous databases. This work presents UltraLogLog, which shares the same practical properties as HyperLogLog. It is commutative, idempotent, mergeable, and has a fast guaranteed constant-time insert operation. At the same time, it requires 28% less space to encode the same amount of distinct count information, which can be extracted using the maximum likelihood method. Alternatively, a simpler and faster estimator is proposed, which still achieves a space reduction of 24%, but at an estimation speed comparable to that of HyperLogLog. In a non-distributed setting where martingale estimation can be used, UltraLogLog is able to reduce space by 17%. Moreover, its smaller entropy and its 8-bit registers lead to better compaction when using standard compression algorithms. All this is verified by experimental results that are in perfect agreement with the theoretical analysis which also outlines potential for even more space-efficient data structures. A production-ready Java implementation of UltraLogLog has been released as part of the open-source Hash4j library.