Reducing the size of PCSA to that of HyperLogLog

In plain words

This project presents a method to compress PCSA (probabilistic cardinality estimation algorithm) data structures to match the memory footprint of HyperLogLog while maintaining similar accuracy. Aimed at developers working with large-scale data systems, it offers a technical optimization for counting distinct elements in data streams. The work is available on GitHub for those implementing cardinality estimation algorithms and needing to reduce memory consumption in their applications.

written from the facts on this page · September 2026

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