
HyperLogLog estimates the cardinality of massive, unbounded data streams using a microscopic memory footprint. It relies on stochastic averaging, observing the maximum number of leading zeros in the hashed representations of the elements to calculate the scale of the crowd. By tracking only the rarest geometric patterns, a few kilobytes can count billions of unique events. The leading zero estimates the infinite.