HyperLogLog
A probabilistic algorithm for cardinality estimation (distinct-value counting) that exploits the relationship between the maximum number of leading zeros in hash values and the logarithm of set cardinality. It estimates the count of billions of unique elements using only a few kilobytes of memory and is natively implemented in databases such as Redis.
Timeline (last 90 days)
HyperLogLog is used for cardinality estimation and can estimate the number of unique elements in the billions using only a few KB of memory.
HyperLogLog is based on the statistical insight that there is a logarithmic relationship between the maximum length of leading zeros after uniform hashing and the cardinality of a set.
Mainstream databases such as Redis have built HyperLogLog in as a native data type.
All Facts (3)
HyperLogLog is used for cardinality estimation and can estimate the number of unique elements in the billions using only a few KB of memory.
50%UnverifiedHyperLogLog is based on the statistical insight that there is a logarithmic relationship between the maximum length of leading zeros after uniform hashing and the cardinality of a set.
50%UnverifiedMainstream databases such as Redis have built HyperLogLog in as a native data type.
50%