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Hyper-efficient Cardinality Estimation: Redis HyperLogLog in Production with wredis
Hyper-efficient Cardinality Estimation: Redis HyperLogLog in Production with wredis
Counting unique elements across millions of daily active users, IP addresses, or IoT telemetry events in a traditional relational database or standard Redis Set quickly consumes gigabytes of memory.
A Redis Set storing 100 million UUIDs requires several gigabytes of RAM. In contrast, Redis HyperLogLog (HLL) uses a probabilistic counting algorithm that bounds memory consumption to a constant ~12 KB per...
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