--- title: "Hyperloglog and Cardinality Estimation" url: https://daily.dev/posts/hyperloglog-and-cardinality-estimation-3lahr4cwm source_url: https://www.youtube.com/watch?v=tOsb-tFoPCg type: video:youtube source: "Asli Engineering by Arpit Bhayani" published: 2026-06-27T02:46:19.293Z updated: 2026-06-27T02:46:41.158Z tags: ["backend", "redis"] reading_time: 13 upvotes: 0 comments: 0 language: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Hyperloglog and Cardinality Estimation **[Asli Engineering by Arpit Bhayani](https://daily.dev/sources/asli-engineering)** · 13 min read · 0 upvotes · 0 comments ## Summary HyperLogLog is a probabilistic data structure used to estimate the cardinality (number of unique elements) of large data streams with minimal memory. Instead of storing all unique elements in a set, it uses hash functions and tracks the position of the rightmost set bit in hashed values. The probability distribution of rightmost set bits follows a pattern where the first unset bit position approximates 2^B unique elements. Redis implements this via PF commands (PFADD, PFCOUNT, PFMERGE), storing the filter in raw byte encoding. The Flajolet-Martin algorithm underpins this approach, using multiple hash functions and median averaging to reduce error, requiring only O(log M) space for M unique elements. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [How YouTube Counts Millions of Live Viewers](https://daily.dev/posts/how-youtube-counts-millions-of-live-viewers-l3kj0h2bq) · Code Like A Girl · 2 upvotes · 1 comments --- Tags: [#backend](https://daily.dev/tags/backend), [#redis](https://daily.dev/tags/redis) [View this post on daily.dev](https://daily.dev/posts/hyperloglog-and-cardinality-estimation-3lahr4cwm)