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#probabilistic-data-structure

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CosmosJan 21 · 9 min read

Cuckoo Filters vs. Bloom Filters: Let’s Take it Easy

Ok, before we go into the depths of these concepts, I want to tell you that we will take it easy. I don’t want you to get overwhelmed about the topics and the depth of the discussion. Bloom Filters A Bloom filter is a space-efficient probabilistic d...

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Sagyam ThapaJun 25, 2025 · 3 min read

An Interactive Guide To Count Min Sketch

Introduction Count min sketch is a probabilistic data structure that can estimate the frequency of items in a stream. It is an improvement over Hyperloglog. While hyperloglog can estimate the number of unique items in a fixed amount of data, count mi...

blog.sagyamthapa.com.np

Andrea IaconoFeb 2, 2024 · 8 min read

Introduction to HyperLogLog

Calculating the exact number of distinct items in a collection can be a difficult task if the collection is very large or if you have a very limited amount of memory. Typical approaches can be: using a hash map (uses more memory) using a bit map (u...

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Surabhi SumanDec 14, 2023 · 2 min read

Understanding Bloom Filter

It is a probabilistic space-efficient data structure with O(1) insertion and retrieval. It is used to find if a key exists (with false positives) or not (no false negatives). It can be used as a data layer to check if a key exists before querying the...

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satish MishraApr 9, 2023 · 4 min read

Implementing Bloom Filters in Python and Understanding its error probability: A Step-by-Step Guide

Before diving into the implementation of the bloom filters data structure, I highly recommend reading my article on the "What, Why, and How" of bloom filters. You can find the link to the article here. Main components required for Bloom filters imple...

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Ahmed ShamimJul 19, 2022 · 12 min read