HyperLogLog

A TypeScript implementation of the HyperLogLog algorithm for cardinality estimation.

Installation

``bash
npm install @hazemaltakriti/hyperloglog
`

Usage

`typescript
import { HyperLogLog } from '@hazemaltakriti/hyperloglog';

// Create a new HyperLogLog instance with default precision (14)
const hll = new HyperLogLog();

// Add elements
hll.add('item1');
hll.add('item2');
hll.add('item3');

// Get the estimated cardinality
const count = hll.count();
console.log(Estimated unique elements: ${count});
`

API

$3

`typescript
new HyperLogLog(precision?: number)
`

- precision: Optional. Number between 4 and 16. Default is 14. Higher precision means better accuracy but more memory usage.

$3

#### add(element: string | number): void
Adds an element to the HyperLogLog counter.

#### count(): number
Returns the estimated cardinality (number of unique elements).

Development

`bash


Install dependencies

npm install

Run tests

npm test

Build the project

npm run build
``

Authors

- Hazem Altakriti - Senior Backend Developer
- LinkedIn
- Medium

Acknowledgments

This implementation is based on the seminal paper:
- Flajolet, P., Fusy, É., Gandouet, O., & Meunier, F. (2007). HyperLogLog: the analysis of a near-optimal cardinality estimation algorithm. In Proceedings of the 2007 International Conference on Analysis of Algorithms.