Bloom Filters Imagine ensuring web safety by identifying ma | Programming Tips 💡

Bloom Filters

Imagine ensuring web safety by identifying malicious links without storing massive data. Traditional methods involve keeping a huge list of bad links, consuming substantial storage and bandwidth. Enter Bloom Filters - a genius method allowing us to significantly reduce storage needs (up to 82% smaller) with a minimal error rate.

For instance, instead of a 20MB list for 1,000,000 links, a Bloom Filter achieves this with just 3.59MB, accepting a tiny error chance (0.0001%). Even more impressive, with a 0.1% error tolerance, the size shrinks to 1.8MB. This technique was even utilized by Google Chrome until 2012.

Bloom Filters offer a balance between efficiency and accuracy. For critical checks, it pairs with a database API for zero false positives. A practical, space-saving solution for modern web browsers!


[ Article ] : https://samwho.dev/bloom-filters


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