# Bloom Filter

Probabilistic data structure used like a set that provides:

• No false negatives
• Low false positive rate

## What’s a bloom filter?

Simply put, a bit vector of N bits, and a set of K hash functions.

## Set operations

### Insertion

To insert a value X into a Bloom filter, simply hash it over each one of the K hash functions, and treating the hash outputs as indices into the bit-vector, raise the corresponding bits.

### Query

To query for a value X in the Bloom filter, once again hash it over each one o f the K hash functions, and then check whether all of the corresponding bits are raised.

# Source

https://gopiandcode.uk/logs/log-bloomfilters-debunked.html