Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/michael-spengler/bloomfilter
Bloom Filters
https://github.com/michael-spengler/bloomfilter
bloom-filter
Last synced: 26 days ago
JSON representation
Bloom Filters
- Host: GitHub
- URL: https://github.com/michael-spengler/bloomfilter
- Owner: michael-spengler
- License: mit
- Created: 2021-11-05T22:29:55.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2024-01-07T12:02:36.000Z (10 months ago)
- Last Synced: 2024-05-23T00:15:36.272Z (6 months ago)
- Topics: bloom-filter
- Language: TypeScript
- Homepage:
- Size: 20.5 KB
- Stars: 7
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Bloom Filter
Bloom Filters are efficient probabilistic data structures which you can use to check whether entries are potentially already [in an array or not](https://www.youtube.com/watch?v=gBygn3cVP80).
## Usage Examples
### Default Hash Function
```sh
deno run https://deno.land/x/bloomfilter/usage-example.ts
```
```ts
import { BloomFilter } from "https://deno.land/x/bloomfilter/mod.ts"
const numberOfExpectedItemsInArray = 10000
const falsePositiveRate = 0.1 // 10 percent
const numberOfBitsInBitset = BloomFilter.getOptimalNumberOfBits(numberOfExpectedItemsInArray, falsePositiveRate)
const numberOfHashFunctions = BloomFilter.getOptimalNumberOfHashFunctions(numberOfBitsInBitset, numberOfExpectedItemsInArray)
const bloomFilter = new BloomFilter(numberOfBitsInBitset, numberOfHashFunctions)
const testArray = ["dog", "chicken", "cat"]
for (const entry of testArray) {
bloomFilter.add(entry)
}
let actualTestResult = bloomFilter.test("horse")
console.log(actualTestResult)
actualTestResult = bloomFilter.test("cat")
console.log(actualTestResult)
```
### Custom Hash Functions
```ts
import { BloomFilter } from "https://deno.land/x/bloomfilter/mod.ts"
const numberOfExpectedItemsInArray = 10000
const falsePositiveRate = 0.1 // 10 percent
const numberOfBitsInBitset = BloomFilter.getOptimalNumberOfBits(numberOfExpectedItemsInArray, falsePositiveRate)
const bloomFilter =
new BloomFilter(numberOfBitsInBitset, (x: number) => (x * 2) % 11, (x: number) => (x * 3) % 11, (x: number) => (x * 4) % 11)
const exampleArray = [2, 5, 6]
for (const entry of exampleArray) {
bloomFilter.add(entry)
}
let actualTestResult = bloomFilter.test(3)
console.log(actualTestResult)
actualTestResult = bloomFilter.test(34)
console.log(actualTestResult)
```
## Execute Unit Tests
```sh
deno test https://deno.land/x/bloomfilter/src/bloom-filter.spec.ts
```
---
For further examples you can check the [unit tests](https://github.com/michael-spengler/bloomfilter/blob/main/src/bloom-filter.spec.ts).
## Considering Optimization Options
See https://hur.st/bloomfilter/?n=100000&p=0.6&m=&k=
### Number of Hash Functions
Increasing the number of hash functions used for the Bloomfilter (Bitset) population increases the probability that a specific item from the array is in fact represented by a specific (set) of bit(s).
The downside is that with more hash functions the likelyhood that e.g. (almost) all Bits are set to 1 resulting in unnecessarily frequent "Perhaps" responses... increases.
## Donations
Thanks to [Freedom Cash](https://FreedomCash.org), we are already free.
If you want to donate, you might consider donating to the [otherparty.co.uk](https://www.otherparty.co.uk/donate-crypto-the-other-party) to ensure people do not need to donate to victims but rather donate successfully to problem solvers.
