# count-min-sketch-ts

> Count-Min-Sketch Data Structure in TS

Latest version **2.0.1** (published 2022-12-11) · MIT license · 0 weekly downloads

## Install

```sh
npm install count-min-sketch-ts
pnpm add count-min-sketch-ts
yarn add count-min-sketch-ts
bun add count-min-sketch-ts
```

## Health

**Score 15/100 (F)** — status: abandoned.

Positive: no vulnerabilities.

Warnings: low downloads; no types; no esm support.

Negative: abandoned; low maintenance score.

## Facts

| | |
|---|---|
| Version | 2.0.1 |
| Published | 2022-12-11 |
| First published | 2022-11-07 |
| Weekly downloads | 0 |
| License | MIT |
| TypeScript types | none |
| Module format | CommonJS |
| Node | >=16.17.1 |
| Dependencies | 0 |
| Unpacked size | 21.9 KB |
| Known vulnerabilities | 0 |
| Install scripts | no |
| GitHub stars | 0 |
| Author | a5node |
| Maintainers | a5node |
| Keywords | count-min-sketch, typescript |

## Links

- npm: https://www.npmjs.com/package/count-min-sketch-ts
- Repository: https://github.com/a5node/count-min-sketch-ts
- Homepage: https://github.com/a5node/count-min-sketch-ts#readme
- Issues: https://github.com/a5node/count-min-sketch-ts/issues
- npm.io page: https://npm.io/package/count-min-sketch-ts

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## Recent versions

- 2.0.1 (latest) — 2022-12-11
- 2.0.0 — 2022-12-11
- 1.0.1 — 2022-11-07
- 1.0.0 — 2022-11-07

## README

count-min-sketch-ts
================
Depends on Jest, required Node 18+

The TypeScript implementation of Coromode and Muthukrishnan's [Count-Min sketch](http://en.wikipedia.org/wiki/Count-Min_sketch) data structure for JavaScript.  The count-min sketch is basically a high powered generalization of the bloom filter.  While a bloom filter gives an efficient way to approximate membership of a set, a count-min sketch can give approximate data about the relative frequency of items in the set.

For more information see the following references:

* Count-Min sketch:  https://sites.google.com/site/countminsketch/
* next big thing syndrome: http://lkozma.net/blog/sketching-data-structures/
* G. Cormode, S. Muthukrishnan. ["Approximating Data with the Count-Min Data Structure"](http://dimacs.rutgers.edu/~graham/pubs/papers/cmsoft.pdf).  IEEE Trans. on Software (2012)

## Example

```typescript
//Import data structures
import { createCountMin, createCountMinSketch } from 'count-min-sketch-ts'

//Import hash functions
import { JSHash, SDBMHash, DJBHash, DEKHash, APHash, wrapperHashFunction } from 'count-min-sketch-ts'

//Create data structure, with default 28 width, 10 depth and single hash ('k-hash') function used
let sketch = createCountMin()

//Create customizable implementation with user-defined width, depth and set of hash functions (each raw in table calculated with different hash function)
let sketch = createCountMinSketch(10, 6, wrapperHashFunction([APHash, JSHash, SDBMHash, DJBHash, DEKHash]))

//Increment counters
sketch.update("foo")
sketch.update(1515)
sketch.update(1515)

let obj= {test: "test", key: 123}
sketch.update(obj)

//Query results
console.log(sketch.query(1515))  //Prints 2
console.log(sketch.query(obj))   //Prints 1
console.log(sketch.query("bar")) //Prints 0
```

## Install

    npm install count-min-sketch-ts

## Test (Jest)

    npm test
    
## API

`module.exports` is a constructor for the data structure, and you import it like so:

```typescript

import { createCountMin, createCountMinSketch } from 'count-min-sketch-ts'

let sketch = createCountMin()
```

### `let sketch = createCountMin(epsilon, probError[, hashFunc])`
Creates a count-min sketch data structure.

* `epsilon` is the accuracy of the data structure (ie the size of bins that we are computing frequencies of)
* `probError` is the probability of incorrectly computing a value
* `hashFunc(key, hashes)` is a hash function for the data structure. (optional)  the parameters to this function are as follows:

    + `key` is the item that is being hashed
    + `hashes` is an array of `k` hashes which are required to be pairwise independent.

**Returns** A count-min sketch data structure

### `sketch.update(key)`
Increments `key` frequency by 1

* `key` is the item in the table to increment.


### `sketch.query(key)`
Returns the frequency of the item `key`

* `key` is the item whose frequency we are counting

**Returns** An estimate of the frequency of `key`

### `sketch.toJSON()`
Returns a serializable JSON representation of the table.

### `sketch.fromJSON(obj)`
Converts a JSON object into a deserialized sketch.  The hash function is reused from the current sketch.  

**Note** In order for this to be successful both the serialized hash table and the current hash table have to have the same hash functions set.

## Credits
(c) 2022 a5node node@a5.ua . MIT License

---
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