sketches-js

!Continuous Integration 

This repo contains the TypeScript implementation of the distributed quantile sketch algorithm DDSketch. DDSketch is mergeable, meaning that multiple sketches from distributed systems can be combined in a central node.

---

This fork also contains a serialization/deserialization strategy for JSON which uses a compact tuple format

``ts
const sketch = new DDSketch({ relativeAccuracy: 0.01 });
sketch.accept(100);
sketch.accept(200);
sketch.accept(300);

// Serialize
const json = sketch.toJSON();
// Result: [1.02020202020202, 0, [202, [29,1], [63,1], [84,1]], [0], 0]

// Deserialize
const restored = DDSketch.fromJSON(json);
`

---

Installation

The package is under @datadog/sketches-js and can be installed through NPM or Yarn:

`sh


NPM

npm install @datadog/sketches-js

Yarn

yarn add @datadog/sketches-js
`

When using Protobuf serialization, the protobufjs module must also be installed manually:

`sh


NPM

npm install protobufjs

Yarn

yarn add protobufjs
`

Usage

$3

To initialize a sketch with the default parameters:

`js
import { DDSketch } from '@datadog/sketches-js'; // or const { DDSketch } = require('@datadog/sketches-js');
const sketch = new DDSketch();
`

#### Modify the relativeAccuracy

If you want more granular control over how accurate the sketch's results will be, you can pass a relativeAccuracy parameter when initializing a sketch.

Whereas other histograms use _rank error_ guarantees (i.e. retrieving the p99 of the histogram will give you a value between p98.9 and p99.1), DDSketch uses a _relative error_ guarantee (if the actual value at p99 is 100, the value will be between 99 and 101 for a relativeAccuracy of 0.01).

This property makes DDSketch especially useful for long-tailed distributions of data, like measurements of latency.

`js
import { DDSketch } from '@datadog/sketches-js';

const sketch = new DDSketch({
relativeAccuracy: 0.01 // relativeAccuracy must be between 0 and 1
});
`

$3

To add a number to a sketch, call sketch.accept(value). Both positive and negative numbers are supported.

`js
const measurementOne = 1607374726;
const measurementTwo = 0;
const measurementThree = -3.1415;

sketch.accept(measurementOne);
sketch.accept(measurementTwo);
sketch.accept(measurementThree);
`

$3

To retrieve measurements from a sketch, use sketch.getValueAtQuantile(quantile). Any number between 0 and 1 (inclusive) can be used as a quantile.

Additionally, common summary statistics are available such as sketch.min, sketch.max, sketch.sum, and sketch.count:

`js
const measurementOne = 1607374726;
const measurementTwo = 0;
const measurementThree = -3.1415;

sketch.accept(measurementOne);
sketch.accept(measurementTwo);
sketch.accept(measurementThree);

sketch.getValueAtQuantile(0); // -3.1415
sketch.getValueAtQuantile(0.5); // 0
sketch.getValueAtQuantile(0.99); // 1607374726
sketch.getValueAtQuantile(1); // 1607374726

sketch.min; // -3.1415
sketch.max; // 1607374726
sketch.count; // 3
sketch.sum; // 1607374722.86
`

$3

Independent sketches can be merged together, provided that they were initialized with the same relativeAccuracy. This allows collecting and transmitting measurements in a distributed manner, and merging their results together while preserving the relativeAccuracy guarantee.

`js
import { DDSketch } from '@datadog/sketches-js';

const sketch1 = new DDSketch();
const sketch2 = new DDSketch();

[1, 2, 3, 4, 5].forEach(value => sketch1.accept(value));
[6, 7, 8, 9, 10].forEach(value => sketch2.accept(value));

// sketch2 is merged into sketch1, without modifying sketch2
sketch1.merge(sketch2);

sketch1.getValueAtQuantile(1); // 10
``

References

- DDSketch: A Fast and Fully-Mergeable Quantile Sketch with Relative-Error Guarantees. Charles Masson, Jee E. Rim and Homin K. Lee. 2019.
- Java implementation: https://github.com/DataDog/sketches-java
- Go implementation: https://github.com/DataDog/sketches-go
- Python implementation: https://github.com/DataDog/sketches-py