geokdbush-tk

geokdbush

A geographic extension for kdbush, the fastest static spatial index for points in JavaScript.

It implements fast nearest neighbors queries for locations on Earth, taking Earth curvature and date line wrapping into account. Inspired by sphere-knn, but uses a different algorithm.

This fork works with kdbush 4.x, which doesn't store the whole objects, but only ids, so you have to keep the id-to-object lookup by yourself, and the .around method returns just ids.

Example

import KDBush from 'kdbush'
import * as geokdbush from 'geokdbush'

// create a point array
const points = [
	{ lat: 12.345, lon: 123.456 } // , ...
]

// create kdbush index of given length
let index = new KDBush(points.length)

// add locations
for (const point of points) {
	index.add(point.lon, point.lat)
}

// perform the indexing
index.finish()

// look up ids ...
const nearestIds = geokdbush.around(index, -119.7051, 34.4363, 1000)

// ... and optionally convert to points
const nearestPoints = nearestIds.map((id) => points[id])

API

geokdbush.around(index, longitude, latitude[, maxResults, maxDistance, filterFn])

Returns an array of the closest ids (indices) of points from a given location in order of increasing distance.

• index: kdbush index.
• longitude: query point longitude.
• latitude: query point latitude.
• maxResults: (optional) maximum number of points to return (Infinity by default).
• maxDistance: (optional) maximum distance in kilometers to search within (Infinity by default).
• filterFn: (optional) a function to filter the results (ids) with.

geokdbush.distance(longitude1, latitude1, longitude2, latitude2)

Returns great circle distance between two locations in kilometers.

Performance

This library is incredibly fast. The results below were obtained with npm run bench (Node v7.7.2, Macbook Pro 15 mid-2012).

benchmark	geokdbush	sphere-knn	naive
index 138398 points	69ms	967ms	n/a
query 1000 closest	4ms	4ms	155ms
query 50000 closest	31ms	368ms	155ms
query all 138398	80ms	29.7s	155ms
1000 queries of 1	55ms	165ms	18.4s