hyperlog-kdb-index

n-dimensional kdb tree spatial index for hyperlogs

example

var fdstore = require('fd-chunk-store')
var hyperkdb = require('hyperlog-kdb-index')
var level = require('level')

var hyperlog = require('hyperlog')
var log = hyperlog(level('/tmp/kdb-log/log'), { valueEncoding: 'json' })

var kdb = hyperkdb({
  log: log,
  db: level('/tmp/kdb-log/index'),
  types: [ 'float', 'float' ],
  kdbtree: require('kdb-tree-store'),
  store: fdstore(1024, '/tmp/kdb-log/tree'),
  map: function (row, next) {
    if (row.value.type === 'point') {
      next(null, [ row.value.lat, row.value.lon ])
    } else next()
  }
})

if (process.argv[2] === 'add') {
  log.add(null, {
    type: 'point',
    lat: Number(process.argv[3]),
    lon: Number(process.argv[4])
  })
} else if (process.argv[2] === 'query') {
  var q = process.argv.slice(3).map(commaSplit)
  kdb.query(q, function (err, pts) {
    if (err) return console.error(err)
    pts.forEach(function (pt) {
      console.log(pt.point)
    })
  })
}

function commaSplit (s) { return s.split(',').map(Number) }

$ mkdir /tmp/kdb-log
$ node log.js add 64.7 -147.9
$ node log.js add 66.2 -147.5
$ node log.js add 61.6 -148.3
$ node log.js query 60,65 -149,-146
[ 64.69999694824219, -147.89999389648438 ]
[ 61.599998474121094, -148.3000030517578 ]

api

var hyperkdb = require('hyperlog-kdb-index')

var kdb = hyperkdb(opts)

Create a kdb-tree spatial index for a hyperlog. These options are required:

• opts.log - a hyperlog where data is written
• opts.db - leveldb instance to store index data
• opts.types - array of kdb-tree-store types
• opts.kdbtree - kdb-tree-store interface (require('kdb-tree-store'))
• opts.store - abstract-chunk-store for the kdb tree data
• opts.map(row, next) - asynchornous function mapping hyperlog rows to points

In the opts.map(row, next), if there are no points to map in a given row, call next() with a falsy value. Otherwise call next(err, rec) with a record:

• rec.type - 'put' or 'del'
• rec.point - array of coordinates

If rec is an array, it will be interpreted as a point in a 'put'.

kdb.query(q, opts={}, cb)

Query for all points in the region described by q. This method is passed through to the underlying kdb-tree-store query method.

var r = kdb.queryStream(q, opts={})

Return a readable stream r with the region described by q. This method is passed through to the underlying kdb-tree-store query method.

kdb.ready(fn)

When the index has caught up with the latest known entry in the hyperlog, fn() fires.

log.add(links, doc, cb)

When you write to the hyperlog, the links should refer to the ancestors of the current doc which will be replaced with the new value.

When you create a new point, links should be any empty array [].

When you update an existing point, links should contain a list of immediate ancestors that the update will replace. Usually this will be a single key, but for merge cases, this can be several keys.

install

npm install hyperlog-kdb-index

license

BSD