unordered-materialized-bkd

materialized view spatial tree based on unordered log messages

This library finds points written to an append-only-log inside of a bounding box search region. These points can update previous documents by linking to them and the documents can be inserted into the log in any order. Every point that is not linked to by any other point will be included in query results, including multiple forks of the same underlying resource such as the values for a key. This is sometimes known as a multi-register conflict strategy. Likewise, multiple forks can be merged into a single value by linking to the forks.

This library is useful for kappa architectures with missing or out of order log entries, or where calculating a topological ordering would be expensive.

This library does not store the primary records yourself to save space. You'll need to pass in a function to perform lookups. You'll also need to pass in another method to look up if a document has been linked to so that you can avoid duplicating the work of other libraries such as unordered-materialized-kv.

example

This library stores a bkd tree in memory and prints all the "heads" (documents that aren't linked to). In this case, there is one head: the document with id 3.

var memdb = require('memdb')
var ram = require('random-access-memory')
var concatMap = require('concat-map')
var umbkd = require('unordered-materialized-bkd')

var db = memdb({ valueEncoding: 'json' })
var bkd = umbkd({
  storage: function (name, cb) { cb(null, ram()) },
  isLinked: function (id, cb) {
    db.get('link!' + id, function (err, value) {
      cb(null, value !== undefined)
    })
  },
  getPoint: function (key, cb) {
    db.get('doc!' + key, function (err, doc) {
      if (err) cb(err)
      else cb(null, { point: doc.point, value: [doc.id] })
    })
  },
  type: {
    point: [ 'float64be', 'float64be' ],
    value: [ 'uint32be' ]
  },
  compare: function (a, b) {
    return a.value[0] === b.value[0]
  }
})

var docs = [
  { id: 0, links: [], point: [13.37,66.67] },
  { id: 1, links: [0], point: [-155.0,19.6] },
  { id: 2, links: [1], point: [-155.0,19.5] },
  { id: 3, links: [2], point: [-155.0,19.5] }
]

var dbBatch = concatMap(docs, function (doc) {
  return [
    {
      type: 'put',
      key: 'doc!' + doc.id,
      value: { id: doc.id, point: doc.point }
    }
  ].concat(doc.links.map(function (link) {
    return {
      type: 'put',
      key: 'link!' + link,
      value: ''
    }
  }))
})

db.batch(dbBatch, function (err) {
  if (err) return console.error(err)
  bkd.batch(docs, function (err) {
    if (err) return console.error(err)
    bkd.query([-180,-90,+180,+90], function (err, results) {
      if (err) return console.error(err)
      results.forEach(function (result) {
        console.log(result)
      })
    })
  })
})

output:

{ point: [ -155, 19.5 ], value: [ 3 ] }

If you use this module with unordered-materialized-kv, you can use the isLinked implementation from that module:

var memdb = require('memdb')
var ram = require('random-access-memory')
var umkv = require('unordered-materialized-kv')
var umbkd = require('unordered-materialized-bkd')

var db = memdb({ valueEncoding: 'json' })
var kv = umkv(memdb())

var bkd = umbkd({
  storage: function (name, cb) { cb(null, ram()) },
  isLinked: function (id, cb) { kv.isLinked(id, cb) },
  getPoint: function (key, cb) {
    db.get(key, function (err, doc) {
      if (err) cb(err)
      else cb(null, { point: doc.point, value: [doc.id] })
    })
  },
  type: {
    point: [ 'float64be', 'float64be' ],
    value: [ 'uint32be' ]
  },
  compare: function (a, b) {
    return a.value[0] === b.value[0]
  }
})

var docs = [
  { key: 'x', id: 0, links: [], point: [13.37,66.67] },
  { key: 'x', id: 1, links: [0], point: [-155.0,19.6] },
  { key: 'x', id: 2, links: [1], point: [-155.0,19.5] },
  { key: 'x', id: 3, links: [2], point: [-155.0,19.5] }
]

var dbBatch = docs.map(function (doc) {
  return {
    type: 'put',
    key: doc.id,
    value: { id: doc.id, point: doc.point }
  }
})
var kvBatch = docs.map(function (doc) {
  return {
    key: doc.key,
    id: doc.id,
    links: doc.links
  }
})

db.batch(dbBatch, function (err) {
  if (err) return console.error(err)
  kv.batch(kvBatch, function (err) {
    if (err) return console.error(err)
    bkd.batch(docs, function (err) {
      if (err) return console.error(err)
      query()
    })
  })
})

function query () {
  bkd.query([-180,-90,+180,+90], function (err, results) {
    if (err) return console.error(err)
    results.forEach(function (result) {
      console.log(result)
    })
  })
}

api

var umbkd = require('unordered-materialized-bkd')

var bkd = umbkd(opts)

Create a new bkd instance from:

opts.storage - random-access storage instance
opts.getPoint(id, cb) - provide the primary document for id as cb(err, doc). The doc should have doc.point and doc.value.
opts.isLinked(id, cb) - provide whether the document id is linked to by any other documents as cb(err, exists) for a boolean exists.

in addition to these options which are forwarded along to bkd-tree:

opts.type.point - array of types for the coordinates
opts.type.value - array of types for the data payload
opts.branchFactor - branch factor. default: 4
opts.levels - number of levels in the smallest tree. default: 5
opts.compare(a,b) - boolean comparison function required for deletes

bkd.batch(rows, cb)

Write an array of rows into the bkd. Each row in the rows array has:

row.id - unique identifier for each document
row.point - spatial coordinate array
row.links - array of document ids that this document supercedes

var stream = bkd.query(bbox)

bkd.query(bbox, cb)

Search for records inside the bounding box bbox either by read a pull-stream stream or as an array of results in cb(err, results).

The bbox should contain all the minimum values for each dimension followed by all the maximum values for each dimension. In 2d, the bbox is [minX,minY,maxX,maxY], or the more familiar [west,south,east,north].

install

npm install unordered-materialized-bkd

license

BSD

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