Geospatial queries

Geospatial coordinates consisting of a latitude and longitude value can be stored either as two separate attributes, or as a single attribute in the form of an array with both numeric values. ArangoDB can index such coordinates for fast geospatial queries.

Locations data

Let us insert some filming locations into a new collection Locations, which you need to create first, then run below AQL query:

LET places = [
    { "name": "Dragonstone", "coordinate": [ 55.167801, -6.815096 ] },
    { "name": "King's Landing", "coordinate": [ 42.639752, 18.110189 ] },
    { "name": "The Red Keep", "coordinate": [ 35.896447, 14.446442 ] },
    { "name": "Yunkai", "coordinate": [ 31.046642, -7.129532 ] },
    { "name": "Astapor", "coordinate": [ 31.50974, -9.774249 ] },
    { "name": "Winterfell", "coordinate": [ 54.368321, -5.581312 ] },
    { "name": "Vaes Dothrak", "coordinate": [ 54.16776, -6.096125 ] },
    { "name": "Beyond the wall", "coordinate": [ 64.265473, -21.094093 ] }
]

FOR place IN places
    INSERT place INTO Locations

Visualization of the coordinates on a map with their labels:

Geospatial index

To query based on coordinates, a geo index is required. It determines which fields contain the latitude and longitude values.

• Go to COLLECTIONS
• Click on the Locations collection
• Switch to the Indexes tab at top
• Click the green button with a plus on the right-hand side
• Change the type to Geo Index
• Enter coordinate into the Fields field
• Click Create to confirm

Find nearby locations

A FOR loop is used again, with a subsequent SORT operation based on the DISTANCE() between a stored coordinate and a coordinate given in a query. This pattern is recognized by the query optimizer. A geo index will be used to accelerate such queries if one is available.

The default sorting direction is ascending, so a query finds the coordinates closest to the reference point first (lowest distance). LIMIT can be used to restrict the number of results to at most n matches.

In below example, the limit is set to 3. The origin (the reference point) is a coordinate somewhere downtown in Dublin, Ireland:

FOR loc IN Locations
  LET distance = DISTANCE(loc.coordinate[0], loc.coordinate[1], 53.35, -6.25)
  SORT distance
  LIMIT 3
  RETURN {
    name: loc.name,
    latitude: loc.coordinate[0],
    longitude: loc.coordinate[1],
    distance
  }

[
  {
    "name": "Vaes Dothrak",
    "latitude": 54.16776,
    "longitude": -6.096125,
    "distance": 91491.58596795711
  },
  {
    "name": "Winterfell",
    "latitude": 54.368321,
    "longitude": -5.581312,
    "distance": 121425.66829502625
  },
  {
    "name": "Dragonstone",
    "latitude": 55.167801,
    "longitude": -6.815096,
    "distance": 205433.7784182078
  }
]

The query returns the location name, as well as the coordinate and the calculated distance in meters. The coordinate is returned as two separate attributes. You may return just the document with a simple RETURN loc instead if you want. Or return the whole document with an added distance attribute using RETURN MERGE(loc, { distance }).

Find locations within radius

LIMIT can be swapped out with a FILTER that checks the distance, to find locations within a given radius from a reference point. Remember that the unit is meters. The example uses a radius of 200,000 meters (200 kilometers):

FOR loc IN Locations
  LET distance = DISTANCE(loc.coordinate[0], loc.coordinate[1], 53.35, -6.25)
  SORT distance
  FILTER distance < 200 * 1000
  RETURN {
    name: loc.name,
    latitude: loc.coordinate[0],
    longitude: loc.coordinate[1],
    distance: ROUND(distance / 1000)
  }

[
  {
    "name": "Vaes Dothrak",
    "latitude": 54.16776,
    "longitude": -6.096125,
    "distance": 91
  },
  {
    "name": "Winterfell",
    "latitude": 54.368321,
    "longitude": -5.581312,
    "distance": 121
  }
]

The distances are converted to kilometers and rounded for readability.