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Geospatial and GeoJSON location data in Azure Cosmos DB for NoSQL

  • บทความ

APPLIES TO: NoSQL

Azure Cosmos DB for NoSQL has built-in geospatial functionality to represent geometric shapes or actual locations/polygons on a map.

Geospatial data often involves proximity queries. For example, the question "find all retail locations near my current location" is answered using a proximity query over multiple geospatial data object.

Common geospatial use cases include, but aren't limited to:

  • Geolocation analytics, driving specific location-based marketing initiatives.
  • Location-based personalization, for industries like retail and healthcare to improve user experience.
  • Logistics enhancement, for industries like transportation where optimization is critical.
  • Risk Analysis, for industries like insurance and finance to supplement other metadata.
  • Situational awareness*, for proximity-based alerts and notifications.

Introduction to spatial data

Spatial data describes the position and shape of objects in space. In most applications, these points and shapes correspond to objects on the earth and geospatial data. Spatial data can be used to represent the location of a person, a place of interest, or the boundary of a city, or a lake.

Azure Cosmos DB for NoSQL supports two spatial data types: the geometry data type and the geography data type.

  • The geometry type represents data in a Euclidean (flat) coordinate system. This type is useful for common geometric tasks, like measuring lines, intersecting polygons, and measuring distance between points.
  • The geography type represents data in a round-earth coordinate system. This type is useful for common geographical tasks, like determining if a location is within specific bounds and measuring distance between locations.

Supported data types

Azure Cosmos DB for NoSQL supports indexing and querying of geospatial point data that's represented using the GeoJSON specification. GeoJSON data structures are always valid JSON objects, so they can be stored and queried using Azure Cosmos DB without any specialized tools or libraries.

Azure Cosmos DB supports the following spatial data types:

  • Point
  • LineString
  • Polygon
  • MultiPolygon

Points

A Point denotes a single position in space. In geospatial data, a Point represents the exact location, which could be a street address of a grocery store, a kiosk, an automobile, or a city. A point is represented in GeoJSON (and Azure Cosmos DB for NOSQL) using its coordinate pair (longitude and latitude).

Consider this example GeoJSON point. The longitude is -122.12826822304672 and the latitude is 47.63980239335718.

{
  "type": "Point",
  "coordinates": [
    -122.12826822304672,
    47.63980239335718
  ]
}

Tip

For the geography data type, GeoJSON specification specifies longitude first and latitude second. Like in other mapping applications, longitude and latitude are angles and represented in terms of degrees. Longitude values are measured from the Prime Meridian and are between -180 degrees and 180.0 degrees, and latitude values are measured from the equator and are between -90.0 degrees and 90.0 degrees.

For the geometry data type, GeoJSON specification specifies the horizontal axis first and the vertical axis second.

Spatial data types can be embedded in an item as shown in this example of a facility item that includes the GeoJSON data.

{
  "name": "Headquarters",
  "location": {
    "type": "Point",
    "coordinates": [
      -122.12826822304672,
      47.63980239335718
    ]
  },
  "category": "business-offices"
}

Azure Cosmos DB for NoSQL interprets coordinates as represented per the WGS-84 reference system. For more information, see coordinate reference systems.

LineStrings

LineStrings represent a series of two or more points in space and the line segments that connect them. In geospatial data, LineStrings are commonly used to represent highways or rivers.

In this example, a line string is used to represent a line that drawn between two points.

{
  "type": "LineString",
  "coordinates": [
    [ 31.8, -5 ],
    [ 31.8, -4.7 ]
  ]
}

Polygons

A Polygon is a boundary of connected points that forms a closed LineString. Polygons are commonly used to represent natural formations like lakes or political jurisdictions like cities and states.

Points within a Polygon must be specified in counter-clockwise order. A Polygon specified in clockwise order represents the inverse of the region within it.

In this example, a polygon is created by connecting multiple points.

{
    "type":"Polygon",
    "coordinates":[ [
        [ 31.8, -5 ],
        [ 32, -5 ],
        [ 32, -4.7 ],
        [ 31.8, -4.7 ],
        [ 31.8, -5 ]
    ] ]
}

Tip

The GeoJSON specification requires that for valid Polygons, the last coordinate pair provided should be the same as the first, to create a closed shape.

MultiPolygons

A MultiPolygon is an array of zero or more Polygons. MultiPolygons can't overlap sides or have any common area. They may touch at one or more points.

Here's an example of a MultiPolygon.

{
    "type":"MultiPolygon",
    "coordinates":[[[
            [52.0, 12.0],
            [53.0, 12.0],
            [53.0, 13.0],
            [52.0, 13.0],
            [52.0, 12.0]
        ]],
        [[
            [50.0, 0.0],
            [51.0, 0.0],
            [51.0, 5.0],
            [50.0, 5.0],
            [50.0, 0.0]
        ]]]
}

Coordinate reference systems

Since the shape of the earth is irregular, coordinates of geography geospatial data are represented in many coordinate reference systems (CRS). Each CRS has their own frames of reference and units of measurement. For example, the "National Grid of Britain" is a reference system is accurate for the United Kingdom, but not outside it.

The most popular CRS in use today is the World Geodetic System WGS-84. GPS devices, and many mapping services including Google Maps and Bing Maps APIs use WGS-84. Azure Cosmos DB for NoSQL supports indexing and querying of geography geospatial data using the WGS-84 CRS only.

Creating items with spatial data

When you create items that contain GeoJSON values, they're automatically indexed with a spatial index. This default indexing occurs in accordance to the indexing policy of the container. The default indexing policy, if not specified, will accurately index GeoJSON data. If you're working with an SDK in a dynamically typed language like Python or Node.js, you must create valid GeoJSON.

var userProfileitem = {
    "id": "aaaaaaaa-0000-1111-2222-bbbbbbbbbbbb",
    "location":{
        "type":"Point",
        "coordinates":[ -122.12, 47.66 ]
    }
};

client.createitem(`dbs/${databaseName}/colls/${collectionName}`, userProfileitem, (err, created) => {
    // additional code within the callback
});

If you don't have the latitude and longitude information, but have the physical addresses or location name, look up the actual coordinates using an online service. Services like Bing Maps can assist with finding the actual geography data from a known location name. For more information about Bing Maps geocoding, see Bing Maps REST Services.

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