Find Restaurants with Geospatial Queries

Prerequisites

Download the example datasets from https://raw.githubusercontent.com/mongodb/docs-assets/geospatial/neighborhoods.json and https://raw.githubusercontent.com/mongodb/docs-assets/geospatial/restaurants.json. These contain the collections restaurants and neighborhoods respectively.

After downloading the datasets, import them into the database:

mongoimport <path to restaurants.json> -c=restaurants
mongoimport <path to neighborhoods.json> -c=neighborhoods

A geospatial index, and almost always improves performance of $geoWithin and $geoIntersects queries.

Because this data is geographical, create a 2dsphere index on each collection using the mongo shell:

db.restaurants.createIndex({ location: "2dsphere" })
db.neighborhoods.createIndex({ geometry: "2dsphere" })

Exploring the Data

Inspect an entry in the newly-created restaurants collection from within the mongo shell:

db.restaurants.findOne()

This query returns a document like the following:

{
   location: {
      type: "Point",
      coordinates: [-73.856077, 40.848447]
   },
   name: "Morris Park Bake Shop"
}

This restaurant document corresponds to the location shown in the following figure:

Because the tutorial uses a 2dsphere index, the geometry data in the location field must follow the GeoJSON format.

Now inspect an entry in the neighborhoods collection:

db.neighborhoods.findOne()

This query will return a document like the following:

{
   geometry: {
      type: "Polygon",
      coordinates: [[
         [ -73.99, 40.75 ],
         ...
         [ -73.98, 40.76 ],
         [ -73.99, 40.75 ]
      ]]
    },
    name: "Hell's Kitchen"
}

This geometry corresponds to the region depicted in the following figure:

click to enlarge

Find the Current Neighborhood

Assuming the user’s mobile device can give a reasonably accurate location for the user, it is simple to find the user's current neighborhood with $geoIntersects.

Suppose the user is located at -73.93414657 longitude and 40.82302903 latitude. To find the current neighborhood, you will specify a point using the special $geometry field in GeoJSON format:

db.neighborhoods.findOne({ geometry: { $geoIntersects: { $geometry: { type: "Point", coordinates: [ -73.93414657, 40.82302903 ] } } } })

This query will return the following result:

{
    "_id" : ObjectId("55cb9c666c522cafdb053a68"),
    "geometry" : {
        "type" : "Polygon",
        "coordinates" : [
            [
                [
                    -73.93383000695911,
                    40.81949109558767
                ],
                ...
            ]
        ]
    },
    "name" : "Central Harlem North-Polo Grounds"
}

Find all Restaurants in the Neighborhood

You can also query to find all restaurants contained in a given neighborhood. Run the following in the mongo shell to find the neighborhood containing the user, and then count the restaurants within that neighborhood:

var neighborhood = db.neighborhoods.findOne( { geometry: { $geoIntersects: { $geometry: { type: "Point", coordinates: [ -73.93414657, 40.82302903 ] } } } } )
db.restaurants.find( { location: { $geoWithin: { $geometry: neighborhood.geometry } } } ).count()

This query will tell you that there are 127 restaurants in the requested neighborhood, visualized in the following figure:

click to enlarge

Find Restaurants within a Distance

To find restaurants within a specified distance of a point, you can use either $geoWithin with $centerSphere to return results in unsorted order, or $nearSphere with $maxDistance if you need results sorted by distance.

Unsorted with $geoWithin

To find restaurants within a circular region, use $geoWithin with $centerSphere. $centerSphere is a MongoDB-specific syntax to denote a circular region by specifying the center and the radius in radians.

$geoWithin does not return the documents in any specific order, so it may show the user the furthest documents first.

The following will find all restaurants within five miles of the user:

db.restaurants.find({ location:
   { $geoWithin:
      { $centerSphere: [ [ -73.93414657, 40.82302903 ], 5 / 3963.2 ] } } })

$centerSphere's second argument accepts the radius in radians, so you must divide it by the radius of the earth in miles. See Calculate Distance Using Spherical Geometry for more information on converting between distance units.

Sorted with $nearSphere

You may also use $nearSphere and specify a $maxDistance term in meters. This will return all restaurants within five miles of the user in sorted order from nearest to farthest:

var METERS_PER_MILE = 1609.34
db.restaurants.find({ location: { $nearSphere: { $geometry: { type: "Point", coordinates: [ -73.93414657, 40.82302903 ] }, $maxDistance: 5 * METERS_PER_MILE } } })