For AI agents: a documentation index is available at https://www.mongodb.com/docs/llms.txt — markdown versions of all pages are available by appending .md to any URL path.
Docs Menu

Geospatial Queries

In this guide, you can learn how to query geospatial data by using the Scala driver. You can also learn about different geospatial data formats supported by MongoDB.

Geospatial data represents a geographical location on the surface of the Earth. Examples of geospatial data include:

  • Locations of movie theaters

  • Borders of countries

  • Routes of bicycle rides

  • Dog exercise areas in New York City

The examples in this guide use the theaters collection in the sample_mflix database from the Atlas sample datasets. To access this collection from your Scala application, create a MongoClient that connects to an Atlas cluster and assign the following values to your database and collection variables:

val database: MongoDatabase = mongoClient.getDatabase("sample_mflix")
val collection: MongoCollection[Document] = database.getCollection("theaters")

To learn how to create a free MongoDB Atlas cluster and load the sample datasets, see the MongoDB Get Started guide.

To store and query your geospatial data in MongoDB, use GeoJSON. GeoJSON is a data format created by the Internet Engineering Task Force (IETF).

Here is the location of MongoDB headquarters in GeoJSON:

"location" : {
"type": "Point",
"coordinates": [-73.986805, 40.7620853]
}

For definitive information on GeoJSON, see the official IETF specification.

A position represents a single place on Earth and is given as an array containing two or three number values:

  • Longitude in the first position (required)

  • Latitude in the second position (required)

  • Elevation in the third position (optional)

Important

Longitude then Latitude

GeoJSON orders coordinates as longitude first and latitude second. This may be surprising as geographic coordinate system conventions generally list latitude first and longitude second. Make sure to check what format any other tools you are working with use. Popular tools such as OpenStreetMap and Google Maps list coordinates as latitude first and longitude second.

Your GeoJSON object's type determines its geometric shape. Geometric shapes are made up of positions.

Here are some common GeoJSON types and how you can specify them with positions:

To learn more about the shapes you can use in MongoDB, see GeoJSON in the Server manual.

To create a 2dsphere index, use the Indexes.geo2dsphere() helper to create a specification for the 2dsphere index. Pass the specification to the MongoCollection.createIndex() method to create the index.

The following example creates a 2dsphere index on the "location.geo" field in the theaters collection:

val indexObservable = collection.createIndex(Indexes.geo2dsphere("location.geo"))
Await.result(indexObservable.toFuture(), Duration(10, TimeUnit.SECONDS))

To learn more about indexes in the Scala driver, see the Optimize Queries by Using Indexes guide.

You can store geospatial data using x and y coordinates on a two-dimensional Euclidean plane. Coordinates on a two-dimensional plane are called legacy coordinate pairs.

Legacy coordinate pairs have the following structure:

{ "location" : [ x, y ] }

The field value contains an array of two values in which the first represents the x axis value and the second represents the y axis value.

To query data stored as legacy coordinate pairs, you must add the field containing legacy coordinate pairs to a 2d index. The following snippet creates a 2d index on the coordinates field by using the Indexes object:

val indexObservable = collection.createIndex(Indexes.geo2d("coordinates"))
Await.result(indexObservable.toFuture(), Duration(10, TimeUnit.SECONDS))

To learn more about indexes in the Scala driver, see the Optimize Queries by Using Indexes guide.

For more information on legacy coordinate pairs, see the Legacy Coordinate Pairs section of the Geospatial Queries guide in the Server manual.

Tip

Supported Operators

Spherical (2dsphere) and flat (2d) indexes support some, but not all, of the same query operators. To view a full list of operators and their index compatibility, see the Geospatial Query Operators section of the Geospatial Queries guide in the Server manual.

Geospatial queries consist of a query operator and GeoJSON shapes as query parameters.

To query your geospatial data, use one of the following query operators:

  • $near

  • $geoWithin

  • $nearSphere

  • $geoIntersects requires a 2dsphere index

You can specify these query operators in the Scala driver with the near(), geoWithin(), nearSphere(), and geoIntersects() methods of the Filters object.

To learn more about geospatial query operators, see the Geospatial Query Operators section of the Geospatial Queries guide in the Server manual.

To view a full list of Filters helper methods, see the Filters API documentation.

To specify a shape to use in a geospatial query, use the Position, Point, LineString, and Polygon classes from the Scala driver.

To learn more about the GeoJSON shape classes, see the GeoJSON package API Documentation.

The following examples use the MongoDB Atlas theaters collection in the sample_mflix sample database. You can learn how to set up your own free-tier Atlas cluster and how to load the sample dataset in the Get Started with the Scala Driver guide.

The examples in this section require the following imports:

import org.mongodb.scala.*
import org.mongodb.scala.model.Indexes
import org.mongodb.scala.model.Filters
import org.mongodb.scala.model.Projections
import com.mongodb.client.model.geojson.{Point, Polygon, Position}
import java.util.Arrays
import java.util.concurrent.TimeUnit
import scala.concurrent.Await
import scala.concurrent.duration.Duration

The theaters collection already contains a 2dsphere index on the location.geo field.

To search for and return documents from nearest to farthest from a point, use the near() method of the Filters object. The near() method constructs a query with the $near query operator.

The following example returns documents that are at most 1000 meters from the specified GeoJSON Point instance, sorted from nearest to farthest:

val refPoint = new Point(new Position(-73.986805, 40.7620853))
val findObservable = collection.find(Filters.near("location.geo", refPoint, Some(1000.0), Some(0.0)))
val results = Await.result(findObservable.toFuture(), Duration(10, TimeUnit.SECONDS))
{"_id": {"$oid": "59a47287cfa9a3a73e51e8e2"}, "theaterId": 1908, "location":
{"address": {"street1": "750 Seventh Ave", "city": "New York", "state": "NY",
"zipcode": "10019"}, "geo": {"type": "Point", "coordinates": [-73.983487, 40.76078]}}}
{"_id": {"$oid": "59a47286cfa9a3a73e51e838"}, "theaterId": 1448, "location":
{"address": {"street1": "1880 Broadway", "city": "New York", "state": "NY",
"zipcode": "10023"}, "geo": {"type": "Point", "coordinates": [-73.982094, 40.769882]}}}

Tip

MongoDB uses the same reference system as GPS satellites to calculate geometries over the Earth.

To learn more about the $near operator, see the $near reference in the Server manual.

To search for geospatial data within a specified shape, use the geoWithin() method of the Filters object. The geoWithin() method constructs a query with the $geoWithin query operator.

The following example searches for movie theaters in a section of Long Island. The example applies a projection so that each result includes only the location.address.city field and excludes the _id field:

val longIslandTriangle = new Polygon(Arrays.asList(
new Position(-72.0, 40.0),
new Position(-74.0, 41.0),
new Position(-72.0, 39.0),
new Position(-72.0, 40.0)
))
val projection = Projections.fields(
Projections.include("location.address.city"),
Projections.excludeId()
)
val geoWithinComparison = Filters.geoWithin("location.geo", longIslandTriangle)
val findObservable = collection.find(geoWithinComparison).projection(projection)
val results = Await.result(findObservable.toFuture(), Duration(10, TimeUnit.SECONDS))
results.foreach(doc => println(doc.toJson()))
{"location": {"address": {"city": "Baldwin"}}}
{"location": {"address": {"city": "Levittown"}}}
{"location": {"address": {"city": "Westbury"}}}
{"location": {"address": {"city": "Mount Vernon"}}}
{"location": {"address": {"city": "Massapequa"}}}

The following figure shows the polygon defined by the longIslandTriangle variable and dots representing the locations of the movie theaters that the query returns.

Area of Long Island in which to search for movie theaters

To learn more about the $geoWithin operator, see the $geoWithin reference in the Server manual.

To learn more about performing geospatial queries, see Geospatial Queries in the Server manual.