Working with Geospatial Data

Working with geospatial data in MongoDB

MongoDB supports geospatial data and provides various features for storing and querying location-based data. Geospatial indexes and queries allow you to efficiently perform spatial operations such as finding points within a specific area or determining the distance between points.

Geospatial Indexes

To work with geospatial data, you need to create a geospatial index. MongoDB supports two types of geospatial indexes:

• 2d Index: Suitable for flat, planar surfaces.
• 2dsphere Index: Suitable for spherical surfaces such as the Earth's surface.

Creating a Geospatial Index

Below is an example of creating a 2dsphere index on a location field:

db.places.createIndex({ location: "2dsphere" })

Geospatial Queries

Geospatial queries in MongoDB allow you to perform operations such as finding documents near a specific point, within a specific area, or within a specific shape.

Example: Finding Documents Near a Point

Below is an example of using the $near operator to find documents near a specific point:

db.places.find({
    location: {
        $near: {
            $geometry: {
                type: "Point",
                coordinates: [ -73.9667, 40.78 ]
            },
            $maxDistance: 1000
        }
    }
})

Example: Finding Documents Within a Polygon

Below is an example of using the $geoWithin operator to find documents within a polygon:

db.places.find({
    location: {
        $geoWithin: {
            $geometry: {
                type: "Polygon",
                coordinates: [
                    [
                        [ -73.97, 40.77 ],
                        [ -73.95, 40.77 ],
                        [ -73.95, 40.75 ],
                        [ -73.97, 40.75 ],
                        [ -73.97, 40.77 ]
                    ]
                ]
            }
        }
    }
})