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Tutorials > MongoDB > Geospatial queries and indexing

Geospatial queries and indexing

Geospatial queries and indexing are features in MongoDB that allow you to store and query data based on their spatial location. This is particularly useful for applications that require location-based services, such as mapping, navigation, and social networking. Here are some examples of how to use geospatial queries and indexing in MongoDB:

  • Creating a 2D geospatial index:
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db.places.createIndex({location: "2dsphere"})

This creates a 2D geospatial index on the location field of the places collection. The 2dsphere option specifies that the index should use spherical geometry to support queries on a round earth model.

  • Storing location data as a GeoJSON object:
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db.places.insertOne({
  name: "Central Park",
  location: {
    type: "Point",
    coordinates: [-73.9654, 40.7829]
  }
})

This creates a places document with a location field that contains a GeoJSON Point object, which represents the longitude and latitude of Central Park in New York City.

  • Querying for documents within a certain radius of a location:
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db.places.find({
  location: {
    $near: {
      $geometry: {
        type: "Point",
        coordinates: [-73.9654, 40.7829]
      },
      $maxDistance: 1000
    }
  }
})

This returns all places documents that are within 1000 meters of Central Park, sorted by their distance from the park. The $near operator is used to specify the geospatial query, while the $maxDistance option is used to limit the distance of the query.

By using geospatial queries and indexing in MongoDB, you can build powerful and efficient location-based applications that provide users with relevant and personalized content based on their location.



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