$geometry - Amazon DocumentDB

$geometry

The $geometry operator in Amazon DocumentDB is used to specify a GeoJSON geometry object as part of a geospatial query. This operator is used in conjunction with other geospatial query operators like $geoWithin and $geoIntersects to perform spatial queries on your data.

In Amazon DocumentDB, the $geometry operator supports the following GeoJSON geometry types:

  • Point

  • LineString

  • Polygon

  • MultiPoint

  • MultiLineString

  • MultiPolygon

  • GeometryCollection

Parameters

  • type: The type of the GeoJSON geometry object, e.g., Point, Polygon, etc.

  • coordinates: An array of coordinates representing the geometry. The structure of the coordinates array depends on the geometry type.

Example (MongoDB Shell)

The following example demonstrates how to use the $geometry operator to perform a $geoIntersects query in Amazon DocumentDB.

Create sample documents

db.locations.insertMany([ { "_id": 1, "name": "Location 1", "location": { "type": "Point", "coordinates": [-73.983253, 40.753941] } }, { "_id": 2, "name": "Location 2", "location": { "type": "Polygon", "coordinates": [[ [-73.998427, 40.730309], [-73.954348, 40.730309], [-73.954348, 40.780816], [-73.998427, 40.780816], [-73.998427, 40.730309] ]] } } ]);

Query example

db.locations.find({ "location": { "$geoIntersects": { "$geometry": { "type": "Polygon", "coordinates": [[ [-73.998, 40.730], [-73.954, 40.730], [-73.954, 40.781], [-73.998, 40.781], [-73.998, 40.730] ]] } } } })

Output

[ { "_id": 2, "name": "Location 2", "location": { "type": "Polygon", "coordinates": [ [ [-73.998427, 40.730309], [-73.954348, 40.730309], [-73.954348, 40.780816], [-73.998427, 40.780816], [-73.998427, 40.730309] ] ] } } ]

Code examples

To view a code example for using the $geometry command, choose the tab for the language that you want to use:

Node.js
const { MongoClient } = require('mongodb'); async function example() { const client = await MongoClient.connect('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false'); const db = client.db('test'); const collection = db.collection('locations'); const query = { "location": { "$geoIntersects": { "$geometry": { "type": "Polygon", "coordinates": [[ [-73.998, 40.730], [-73.954, 40.730], [-73.954, 40.781], [-73.998, 40.781], [-73.998, 40.730] ]] } } } }; const result = await collection.find(query).toArray(); console.log(result); await client.close(); } example();
Python
from pymongo import MongoClient def example(): client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false') db = client['test'] collection = db['locations'] query = { "location": { "$geoIntersects": { "$geometry": { "type": "Polygon", "coordinates": [[ [-73.998, 40.730], [-73.954, 40.730], [-73.954, 40.781], [-73.998, 40.781], [-73.998, 40.730] ]] } } } } result = list(collection.find(query)) print(result) client.close() example()