AWS documentdb documentation change

Service: documentdb · 2026-03-31 · Documentation low

File: documentdb/latest/developerguide/nearSphere.md

Summary

Added new documentation page for the $nearSphere operator in Amazon DocumentDB, including operator description, parameters, MongoDB shell example, and code examples in Node.js and Python

Security assessment

This change adds standard documentation for a geospatial query operator ($nearSphere) with no mention of security vulnerabilities, patches, or security incidents. The code examples include standard TLS connection parameters (tls=true, tlsCAFile) which are routine security best practices for DocumentDB connections, but these are not new security features being documented.

Diff

diff --git a/documentdb/latest/developerguide/nearSphere.md b/documentdb/latest/developerguide/nearSphere.md
index 8b1378917..9c6bdad54 100644
--- a//documentdb/latest/developerguide/nearSphere.md
+++ b//documentdb/latest/developerguide/nearSphere.md
@@ -0,0 +1 @@
+[](/pdfs/documentdb/latest/developerguide/developerguide.pdf#nearSphere "Open PDF")
@@ -1,0 +3,153 @@
+[Documentation](/index.html)[Amazon DocumentDB](/documentdb/index.html)[Developer Guide](what-is.html)
+
+Example (MongoDB Shell)Code examples
+
+# $nearSphere
+
+The `$nearSphere` operator in Amazon DocumentDB is used to find documents that are within a specified distance of a geospatial point. This operator is particularly useful for geo-spatial queries, such as finding all restaurants within a certain radius of a given location.
+
+**Parameters**
+
+  * `$geometry`: A GeoJSON object that represents the reference point. Must be a `Point` object with `type` and `coordinates` fields.
+
+  * `$minDistance`: (optional) The minimum distance (in meters) from the reference point that documents must be.
+
+  * `$maxDistance`: (optional) The maximum distance (in meters) from the reference point that documents must be.
+
+
+
+
+## Example (MongoDB Shell)
+
+In this example, we will find all restaurants within 2 kilometers (2000 meters) of a specific location in Seattle, WA.
+
+**Create sample documents**
+    
+    
+    db.usarestaurants.insert([
+      {
+        name: "Noodle House",
+        location: { type: "Point", coordinates: [-122.3516, 47.6156] }
+      },
+      {
+        name: "Pike Place Grill",
+        location: { type: "Point", coordinates: [-122.3403, 47.6101] }
+      },
+      {
+        name: "Seattle Coffee Co.",
+        location: { type: "Point", coordinates: [-122.3339, 47.6062] }
+      }
+    ]);
+
+**Query example**
+    
+    
+    db.usarestaurants.find({
+      location: {
+        $nearSphere: {
+          $geometry: {
+            type: "Point",
+            coordinates: [-122.3516, 47.6156]
+          },
+          $minDistance: 1,
+          $maxDistance: 2000
+        }
+      }
+    }, {
+      name: 1
+    });
+
+**Output**
+    
+    
+    { "_id" : ObjectId("611f3da985009a81ad38e74b"), "name" : "Noodle House" }
+    { "_id" : ObjectId("611f3da985009a81ad38e74c"), "name" : "Pike Place Grill" }
+
+## Code examples
+
+To view a code example for using the `$nearSphere` command, choose the tab for the language that you want to use:
+
+Node.js
+    
+    
+    
+    const { MongoClient } = require('mongodb');
+    
+    async function findNearbyRestaurants() {
+      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 restaurants = db.collection('usarestaurants');
+    
+      const result = await restaurants.find({
+        location: {
+          $nearSphere: {
+            $geometry: {
+              type: "Point",
+              coordinates: [-122.3516, 47.6156]
+            },
+            $minDistance: 1,
+            $maxDistance: 2000
+          }
+        }
+      }, {
+        projection: { name: 1 }
+      }).toArray();
+    
+      console.log(result);
+      client.close();
+    }
+    
+    findNearbyRestaurants();
+
+Python
+    
+    
+    
+    from pymongo import MongoClient
+    
+    def find_nearby_restaurants():
+        client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
+        db = client.test
+        restaurants = db.usarestaurants
+    
+        result = list(restaurants.find({
+            'location': {
+                '$nearSphere': {
+                    '$geometry': {
+                        'type': 'Point',
+                        'coordinates': [-122.3516, 47.6156]
+                    },
+                    '$minDistance': 1,
+                    '$maxDistance': 2000
+                }
+            }
+        }, {
+            'name': 1
+        }))
+    
+        print(result)
+        client.close()
+    
+    find_nearby_restaurants()
+
+![Warning](https://d1ge0kk1l5kms0.cloudfront.net/images/G/01/webservices/console/warning.png) **Javascript is disabled or is unavailable in your browser.**
+
+To use the Amazon Web Services Documentation, Javascript must be enabled. Please refer to your browser's Help pages for instructions.
+
+[Document Conventions](/general/latest/gr/docconventions.html)
+
+$near
+
+Query and projection operators
+
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+
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