AWS documentdb documentation change

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

File: documentdb/latest/developerguide/minDistance.md

Summary

Added new documentation page for the $minDistance operator in Amazon DocumentDB, including detailed explanation, MongoDB shell example, and code examples in Node.js and Python

Security assessment

This change adds routine documentation for a geospatial query operator ($minDistance) used with $nearSphere and $geoNear. The documentation includes standard usage examples and connection strings with TLS parameters, but there is no evidence of addressing a specific security vulnerability, weakness, or incident. The TLS parameters shown in code examples (tls=true, tlsCAFile=global-bundle.pem) are standard security best practices for DocumentDB connections, but this is not new security documentation - it's part of routine example code.

Diff

diff --git a/documentdb/latest/developerguide/minDistance.md b/documentdb/latest/developerguide/minDistance.md
index 8b1378917..4a93fed7d 100644
--- a//documentdb/latest/developerguide/minDistance.md
+++ b//documentdb/latest/developerguide/minDistance.md
@@ -0,0 +1 @@
+[](/pdfs/documentdb/latest/developerguide/developerguide.pdf#minDistance "Open PDF")
@@ -1,0 +3,167 @@
+[Documentation](/index.html)[Amazon DocumentDB](/documentdb/index.html)[Developer Guide](what-is.html)
+
+Example (MongoDB Shell)Code examples
+
+# $minDistance
+
+`$minDistance` is a find operator used in conjunction with `$nearSphere` or `$geoNear` to filter documents that are at least at the specified minimum distance from the center point. This operator is supported in Amazon DocumentDB and functions similarly to its counterpart in MongoDB.
+
+**Parameters**
+
+  * `$minDistance`: The minimum distance (in meters) from the center point to include documents in the results.
+
+
+
+
+## Example (MongoDB Shell)
+
+In this example, we'll find all restaurants within a 2-kilometer radius of a specific location in Seattle, Washington.
+
+**Create sample documents**
+    
+    
+    db.usarestaurants.insertMany([
+      {
+        "state": "Washington",
+        "city": "Seattle",
+        "name": "Noodle House",
+        "rating": 4.8,
+        "location": {
+          "type": "Point",
+          "coordinates": [-122.3517, 47.6159]
+        }
+      },
+      {
+        "state": "Washington",
+        "city": "Seattle",
+        "name": "Pike Place Grill",
+        "rating": 4.5,
+        "location": {
+          "type": "Point",
+          "coordinates": [-122.3412, 47.6102]
+        }
+      },
+      {
+        "state": "Washington",
+        "city": "Bellevue",
+        "name": "The Burger Joint",
+        "rating": 4.2,
+        "location": {
+          "type": "Point",
+          "coordinates": [-122.2007, 47.6105]
+        }
+      }
+    ]);
+
+**Query example**
+    
+    
+    db.usarestaurants.find({
+      "location": {
+        "$nearSphere": {
+          "$geometry": {
+            "type": "Point",
+            "coordinates": [-122.3516, 47.6156]
+          },
+          "$minDistance": 1,
+          "$maxDistance": 2000
+        }
+      }
+    }, {
+      "name": 1
+    });
+
+**Output**
+    
+    
+    { "_id" : ObjectId("611f3da985009a81ad38e74b"), "name" : "Noodle House" }
+    { "_id" : ObjectId("611f3da985009a81ad38e74c"), "name" : "Pike Place Grill" }
+
+## Code examples
+
+To view a code example for using the `$minDistance` command, choose the tab for the language that you want to use:
+
+Node.js
+    
+    
+    
+    const { MongoClient } = require('mongodb');
+    
+    async function findRestaurantsNearby() {
+      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('usarestaurants');
+    
+      const result = await collection.find({
+        "location": {
+          "$nearSphere": {
+            "$geometry": {
+              "type": "Point",
+              "coordinates": [-122.3516, 47.6156]
+            },
+            "$minDistance": 1,
+            "$maxDistance": 2000
+          }
+        }
+      }, {
+        "projection": { "name": 1 }
+      }).toArray();
+    
+      console.log(result);
+      client.close();
+    }
+    
+    findRestaurantsNearby();
+
+Python
+    
+    
+    
+    from pymongo import MongoClient
+    
+    def find_restaurants_nearby():
+        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.usarestaurants
+    
+        result = list(collection.find({
+            "location": {
+                "$nearSphere": {
+                    "$geometry": {
+                        "type": "Point",
+                        "coordinates": [-122.3516, 47.6156]
+                    },
+                    "$minDistance": 1,
+                    "$maxDistance": 2000
+                }
+            }
+        }, {
+            "projection": {"name": 1}
+        }))
+    
+        print(result)
+        client.close()
+    
+    find_restaurants_nearby()
+
+![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)
+
+$maxDistance
+
+$near
+
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+
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+
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+
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