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AWS documentdb documentation change

Service: documentdb · 2026-03-28 · Documentation low

File: documentdb/latest/developerguide/minDistance.md

Summary

Entire documentation page for the $minDistance operator was removed, including all examples and code samples

Security assessment

This change removes documentation for a specific MongoDB operator ($minDistance) used with geospatial queries. There is no evidence in the diff that this removal is related to a security vulnerability. The change appears to be routine documentation maintenance, possibly removing deprecated or unsupported content. No security implications are evident from the removal of this operator documentation.

Diff

diff --git a/documentdb/latest/developerguide/minDistance.md b/documentdb/latest/developerguide/minDistance.md
index 4a93fed7d..8b1378917 100644
--- a//documentdb/latest/developerguide/minDistance.md
+++ b//documentdb/latest/developerguide/minDistance.md
@@ -1 +0,0 @@
-[](/pdfs/documentdb/latest/developerguide/developerguide.pdf#minDistance "Open PDF")
@@ -3,167 +1,0 @@
-[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
-
-Did this page help you? - Yes
-
-Thanks for letting us know we're doing a good job!
-
-If you've got a moment, please tell us what we did right so we can do more of it.
-
-Did this page help you? - No
-
-Thanks for letting us know this page needs work. We're sorry we let you down.
-
-If you've got a moment, please tell us how we can make the documentation better.