AWS documentdb documentation change

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

File: documentdb/latest/developerguide/group.md

Summary

Added comprehensive documentation for the $group aggregation stage in Amazon DocumentDB, including parameters, MongoDB Shell example, and code examples in Node.js and Python with connection strings.

Security assessment

This change adds standard documentation for a database aggregation operator ($group) with example code. The examples include connection strings with TLS parameters (tls=true, tlsCAFile=global-bundle.pem) which are standard security practices for DocumentDB connections, but this is routine documentation of existing security features rather than addressing a specific security issue. There is no evidence of vulnerability fixes, security patches, or incident response documentation.

Diff

diff --git a/documentdb/latest/developerguide/group.md b/documentdb/latest/developerguide/group.md
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--- a//documentdb/latest/developerguide/group.md
+++ b//documentdb/latest/developerguide/group.md
@@ -0,0 +1 @@
+[](/pdfs/documentdb/latest/developerguide/developerguide.pdf#group "Open PDF")
@@ -1,0 +3,138 @@
+[Documentation](/index.html)[Amazon DocumentDB](/documentdb/index.html)[Developer Guide](what-is.html)
+
+Example (MongoDB Shell)Code examples
+
+# $group
+
+The `$group` aggregation stage in Amazon DocumentDB allows you to group documents by a specified expression and perform various accumulative operations on the grouped data. This can be useful for tasks such as calculating totals, averages, or other statistics based on the grouped data.
+
+**Parameters**
+
+  * `_id`: Specifies the expression by which the input documents should be grouped. This can be a field name, a computed expression, or a combination of both.
+
+  * `accumulator expressions`: (optional) One or more accumulator expressions that should be applied to the grouped data. These expressions use the accumulator operators mentioned above.
+
+
+
+
+## Example (MongoDB Shell)
+
+The following example groups customers by their city and calculates the total order amount for each city.
+
+**Create sample documents**
+    
+    
+    db.customers.insertMany([
+      { name: "John Doe", city: "New York", orders: [{ amount: 100 }, { amount: 200 }] },
+      { name: "Jane Smith", city: "Los Angeles", orders: [{ amount: 150 }, { amount: 300 }] },
+      { name: "Bob Johnson", city: "New York", orders: [{ amount: 75 }, { amount: 125 }] },
+      { name: "Samantha Lee", city: "Chicago", orders: [{ amount: 50 }, { amount: 100 }] }
+    ]);
+
+**Query example**
+    
+    
+    db.customers.aggregate([
+      {
+        $group: {
+          _id: "$city",
+          totalOrders: { $sum: { $sum: "$orders.amount" } }
+        }
+      }
+    ]);
+
+**Output**
+    
+    
+    [
+      { _id: 'Chicago', totalOrders: 150 },
+      { _id: 'Los Angeles', totalOrders: 450 },
+      { _id: 'New York', totalOrders: 500 }
+    ]
+
+## Code examples
+
+To view a code example for using the `$group` command, choose the tab for the language that you want to use:
+
+Node.js
+    
+    
+    
+    const { MongoClient } = require('mongodb');
+    
+    async function groupByCity() {
+      const uri = 'mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false';
+      const client = new MongoClient(uri);
+    
+      try {
+        await client.connect();
+        const db = client.db('test');
+        const result = await db.collection('customers').aggregate([
+          { $unwind: '$orders' },
+          {
+            $group: {
+              _id: '$city',
+              totalOrders: { $sum: '$orders.amount' }
+            }
+          }
+        ]).toArray();
+    
+        console.log(result);
+      } catch (err) {
+        console.error('Error during aggregation:', err);
+      } finally {
+        await client.close();
+      }
+    }
+    
+    groupByCity();
+
+Python
+    
+    
+    
+    from pymongo import MongoClient
+    
+    def group_by_city():
+        client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
+        
+        try:
+            db = client.test
+            result = list(db.customers.aggregate([
+                {'$unwind': '$orders'},
+                {
+                    '$group': {
+                        '_id': '$city',
+                        'totalOrders': {'$sum': '$orders.amount'}
+                    }
+                }
+            ]))
+            print(result)
+        except Exception as e:
+            print(f"Error during aggregation: {e}")
+        finally:
+            client.close()
+    
+    group_by_city()
+
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+
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+
+[Document Conventions](/general/latest/gr/docconventions.html)
+
+$geoNear
+
+$gt
+
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