AWS documentdb documentation change

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

File: documentdb/latest/developerguide/meta.md

Summary

Added new documentation page for the $meta operator with detailed explanation, parameters, MongoDB shell example, and code examples in Node.js and Python

Security assessment

This change adds documentation for a query operator ($meta) used in text search operations to retrieve relevance scores. The code examples include TLS connection parameters (tls=true, tlsCAFile=global-bundle.pem) which are standard secure connection practices, but this is not addressing a specific security vulnerability or incident. The change appears to be routine feature documentation.

Diff

diff --git a/documentdb/latest/developerguide/meta.md b/documentdb/latest/developerguide/meta.md
index 8b1378917..3372b412c 100644
--- a//documentdb/latest/developerguide/meta.md
+++ b//documentdb/latest/developerguide/meta.md
@@ -0,0 +1 @@
+[](/pdfs/documentdb/latest/developerguide/developerguide.pdf#meta "Open PDF")
@@ -1,0 +3,127 @@
+[Documentation](/index.html)[Amazon DocumentDB](/documentdb/index.html)[Developer Guide](what-is.html)
+
+Example (MongoDB Shell)Code examples
+
+# $meta
+
+The `$meta` operator is used to access metadata associated with the current query execution. This operator is primarily used for text search operations, where the metadata can provide information about the relevance of the matched documents.
+
+**Parameters**
+
+  * `textScore`: Retrieves the text search score for the document. This score indicates the relevance of the document to the text search query.
+
+
+
+
+## Example (MongoDB Shell)
+
+The following example demonstrates how to use the `$meta` operator to retrieve the text search score for documents matching a text search query.
+
+**Create sample documents**
+    
+    
+    db.documents.insertMany([
+      { _id: 1, title: "Coffee Basics", content: "Coffee is a popular beverage made from roasted coffee beans." },
+      { _id: 2, title: "Coffee Culture", content: "Coffee coffee coffee - the ultimate guide to coffee brewing and coffee preparation." },
+      { _id: 3, title: "Tea vs Coffee", content: "Many people prefer tea over coffee for its health benefits." }
+    ]);
+
+**Create text index**
+    
+    
+    db.documents.createIndex({ content: "text" });
+
+**Query example**
+    
+    
+    db.documents.find(
+      { $text: { $search: "coffee" } },
+      { _id: 0, title: 1, content: 1, score: { $meta: "textScore" } }
+    ).sort({ score: { $meta: "textScore" } });
+
+**Output**
+    
+    
+    [
+      {
+        title: 'Coffee Culture',
+        content: 'Coffee coffee coffee - the ultimate guide to coffee brewing and coffee preparation.',
+        score: 0.8897688388824463
+      },
+      {
+        title: 'Coffee Basics',
+        content: 'Coffee is a popular beverage made from roasted coffee beans.',
+        score: 0.75990891456604
+      },
+      {
+        title: 'Tea vs Coffee',
+        content: 'Many people prefer tea over coffee for its health benefits.',
+        score: 0.6079270839691162
+      }
+    ]
+
+## Code examples
+
+To view a code example for using the `$meta` command, choose the tab for the language that you want to use:
+
+Node.js
+    
+    
+    
+    const { MongoClient } = require('mongodb');
+    
+    async function findWithTextScore() {
+      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('documents');
+    
+      const result = await collection.find(
+        { $text: { $search: "coffee" } },
+        { projection: { _id: 0, title: 1, content: 1, score: { $meta: "textScore" } } }
+      ).sort({ score: { $meta: "textScore" } }).toArray();
+    
+      console.log(result);
+      client.close();
+    }
+    
+    findWithTextScore();
+
+Python
+    
+    
+    
+    from pymongo import MongoClient
+    
+    client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
+    db = client['test']
+    collection = db['documents']
+    
+    for doc in collection.find(
+        {'$text': {'$search': 'coffee'}},
+        {'_id': 0, 'title': 1, 'content': 1, 'score': {'$meta': 'textScore'}}
+    ).sort([('score', {'$meta': 'textScore'})]):
+        print(doc)
+    
+    client.close()
+
+![Warning](https://d1ge0kk1l5kms0.cloudfront.net/images/G/01/webservices/console/warning.png) **Javascript is disabled or is unavailable in your browser.**
+
+To use the Amazon Web Services Documentation, Javascript must be enabled. Please refer to your browser's Help pages for instructions.
+
+[Document Conventions](/general/latest/gr/docconventions.html)
+
+$lte
+
+$ne
+
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