$merge

Introduced in 8.0

The $merge aggregation stage in Amazon DocumentDB is used to merge the results of the previous pipeline stage into a target collection. This is useful for updating or inserting documents in a target collection based on the data from the input documents.

The $merge stage allows you to perform various actions based on the matching condition between the input documents and the target collection, such as:

- Insert new documents
- Update existing documents
- Delete documents
- Fail the operation if there are any conflicts

Parameters

• into: (required) The name of the target collection to merge the input documents into.

• on: (required) The field(s) to use as the matching condition between the input documents and the target collection.

• whenMatched: (optional) The action to perform when the input document matches an existing document in the target collection. Supported values are: "merge", "replace", "keepExisting", and "fail".

• whenNotMatched: (optional) The action to perform when the input document does not match any document in the target collection. Supported values are: "insert" and "fail".

Example (MongoDB Shell)

The following example demonstrates how to use the $merge stage to update a users collection with new data from an input pipeline.

Create sample documents

db.users.insertMany([
  { _id: 1, name: "John Doe", email: "[e-mail]" },
  { _id: 2, name: "Jane Smith", email: "[e-mail]" }
]);

db.inputData.insertMany([
  { _id: 1, name: "John Doe", email: "[e-mail]", phone: "123-456-7890" },
  { _id: 3, name: "Bob Johnson", email: "[e-mail]", phone: "987-654-3210" }
]);

Query example

db.inputData.aggregate([
  {
    $merge: {
      into: "users",
      on: "_id",
      whenMatched: "merge",
      whenNotMatched: "insert"
    }
  }
])

Output

After running the $merge pipeline, the users collection will contain the following documents:

[
  { _id: 1, name: "John Doe", email: "[e-mail]", phone: "123-456-7890" },
  { _id: 2, name: "Jane Smith", email: "[e-mail]" },
  { _id: 3, name: "Bob Johnson", email: "[e-mail]", phone: "987-654-3210" }
]

Code examples

To view a code example for using the $merge command, choose the tab for the language that you want to use:

Node.js

Here's an example of using the $merge operator in a Node.js application:

const { MongoClient } = require('mongodb');

async function example() {
  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');

  await db.collection('inputData').aggregate([
    {
      $merge: {
        into: 'users',
        on: '_id',
        whenMatched: 'merge',
        whenNotMatched: 'insert'
      }
    }
  ]).toArray();

  const users = await db.collection('users').find({}).toArray();
  console.log(users);

  await client.close();
}

example();

Python

Here's an example of using the $merge operator in a Python application:

from pymongo import MongoClient

def example():
    client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
    db = client['test']

    # Assumes collections 'users' and 'inputData' already exist with sample data
    db.inputData.aggregate([
        {
            '$merge': {
                'into': 'users',
                'on': '_id',
                'whenMatched': 'merge',
                'whenNotMatched': 'insert'
            }
        }
    ])

    users = list(db.users.find({}))
    print(users)

    client.close()

example()