Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

$setUnion

The $setUnion aggregation operator in Amazon DocumentDB is used to combine two or more sets of values and return a set that contains all the unique elements from the input sets. This operator is useful when you need to perform set-based operations on array fields in your documents.

Parameters

Example (MongoDB Shell)

The following example demonstrates how to use the $setUnion operator to combine the unique elements from two array fields in a collection.

Create sample documents

db.users.insertMany([
  { _id: 1, name: "Alice", hobbies: ["reading", "swimming"], skills: ["coding", "writing"] },
  { _id: 2, name: "Bob", hobbies: ["cooking", "gardening"], skills: ["coding", "photography"] },
  { _id: 3, name: "Charlie", hobbies: ["reading", "painting"], skills: ["gardening", "music"] }
]);

Query example

db.users.aggregate([
  {
    $project: {
      name: 1,
      allInterests: { $setUnion: ["$hobbies", "$skills"] }
    }
  }
]);

Output

[
  { "_id" : 1, "name" : "Alice", "allInterests" : [ "coding", "reading", "swimming", "writing" ] },
  { "_id" : 2, "name" : "Bob", "allInterests" : [ "coding", "cooking", "gardening", "photography" ] },
  { "_id" : 3, "name" : "Charlie", "allInterests" : [ "gardening", "music", "painting", "reading" ] }
]

In this example, the $setUnion operator is used to combine the unique elements from the hobbies and skills array fields for each user document. The resulting allInterests field contains the union of all the unique hobbies and skills for each user.

Code examples

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

Node.js

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');
  const users = db.collection('users');

  const result = await users.aggregate([
    {
      $project: {
        _id: 1,
        name: 1,
        allInterests: { $setUnion: ["$hobbies", "$skills"] }
      }
    }
  ]).toArray();

  console.log(result);
  await client.close();
}

example();

Python

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']
    users = db['users']

    result = list(users.aggregate([
        {
            '$project': {
                '_id': 1,
                'name': 1,
                'allInterests': { '$setUnion': ["$hobbies", "$skills"] }
            }
        }
    ]))

    print(result)
    client.close()

example()