$range

The $range aggregation operator in Amazon DocumentDB is used to create an array of consecutive numbers within a specified range. This operator is particularly useful for generating sequences of numbers, such as mile markers for aid stations in a race, as demonstrated in the examples below.

Parameters

• start: The starting value for the range.

• end: The ending value for the range.

• step: (optional) The step value to use when generating the range. If not provided, the default step value is 1.

Example (MongoDB Shell)

In this example, we'll use the $range operator to generate the mile markers for water stations in a bicycle race.

Create sample documents

db.races.insertMany([
  { _id: 0, race: "STP", distance: 206 },
  { _id: 1, race: "RSVP", distance: 160 },
  { _id: 2, race: "Chilly Hilly", distance: 33 },
  { _id: 3, race: "Flying Wheels", distance: 100 }
]);

Query example

db.races.aggregate([
  {
    $project: {
      race: 1,
      "waterStations": { $range: [20, "$distance", 20] }
    }
  }
]);

Output

[
  {
    _id: 0,
    race: 'STP',
    waterStations: [
       20,  40,  60,  80,
      100, 120, 140, 160,
      180, 200
    ]
  },
  {
    _id: 1,
    race: 'RSVP',
    waterStations: [
       20,  40,  60, 80,
      100, 120, 140
    ]
  },
  { _id: 2, race: 'Chilly Hilly', waterStations: [ 20 ] },
  { _id: 3, race: 'Flying Wheels', waterStations: [ 20, 40, 60, 80 ] }
]

Code examples

To view a code example for using the $range 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');

  try {
    await client.connect();
    const db = client.db('test');
    const collection = db.collection('races');

    const pipeline = [
      {
        $project: {
          race: 1,
          waterStations: { $range: [20, "$distance", 20] } 
        }
      }
    ];

    const results = await collection.aggregate(pipeline).toArray();

    console.dir(results, { depth: null });

  } finally {
    await client.close();
  }
}

example().catch(console.error);

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')

  try:
      db = client.test
      collection = db.races

      pipeline = [
          {
              "$project": {
                  "race": 1,
                  "waterStations": { "$range": [20, "$distance", 20] }
              }
          }
      ]

      results = collection.aggregate(pipeline)

      for doc in results:
          print(doc)

  except Exception as e:
      print(f"An error occurred: {e}")

  finally:
      client.close()

example()