$minute - Amazon DocumentDB
Example (MongoDB Shell)Code examples
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$minute

The $minute aggregation pipeline stage in Amazon DocumentDB extracts the minute value from a date or timestamp field.

This operator is useful when you need to perform date and time-based calculations or grouping within your aggregation pipeline.

Parameters

  • expression: The date or timestamp field from which to extract the minute value.

Example (MongoDB Shell)

The following example demonstrates how to use the $minute operator to group the documents by the minute value extracted from the timestamp field and count the number of documents in each group.

Create sample documents

db.events.insertMany([
  { timestamp: new Date("2023-04-15T10:30:25.000Z") },
  { timestamp: new Date("2023-04-15T10:30:35.000Z") },
  { timestamp: new Date("2023-04-15T10:31:05.000Z") },
  { timestamp: new Date("2023-04-15T10:31:45.000Z") },
  { timestamp: new Date("2023-04-15T10:32:15.000Z") }
]);

Query example

db.events.aggregate([
  {
    $group: {
      _id: {
        minute: { $minute: "$timestamp" }
      },
      count: { $count: {} }
    }
  },
  { $sort: { "_id.minute": 1 } }
]);

Output

[
  { "_id": { "minute": 30 }, "count": 2 },
  { "_id": { "minute": 31 }, "count": 2 },
  { "_id": { "minute": 32 }, "count": 1 }
]

Code examples

To view a code example for using the $minute 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 collection = db.collection('events');

  await collection.insertMany([
    { timestamp: new Date("2023-04-15T10:30:25.000Z") },
    { timestamp: new Date("2023-04-15T10:30:35.000Z") },
    { timestamp: new Date("2023-04-15T10:31:05.000Z") },
    { timestamp: new Date("2023-04-15T10:31:45.000Z") },
    { timestamp: new Date("2023-04-15T10:32:15.000Z") }
  ]);

  const result = await collection.aggregate([
    {
      $group: {
        _id: {
          minute: { $minute: "$timestamp" }
        },
        count: { $count: {} }
      }
    },
    { $sort: { "_id.minute": 1 } }
  ]).toArray();

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

example();
Python
from pymongo import MongoClient
from datetime import datetime

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']
    collection = db['events']

    collection.insert_many([
        {'timestamp': datetime(2023, 4, 15, 10, 30, 25)},
        {'timestamp': datetime(2023, 4, 15, 10, 30, 35)},
        {'timestamp': datetime(2023, 4, 15, 10, 31, 5)},
        {'timestamp': datetime(2023, 4, 15, 10, 31, 45)},
        {'timestamp': datetime(2023, 4, 15, 10, 32, 15)}
    ])

    result = list(collection.aggregate([
        {
            '$group': {
                '_id': {
                    'minute': {'$minute': '$timestamp'}
                },
                'count': {'$count': {}}
            }
        },
        {'$sort': {'_id.minute': 1}}
    ]))

    print(result)
    client.close()

example()