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

$sampleRate

New from version 8.0.1.

Not supported by Elastic cluster.

The $sampleRate operator in Amazon DocumentDB matches a random sample of the input documents based on the specified rate. You can use it in a find() query filter or in an aggregation $match stage. Because selection is probabilistic, the number of documents returned is approximate and can vary between runs.

Parameters

  • value: A number in the range [0, 1] (inclusive), passed directly to the operator (for example, { $sampleRate: 0.3 }), that sets the probability of including each document. A value of 0 returns no documents; a value of 1 returns all documents.

Example (MongoDB Shell)

The following example uses $sampleRate to return approximately 30 percent of the documents in a collection.

Create sample documents

db.events.insertMany([
  { _id: 1, type: "click" },
  { _id: 2, type: "view" },
  { _id: 3, type: "click" },
  { _id: 4, type: "view" },
  { _id: 5, type: "purchase" }
]);

Query example

db.events.aggregate([
  { $match: { $sampleRate: 0.3 } }
]);

Output

The operation returns a random subset of the documents. Because $sampleRate is probabilistic, the specific documents returned and their count vary each time the query runs.

Code examples

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

Node.js
const { MongoClient } = require('mongodb');

async function example() {
  const uri = 'mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false';
  const client = new MongoClient(uri);

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

    // Return approximately 30% of the documents
    const result = await collection.aggregate([
      { $match: { $sampleRate: 0.3 } }
    ]).toArray();

    console.log(result);
  } finally {
    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')

    try:
        db = client['test']
        collection = db['events']

        # Return approximately 30% of the documents
        result = list(collection.aggregate([
            { '$match': { '$sampleRate': 0.3 } }
        ]))

        print(result)
    finally:
        client.close()

example()