# \$1sample
<a name="sample"></a>

The `$sample` aggregation stage in Amazon DocumentDB is used to randomly select a specified number of documents from a collection. This is useful for tasks such as data analysis, testing, and generating samples for further processing.

**Parameters**
+ `size`: The number of documents to randomly select.

## Example (MongoDB Shell)
<a name="sample-examples"></a>

The following example demonstrates how to use the `$sample` stage to randomly select two documents from the `temp` collection.

**Create sample documents**

```
db.temp.insertMany([
  { "_id": 1, "temperature": 97.1, "humidity": 0.60, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 2, "temperature": 98.2, "humidity": 0.59, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 3, "temperature": 96.8, "humidity": 0.61, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 4, "temperature": 97.9, "humidity": 0.61, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 5, "temperature": 97.5, "humidity": 0.60, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 6, "temperature": 98.0, "humidity": 0.59, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 7, "temperature": 97.2, "humidity": 0.60, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 8, "temperature": 98.1, "humidity": 0.59, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 9, "temperature": 96.9, "humidity": 0.62, "timestamp": ISODate("2019-03-21T21:17:22.425Z") },
  { "_id": 10, "temperature": 97.7, "humidity": 0.60, "timestamp": ISODate("2019-03-21T21:17:22.425Z") }
]);
```

**Query example**

```
db.temp.aggregate([
   { $sample: { size: 2 } }
])
```

**Output**

```
{ "_id" : 4, "temperature" : 97.9, "humidity" : 0.61, "timestamp" : ISODate("2019-03-21T21:17:22.425Z") }
{ "_id" : 9, "temperature" : 96.9, "humidity" : 0.62, "timestamp" : ISODate("2019-03-21T21:17:22.425Z") }
```

As the results show, 2 of the 10 documents were randomly sampled. You can now use these documents to determine an average or to perform min/max calculations.

## Code examples
<a name="sample-code"></a>

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

------
#### [ Node.js ]

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

async function sampleDocuments() {
  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('temp');

  const result = await collection.aggregate([
    { $sample: { size: 2 } }
  ]).toArray();

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

sampleDocuments();
```

------
#### [ Python ]

```
from pymongo import MongoClient

def sample_documents():
    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['temp']

    result = list(collection.aggregate([
        { '$sample': { 'size': 2 } }
    ]))

    print(result)
    client.close()

sample_documents()
```

------