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

`$minDistance` is a find operator used in conjunction with `$nearSphere` or `$geoNear` to filter documents that are at least at the specified minimum distance from the center point. This operator is supported in Amazon DocumentDB and functions similarly to its counterpart in MongoDB.

**Parameters**
+ `$minDistance`: The minimum distance (in meters) from the center point to include documents in the results.

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

In this example, we'll find all restaurants within a 2-kilometer radius of a specific location in Seattle, Washington.

**Create sample documents**

```
db.usarestaurants.insertMany([
  {
    "state": "Washington",
    "city": "Seattle",
    "name": "Noodle House",
    "rating": 4.8,
    "location": {
      "type": "Point",
      "coordinates": [-122.3517, 47.6159]
    }
  },
  {
    "state": "Washington",
    "city": "Seattle",
    "name": "Pike Place Grill",
    "rating": 4.5,
    "location": {
      "type": "Point",
      "coordinates": [-122.3412, 47.6102]
    }
  },
  {
    "state": "Washington",
    "city": "Bellevue",
    "name": "The Burger Joint",
    "rating": 4.2,
    "location": {
      "type": "Point",
      "coordinates": [-122.2007, 47.6105]
    }
  }
]);
```

**Query example**

```
db.usarestaurants.find({
  "location": {
    "$nearSphere": {
      "$geometry": {
        "type": "Point",
        "coordinates": [-122.3516, 47.6156]
      },
      "$minDistance": 1,
      "$maxDistance": 2000
    }
  }
}, {
  "name": 1
});
```

**Output**

```
{ "_id" : ObjectId("611f3da985009a81ad38e74b"), "name" : "Noodle House" }
{ "_id" : ObjectId("611f3da985009a81ad38e74c"), "name" : "Pike Place Grill" }
```

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

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

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

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

async function findRestaurantsNearby() {
  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('usarestaurants');

  const result = await collection.find({
    "location": {
      "$nearSphere": {
        "$geometry": {
          "type": "Point",
          "coordinates": [-122.3516, 47.6156]
        },
        "$minDistance": 1,
        "$maxDistance": 2000
      }
    }
  }, {
    "projection": { "name": 1 }
  }).toArray();

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

findRestaurantsNearby();
```

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

```
from pymongo import MongoClient

def find_restaurants_nearby():
    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.usarestaurants

    result = list(collection.find({
        "location": {
            "$nearSphere": {
                "$geometry": {
                    "type": "Point",
                    "coordinates": [-122.3516, 47.6156]
                },
                "$minDistance": 1,
                "$maxDistance": 2000
            }
        }
    }, {
        "projection": {"name": 1}
    }))

    print(result)
    client.close()

find_restaurants_nearby()
```

------