Terjemahan disediakan oleh mesin penerjemah. Jika konten terjemahan yang diberikan bertentangan dengan versi bahasa Inggris aslinya, utamakan versi bahasa Inggris.

# Geospasial
<a name="mongo-apis-geospatial-operators"></a>

Bagian ini memberikan informasi rinci tentang operator geospasial yang didukung oleh Amazon DocumentDB.

**Topics**
+ [\$1geometry](geometry.md)
+ [\$1geointersects](geoIntersects.md)
+ [\$1geowithin](geoWithin.md)
+ [\$1maxDistance](maxDistance.md)
+ [\$1minDistance](minDistance.md)
+ [\$1near](near.md)
+ [\$1nearSphere](nearSphere.md)

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

`$geometry`Operator di Amazon DocumentDB digunakan untuk menentukan objek geometri GeoJSON sebagai bagian dari kueri geospasial. Operator ini digunakan bersama dengan operator kueri geospasial lainnya seperti `$geoWithin` dan `$geoIntersects` untuk melakukan kueri spasial pada data Anda.

Di Amazon DocumentDB, operator mendukung jenis `$geometry` geometri GeoJSON berikut:
+ Poin
+ LineString
+ Polygon
+ MultiPoint
+ MultiLineString
+ MultiPolygon
+ GeometryCollection

**Parameter**
+ `type`: Jenis objek geometri GeoJSON, misalnya,,, dll. `Point` `Polygon`
+ `coordinates`: Sebuah array koordinat yang mewakili geometri. Struktur array koordinat tergantung pada jenis geometri.

## Contoh (MongoDB Shell)
<a name="geometry-examples"></a>

Contoh berikut menunjukkan cara menggunakan `$geometry` operator untuk melakukan `$geoIntersects` query di Amazon DocumentDB.

**Buat dokumen sampel**

```
db.locations.insertMany([
  { 
    "_id": 1,
    "name": "Location 1",
    "location": { 
      "type": "Point",
      "coordinates": [-73.983253, 40.753941]
    }
  },
  { 
    "_id": 2,
    "name": "Location 2", 
    "location": {
      "type": "Polygon",
      "coordinates": [[
        [-73.998427, 40.730309],
        [-73.954348, 40.730309],
        [-73.954348, 40.780816],
        [-73.998427, 40.780816],
        [-73.998427, 40.730309]
      ]]
    }
  }
]);
```

**Contoh kueri**

```
db.locations.find({
  "location": {
    "$geoIntersects": {
      "$geometry": {
        "type": "Polygon",
        "coordinates": [[
          [-73.998, 40.730],
          [-73.954, 40.730],
          [-73.954, 40.781],
          [-73.998, 40.781],
          [-73.998, 40.730]
        ]]
      }
    }
  }
})
```

**Keluaran**

```
[
  {
    "_id": 2,
    "name": "Location 2",
    "location": {
      "type": "Polygon",
      "coordinates": [
        [
          [-73.998427, 40.730309],
          [-73.954348, 40.730309],
          [-73.954348, 40.780816],
          [-73.998427, 40.780816],
          [-73.998427, 40.730309]
        ]
      ]
    }
  }
]
```

## Contoh kode
<a name="geometry-code"></a>

Untuk melihat contoh kode untuk menggunakan `$geometry` perintah, pilih tab untuk bahasa yang ingin Anda gunakan:

------
#### [ 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('locations');

  const query = {
    "location": {
      "$geoIntersects": {
        "$geometry": {
          "type": "Polygon",
          "coordinates": [[
            [-73.998, 40.730],
            [-73.954, 40.730],
            [-73.954, 40.781],
            [-73.998, 40.781],
            [-73.998, 40.730]
          ]]
        }
      }
    }
  };

  const result = await collection.find(query).toArray();
  console.log(result);

  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')
    db = client['test']
    collection = db['locations']

    query = {
        "location": {
            "$geoIntersects": {
                "$geometry": {
                    "type": "Polygon",
                    "coordinates": [[
                        [-73.998, 40.730],
                        [-73.954, 40.730],
                        [-73.954, 40.781],
                        [-73.998, 40.781],
                        [-73.998, 40.730]
                    ]]
                }
            }
        }
    }

    result = list(collection.find(query))
    print(result)

    client.close()

example()
```

------

# \$1geointersects
<a name="geoIntersects"></a>

`$geoIntersects`Operator di Amazon DocumentDB digunakan untuk menemukan dokumen yang data geospasialnya berpotongan dengan objek GeoJSON tertentu. Operator ini berguna untuk aplikasi yang memerlukan identifikasi dokumen berdasarkan hubungan spasialnya dengan bentuk geografis tertentu, seperti poligon atau multipoligon.

**Parameter**
+ `$geometry`: Sebuah objek GeoJSON yang mewakili bentuk untuk memeriksa persimpangan. Jenis objek GeoJSON yang didukung `Point` adalah`LineString`,,, `Polygon` dan. `MultiPolygon`

## Contoh (MongoDB Shell)
<a name="geoIntersects-examples"></a>

Contoh berikut menunjukkan cara menggunakan `$geoIntersects` operator untuk menemukan nama negara untuk kumpulan koordinat tertentu di Amazon DocumentDB.

**Buat dokumen sampel**

```
db.states.insertMany([
  {
    "name": "New York",
    "loc": {
      "type": "Polygon",
      "coordinates": [[
        [-74.25909423828125, 40.47556838210948],
        [-73.70819091796875, 40.47556838210948],
        [-73.70819091796875, 41.31342607582222],
        [-74.25909423828125, 41.31342607582222],
        [-74.25909423828125, 40.47556838210948]
      ]]
    }
  },
  {
    "name": "California",
    "loc": {
      "type": "Polygon",
      "coordinates": [[
        [-124.4091796875, 32.56456771381587],
        [-114.5458984375, 32.56456771381587],
        [-114.5458984375, 42.00964153424558],
        [-124.4091796875, 42.00964153424558],
        [-124.4091796875, 32.56456771381587]
      ]]
    }
  }
]);
```

**Contoh kueri**

```
var location = [-73.965355, 40.782865];

db.states.find({
  "loc": {
    "$geoIntersects": {
      "$geometry": {
        "type": "Point",
        "coordinates": location
      }
    }
  }
}, {
  "name": 1
});
```

**Keluaran**

```
{ "_id" : ObjectId("536b0a143004b15885c91a2c"), "name" : "New York" }
```

## Contoh kode
<a name="geoIntersects-code"></a>

Untuk melihat contoh kode untuk menggunakan `$geoIntersects` perintah, pilih tab untuk bahasa yang ingin Anda gunakan:

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

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

async function findStateByGeoIntersects(longitude, latitude) {
  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('states');

  const query = {
    loc: {
      $geoIntersects: {
        $geometry: {
          type: 'Point',
          coordinates: [longitude, latitude]
        }
      }
    }
  };

  const projection = {
    _id: 0,
    name: 1
  };

  const document = await collection.findOne(query, { projection });

  await client.close();
  
  if (document) {
    return document.name;
  } else {
    throw new Error('The geo location you entered was not found in the United States!');
  }
}
```

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

```
from pymongo import MongoClient

def find_state_by_geointersects(longitude, latitude):
    try:
        client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
        db = client.test
        collection_states = db.states

        query_geointersects = {
            "loc": {
                "$geoIntersects": {
                    "$geometry": {
                        "type": "Point",
                        "coordinates": [longitude, latitude]
                    }
                }
            }
        }

        document = collection_states.find_one(query_geointersects,
                                              projection={
                                                  "_id": 0,
                                                  "name": 1
                                              })
        if document is not None:
            state_name = document['name']
            return state_name
        else:
            raise Exception("The geo location you entered was not found in the United States!")
    except Exception as e:
        print('Exception in geoIntersects: {}'.format(e))
        raise
    finally:
        if client is not None:
            client.close()
```

------

# \$1geowithin
<a name="geoWithin"></a>

`$geoWithin`Operator di Amazon DocumentDB digunakan untuk menemukan dokumen yang data lokasinya (direpresentasikan sebagai objek GeoJSON) sepenuhnya terkandung dalam bentuk tertentu, seperti poligon atau multipoligon. Ini berguna untuk menanyakan objek yang terletak di dalam wilayah geografis tertentu.

**Parameter**
+ `$geometry`: Sebuah objek GeoJSON yang mewakili bentuk untuk query terhadap.

## Contoh (MongoDB Shell)
<a name="geoWithin-examples"></a>

Contoh berikut menunjukkan bagaimana menggunakan `$geoWithin` operator untuk menemukan semua bandara yang terletak di negara bagian New York.

**Buat dokumen sampel**

```
// Insert state document
db.states.insert({
    "name": "New York",
    "loc": {
        "type": "Polygon",
        "coordinates": [[
            [-79.76278, 45.0],
            [-73.94, 45.0],
            [-73.94, 40.5],
            [-79.76278, 40.5],
            [-79.76278, 45.0]
        ]]
    }
});

// Insert airport documents
db.airports.insert([
    {
        "name": "John F. Kennedy International Airport",
        "type": "airport",
        "code": "JFK",
        "loc": {
            "type": "Point",
            "coordinates": [-73.7781, 40.6413]
        }
    },
    {
        "name": "LaGuardia Airport",
        "type": "airport",
        "code": "LGA",
        "loc": {
            "type": "Point",
            "coordinates": [-73.8772, 40.7769]
        }
    },
    {
        "name": "Buffalo Niagara International Airport",
        "type": "airport",
        "code": "BUF",
        "loc": {
            "type": "Point",
            "coordinates": [-78.7322, 42.9403]
        }
    }
]);
```

**Contoh kueri**

```
var state = db.states.findOne({"name": "New York"});

db.airports.find({
    "loc": {
        "$geoWithin": {
            "$geometry": state.loc
        }
    }
}, {
    "name": 1,
    "type": 1,
    "code": 1,
    "_id": 0
});
```

**Keluaran**

```
[
  {
    "name": "John F. Kennedy International Airport",
    "type": "airport",
    "code": "JFK"
  },
  {
    "name": "LaGuardia Airport",
    "type": "airport",
    "code": "LGA"
  }
]
```

## Contoh kode
<a name="geoWithin-code"></a>

Untuk melihat contoh kode untuk menggunakan `$geoWithin` perintah, pilih tab untuk bahasa yang ingin Anda gunakan:

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

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

async function findAirportsWithinState(stateName) {
  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 stateDoc = await db.collection('states').findOne({ name: stateName }, { projection: { _id: 0, loc: 1 } });
  const airportDocs = await db.collection('airports').find({
    loc: {
      $geoWithin: {
        $geometry: stateDoc.loc
      }
    }
  }, { projection: { name: 1, type: 1, code: 1, _id: 0 } }).toArray();

  console.log(airportDocs);

  await client.close();
}

findAirportsWithinState('New York');
```

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

```
from pymongo import MongoClient

def find_airports_within_state(state_name):
    try:
        client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
        db = client['test']
        state_doc = db.states.find_one({'name': state_name}, {'_id': 0, 'loc': 1})
        airport_docs = db.airports.find({
            'loc': {
                '$geoWithin': {
                    '$geometry': state_doc['loc']
                }
            }
        }, {'name': 1, 'type': 1, 'code': 1, '_id': 0})
        
        return list(airport_docs)
    except Exception as e:
        print(f'Error: {e}')
    finally:
        client.close()

airports = find_airports_within_state('New York')
print(airports)
```

------

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

`$maxDistance`Operator di Amazon DocumentDB digunakan untuk menentukan jarak maksimum (dalam meter) dari titik GeoJSON di mana dokumen harus berada di dalamnya untuk dimasukkan dalam hasil kueri. Operator ini digunakan bersama dengan `$nearSphere` operator untuk melakukan kueri geospasial.

**Parameter**
+ `$maxDistance`: Jarak maksimum (dalam meter) dari titik referensi di mana dokumen harus berada di dalamnya untuk dimasukkan dalam hasil kueri.

## Contoh (MongoDB Shell)
<a name="maxDistance-examples"></a>

Contoh berikut menunjukkan cara menggunakan `$maxDistance` operator di Amazon DocumentDB untuk menemukan semua ibu kota negara bagian dalam jarak 100 kilometer dari Boston.

**Buat dokumen sampel**

```
db.capitals.insert([
  { state: "Massachusetts", city: "Boston", location: { type: "Point", coordinates: [-71.0589, 42.3601] } },
  { state: "Rhode Island", city: "Providence", location: { type: "Point", coordinates: [-71.4128, 41.8239] } },
  { state: "New Hampshire", city: "Concord", location: { type: "Point", coordinates: [-71.5383, 43.2067] } },
  { state: "Vermont", city: "Montpelier", location: { type: "Point", coordinates: [-72.5751, 44.2604] } }
]);
```

**Contoh kueri**

```
db.capitals.find(
  {
    location: {
      $nearSphere: {
        $geometry: { type: "Point", coordinates: [-71.0589, 42.3601] },
        $maxDistance: 100000
      }
    }
  },
  { state: 1, city: 1, _id: 0 }
);
```

**Keluaran**

```
[
  { "state": "Rhode Island", "city": "Providence" },
  { "state": "New Hampshire", "city": "Concord" }
]
```

## Contoh kode
<a name="maxDistance-code"></a>

Untuk melihat contoh kode untuk menggunakan `$maxDistance` perintah, pilih tab untuk bahasa yang ingin Anda gunakan:

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

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

async function findCapitalsNearBoston() {
  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 capitals = db.collection('capitals');

  const result = await capitals.find({
    location: {
      $nearSphere: {
        $geometry: { type: "Point", coordinates: [-71.0589, 42.3601] },
        $maxDistance: 100000
      }
    }
  }, {
    projection: { state: 1, city: 1, _id: 0 }
  }).toArray();

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

findCapitalsNearBoston();
```

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

```
from pymongo import MongoClient

def find_capitals_near_boston():
    client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
    db = client.test
    capitals = db.capitals

    result = list(capitals.find(
        {
            "location": {
                "$nearSphere": {
                    "$geometry": { "type": "Point", "coordinates": [-71.0589, 42.3601] },
                    "$maxDistance": 100000
                }
            }
        },
        {"state": 1, "city": 1, "_id": 0}
    ))

    print(result)
    client.close()

find_capitals_near_boston()
```

------

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

`$minDistance`adalah operator find yang digunakan bersama dengan `$nearSphere` atau `$geoNear` untuk memfilter dokumen yang setidaknya pada jarak minimum yang ditentukan dari titik pusat. Operator ini didukung di Amazon DocumentDB dan fungsinya mirip dengan mitranya di MongoDB.

**Parameter**
+ `$minDistance`: Jarak minimum (dalam meter) dari titik pusat untuk memasukkan dokumen dalam hasil.

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

Dalam contoh ini, kita akan menemukan semua restoran dalam radius 2 kilometer dari lokasi tertentu di Seattle, Washington.

**Buat dokumen sampel**

```
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]
    }
  }
]);
```

**Contoh kueri**

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

**Keluaran**

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

## Contoh kode
<a name="minDistance-code"></a>

Untuk melihat contoh kode untuk menggunakan `$minDistance` perintah, pilih tab untuk bahasa yang ingin Anda gunakan:

------
#### [ 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()
```

------

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

`$near`Operator di Amazon DocumentDB digunakan untuk menemukan dokumen yang secara geografis dekat titik tertentu. Ia mengembalikan dokumen yang dipesan berdasarkan jarak, dengan dokumen terdekat terlebih dahulu. Operator ini memerlukan indeks geospasial 2dsphere dan berguna untuk kueri kedekatan pada data lokasi.

**Parameter**
+ `$geometry`: Sebuah objek GeoJSON Point yang mendefinisikan titik pusat untuk query dekat.
+ `$maxDistance`: (opsional) Jarak maksimum dalam meter dari titik yang ditentukan bahwa dokumen dapat untuk mencocokkan kueri.
+ `$minDistance`: (opsional) Jarak minimum dalam meter dari titik yang ditentukan bahwa dokumen dapat untuk mencocokkan kueri.

**Persyaratan Indeks**
+ `2dsphere index`: Diperlukan untuk kueri geospasial pada data GeoJSON Point.

## Contoh (MongoDB Shell)
<a name="near-examples"></a>

Contoh berikut menunjukkan bagaimana menggunakan `$near` operator untuk menemukan restoran terdekat ke lokasi tertentu di Seattle, Washington.

**Buat dokumen sampel**

```
db.usarestaurants.insert([
  {
    "name": "Noodle House",
    "city": "Seattle",
    "state": "Washington",
    "rating": 4.8,
    "location": { "type": "Point", "coordinates": [-122.3517, 47.6159] }
  },
  {
    "name": "Pike Place Grill",
    "city": "Seattle",
    "state": "Washington",
    "rating": 4.2,
    "location": { "type": "Point", "coordinates": [-122.3403, 47.6062] }
  },
  {
    "name": "Lola",
    "city": "Seattle",
    "state": "Washington",
    "rating": 4.5,
    "location": { "type": "Point", "coordinates": [-122.3407, 47.6107] }
  }
]);
```

**Buat indeks 2dsphere**

```
db.usarestaurants.createIndex({ "location": "2dsphere" });
```

**Contoh kueri dengan GeoJSON Point**

```
db.usarestaurants.find({
  location: {
    $near: {
      $geometry: {
        type: "Point",
        coordinates: [-122.3516, 47.6156]
      },
      $maxDistance: 100,
      $minDistance: 10
    }
  }
});
```

**Keluaran**

```
{
  "_id" : ObjectId("69031ec9ea1c2922a1ce5f4a"),
  "name" : "Noodle House",
  "city" : "Seattle",
  "state" : "Washington",
  "rating" : 4.8,
  "location" : {
    "type" : "Point",
    "coordinates" : [ -122.3517, 47.6159 ]
  }
}
```

## Contoh kode
<a name="near-code"></a>

Untuk melihat contoh kode untuk menggunakan `$near` perintah, pilih tab untuk bahasa yang ingin Anda gunakan:

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

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

async function findNearbyRestaurants() {
  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 restaurants = db.collection('usarestaurants');

  // Create 2dsphere index
  await restaurants.createIndex({ "location": "2dsphere" });

  const result = await restaurants.find({
    location: {
      $near: {
        $geometry: {
          type: "Point",
          coordinates: [-122.3516, 47.6156]
        },
        $maxDistance: 100,
        $minDistance: 10
      }
    }
  }).toArray();

  console.log(result);

  client.close();
}

findNearbyRestaurants();
```

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

```
from pymongo import MongoClient

def find_nearby_restaurants():
    client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
    db = client['test']
    restaurants = db['usarestaurants']

    # Create 2dsphere index
    restaurants.create_index([("location", "2dsphere")])

    result = list(restaurants.find({
        'location': {
            '$near': {
                '$geometry': {
                    'type': 'Point',
                    'coordinates': [-122.3516, 47.6156]
                },
                '$maxDistance': 100,
                '$minDistance': 10
            }
        }
    }))

    print(result)

    client.close()

find_nearby_restaurants()
```

------

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

`$nearSphere`Operator di Amazon DocumentDB digunakan untuk menemukan dokumen yang berada dalam jarak tertentu dari titik geospasial. Operator ini sangat berguna untuk kueri geo-spasial, seperti menemukan semua restoran dalam radius tertentu dari lokasi tertentu.

**Parameter**
+ `$geometry`: Sebuah objek GeoJSON yang mewakili titik referensi. Harus menjadi `Point` objek dengan `type` dan `coordinates` bidang.
+ `$minDistance`: (opsional) Jarak minimum (dalam meter) dari titik referensi yang harus dimiliki dokumen.
+ `$maxDistance`: (opsional) Jarak maksimum (dalam meter) dari titik referensi yang harus dimiliki dokumen.

## Contoh (MongoDB Shell)
<a name="nearSphere-examples"></a>

Dalam contoh ini, kita akan menemukan semua restoran dalam jarak 2 kilometer (2000 meter) dari lokasi tertentu di Seattle, WA.

**Buat dokumen sampel**

```
db.usarestaurants.insert([
  {
    name: "Noodle House",
    location: { type: "Point", coordinates: [-122.3516, 47.6156] }
  },
  {
    name: "Pike Place Grill",
    location: { type: "Point", coordinates: [-122.3403, 47.6101] }
  },
  {
    name: "Seattle Coffee Co.",
    location: { type: "Point", coordinates: [-122.3339, 47.6062] }
  }
]);
```

**Contoh kueri**

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

**Keluaran**

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

## Contoh kode
<a name="nearSphere-code"></a>

Untuk melihat contoh kode untuk menggunakan `$nearSphere` perintah, pilih tab untuk bahasa yang ingin Anda gunakan:

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

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

async function findNearbyRestaurants() {
  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 restaurants = db.collection('usarestaurants');

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

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

findNearbyRestaurants();
```

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

```
from pymongo import MongoClient

def find_nearby_restaurants():
    client = MongoClient('mongodb://<username>:<password>@<cluster-endpoint>:27017/?tls=true&tlsCAFile=global-bundle.pem&replicaSet=rs0&readPreference=secondaryPreferred&retryWrites=false')
    db = client.test
    restaurants = db.usarestaurants

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

    print(result)
    client.close()

find_nearby_restaurants()
```

------