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Operators and Collectors

geoWithin

Definition

geoWithin

The geoWithin operator supports querying geographic points within a given geometry. Only points are returned, even if indexShapes value is true in the index definition.

You can query points within a:

  • Circle

  • Bounding box

  • Polygon

When specifying the coordinates to search, longitude must be specified first and then the latitude. Longitude values can be between -180 and 180, both inclusive. Latitude values can be between -90 and 90, both inclusive. Coordinate values can be integers or doubles.

Note

Atlas Search does not support the following:

  • Non-default coordinate reference system (CRS)

  • Planar XY coordinate system (2 dimensional)

  • Coordinate pairs Point notation (that is, pointFieldName: [12, 34])

Syntax

geoWithin has the following syntax:

{
  "$search": {
     "index": <index name>, // optional, defaults to "default"
     "geoWithin": {
        "path": "<field-to-search>",
        "box | circle | geometry": <object>,
        "score": <score-options>
     }
  }
}

Options

geoWithin uses the following terms to construct a query:

Field
Type
Description
Necessity

box

object

Object that specifies the bottom left and top right GeoJSON points of a box to search within. The object takes the following fields:

  • bottomLeft - Bottom left GeoJSON point.

  • topRight - Top right GeoJSON point.

To learn how to specify GeoJSON data inside a GeoJSON object, see GeoJSON Objects.

Either box, circle, or geometry is required.

conditional

circle

object

Object that specifies the center point and the radius in meters to search within. The object contains the following GeoJSON fields:

  • center - Center of the circle specified as a GeoJSON point.

  • radius - Radius, which is a number, specified in meters. Value must be greater than or equal to 0.

To learn how to specify GeoJSON data inside a GeoJSON object, see GeoJSON Objects.

Either circle, box, or geometry is required.

conditional

geometry

GeoJSON object

GeoJSON object that specifies the MultiPolygon or Polygon to search within. The polygon must be specified as a closed loop where the last position is the same as the first position.

When calculating geospatial results, Atlas Search geoShape and geoWithin operators and MongoDB $geoIntersects operator use different geometries. This difference can be seen in how Atlas Search and MongoDB draw polygonal edges.

Atlas Search draws polygons based on Cartesian distance, which is the shortest line between two points in the coordinate reference system.

MongoDB draws polygons using the geodesic mode based on 2dsphere indexes that is built on top of a third-party library for geodesic types, or the flat mode, from 2d indexes. To learn more, see GeoJSON Objects.

Atlas Search and MongoDB could return different results for geospatial queries involving polygons.

To learn how to specify GeoJSON data inside a GeoJSON object, see GeoJSON Objects.

Either geometry, box, or circle is required.

conditional

path

string or array of strings

Indexed geo type field or fields to search.

yes

score

object

Score to assign to matching search results. By default, the score in the results is 1. You can modify the score using the following options:

  • boost: multiply the result score by the given number.

  • constant: replace the result score with the given number.

  • function: replace the result score with the given expression.

For information on using score in your query, see Score the Documents in the Results.

no

Examples

The following examples use the listingsAndReviews collection in the sample_airbnb database. If you have the sample dataset on your cluster, you can create a custom Atlas Search index for geo type and run the example queries on your cluster.

Use the following sample index definition for indexing the address.location field in the listingsAndReviews collection:

1{
2  "mappings": {
3    "fields": {
4      "address": {
5        "fields": {
6          "location": {
7            "type": "geo"
8          }
9        },
10        "type": "document"
11      },
12      "property_type": {
13        "type": "stringFacet"
14      }
15    }
16  }
17}

box Example

The following query uses the geoWithin operator with the box field to search for properties within a bounding box in Australia.

The query includes a:

  • $limit stage to limit the output to 3 results.

  • $project stage to exclude all fields except name and address.

Note

You don't need to specify indexes named default in your Atlas Search query. If your index has any other name, you must specify the index field.

Basic Example

The following query returns the documents that match the specified search criteria.

1db.listingsAndReviews.aggregate([
2  {
3    "$search": {
4      "geoWithin": {
5        "path": "address.location",
6        "box": {
7          "bottomLeft": {
8            "type": "Point",
9            "coordinates": [112.467, -55.050]
10          },
11          "topRight": {
12            "type": "Point",
13            "coordinates": [168.000, -9.133]
14          }
15        }
16      }
17    }
18  },
19  {
20    $limit: 3
21  },
22  {
23    $project: {
24      "_id": 0,
25      "name": 1,
26      "address": 1
27    }
28  }
29])
{
  "name" : "Surry Hills Studio - Your Perfect Base in Sydney",
  "address" : {
    "street" : "Surry Hills, NSW, Australia",
    "suburb" : "Darlinghurst",
    "government_area" : "Sydney",
    "market" : "Sydney",
    "country" : "Australia",
    "country_code" : "AU",
    "location" : {
      "type" : "Point",
      "coordinates" : [ 151.21554, -33.88029 ],
      "is_location_exact" : true
    }
  }
}
{
  "name" : "Sydney Hyde Park City Apartment (checkin from 6am)",
  "address" : {
    "street" : "Darlinghurst, NSW, Australia",
    "suburb" : "Darlinghurst",
    "government_area" : "Sydney",
    "market" : "Sydney",
    "country" : "Australia",
    "country_code" : "AU",
    "location" : {
      "type" : "Point",
      "coordinates" : [ 151.21346, -33.87603 ],
      "is_location_exact" : false
    }
  }
}
{
  "name" : "THE Place to See Sydney's FIREWORKS",
  "address" : {
    "street" : "Rozelle, NSW, Australia",
    "suburb" : "Lilyfield/Rozelle",
    "government_area" : "Leichhardt",
    "market" : "Sydney",
    "country" : "Australia",
    "country_code" : "AU",
    "location" : {
      "type" : "Point",
      "coordinates" : [ 151.17956, -33.86296 ],
      "is_location_exact" : true
    }
  }
}

Metadata Example

The following query returns the number of types of properties (such as apartment, house, and so on) for the specified search criteria.

1db.listingsAndReviews.aggregate([
2  {
3    "$searchMeta": {
4      "facet": {
5        "operator": {
6          "geoWithin": {
7              "path": "address.location",
8              "box": {
9                "bottomLeft": {
10                  "type": "Point",
11                  "coordinates": [112.467, -55.050]
12                },
13                "topRight": {
14                  "type": "Point",
15                  "coordinates": [168.000, -9.133]
16                }
17              }
18            }
19        },
20        "facets": {
21          "propertyTypeFacet": {
22            "type": "string",
23            "path": "property_type"
24          }
25        }
26      }
27    }
28  }
29])
[
  {
    count: { lowerBound: Long('610') },
    facet: {
      propertyTypeFacet: {
        buckets: [
          { _id: 'Apartment', count: Long('334') },
          { _id: 'House', count: Long('168') },
          { _id: 'Townhouse', count: Long('29') },
          { _id: 'Guest suite', count: Long('20') },
          { _id: 'Condominium', count: Long('11') },
          { _id: 'Cabin', count: Long('8') },
          { _id: 'Serviced apartment', count: Long('7') },
          { _id: 'Villa', count: Long('7') },
          { _id: 'Bungalow', count: Long('5') },
          { _id: 'Guesthouse', count: Long('5') }
        ]
      }
    }
  }
]

circle Example

The following query uses the geoWithin operator with the circle field to search for properties within one mile radius of specified coordinates in Canada.

The query includes a:

  • $limit stage to limit the output to 3 results

  • $project stage to exclude all fields except name and address.

Note

You don't need to specify indexes named default in your Atlas Search query. If your index has any other name, you must specify the index field.

1db.listingsAndReviews.aggregate([
2  {
3    "$search": {
4      "geoWithin": {
5        "circle": {
6          "center": {
7            "type": "Point",
8            "coordinates": [-73.54, 45.54]
9          },
10          "radius": 1600
11        },
12        "path": "address.location"
13      }
14    }
15  },
16  {
17    $limit: 3
18  },
19  {
20    $project: {
21      "_id": 0,
22      "name": 1,
23      "address": 1
24    }
25  }
26])
{
  "name" : "Ligne verte - à 15 min de métro du centre ville.",
  "address" : {
    "street" : "Montréal, Québec, Canada",
    "suburb" : "Hochelaga-Maisonneuve",
    "government_area" : "Mercier-Hochelaga-Maisonneuve",
    "market" : "Montreal",
    "country" : "Canada",
    "country_code" : "CA",
    "location" : {
      "type" : "Point",
      "coordinates" : [ -73.54949, 45.54548 ],
      "is_location_exact" : false
    }
  }
}
{
  "name" : "Belle chambre à côté Metro Papineau",
  "address" : {
    "street" : "Montréal, QC, Canada",
    "suburb" : "Gay Village",
    "government_area" : "Ville-Marie",
    "market" : "Montreal",
    "country" : "Canada",
    "country_code" : "CA",
    "location" : {
      "type" : "Point",
      "coordinates" : [ -73.54985, 45.52797 ],
      "is_location_exact" : false
    }
  }
}
{
  "name" : "L'IDÉAL, ( à 2 min du métro Pie-IX ).",
  "address" : {
    "street" : "Montréal, Québec, Canada",
    "suburb" : "Mercier-Hochelaga-Maisonneuve",
    "government_area" : "Mercier-Hochelaga-Maisonneuve",
    "market" : "Montreal",
    "country" : "Canada",
    "country_code" : "CA",
    "location" : {
      "type" : "Point",
      "coordinates" : [ -73.55208, 45.55157 ],
      "is_location_exact" : true
    }
  }
}

geometry Examples

The following examples use the geoWithin operator with the geometry field to search for properties in Hawaii. The type field specifies whether the area is a GeoJSON Polygon or MultiPolygon.

The queries include a:

  • $limit stage to limit the output to 3 results.

  • $project stage to exclude all fields except name and address.

Note

You don't need to specify indexes named default in your Atlas Search query. If your index has any other name, you must specify the index field.

➤ Use the Select your language drop-down menu on this page to set the language of the examples in this section.

The following Atlas Search query:

  • Uses a compound $search stage to:

    • Specify that results must be within a Polygon defined by a set of coordinates.

    • Give preference to results for properties of type condominium.

  • Uses a $project stage to:

    • Exclude all fields except name, address and property_type.

    • Add a relevance score to each returned document.

[
    {
      "$search": {
        "index": "<INDEX-NAME>",
        "compound": {
          "must": [{
            "geoWithin": {
              "geometry": {
                "type": "Polygon",
                  "coordinates": [[[ -161.323242, 22.512557 ],
                      [ -152.446289, 22.065278 ],
                      [ -156.09375, 17.811456 ],
                      [ -161.323242, 22.512557 ]]]
              },
              "path": "address.location"
            }
          }],
          "should": [{
            "text": {
              "path": "property_type",
              "query": "Condominium"
            }
          }]
        }
      }
    }
]
1SCORE: 2.238388776779175  _id:  "1001265"
2listing_url: "https://www.airbnb.com/rooms/1001265"
3name: "Ocean View Waikiki Marina w/prkg"
4summary: "A short distance from Honolulu's billion dollar mall,
5and the same dis…"
6...
7property_type: "Condominium"
8...
9address: Object
10    street: "Honolulu, HI, United States"
11    suburb: "Oʻahu"
12    government_area: "Primary Urban Center"
13    market: "Oahu"
14    country: "United States"
15    country_code: "US"
16    location: Object
17    type: "Point"
18    coordinates: Array
19        0: -157.83919
20        1: 21.28634
21    is_location_exact: true
22...
23
24SCORE: 2.238388776779175  _id:  "10227000"
25listing_url: "https://www.airbnb.com/rooms/10227000"
26name: "LAHAINA, MAUI! RESORT/CONDO BEACHFRONT!! SLEEPS 4!"
27summary: "THIS IS A VERY SPACIOUS 1 BEDROOM FULL CONDO (SLEEPS 4) AT THE BEAUTIF…"
28...
29property_type: "Condominium"
30...
31address: Object
32    street: "Lahaina, HI, United States"
33    suburb: "Maui"
34    government_area: "Lahaina"
35    market: "Maui"
36    country: "United States"
37    country_code: "US"
38    location: Object
39    type: "Point"
40    coordinates: Array
41        0: -156.68012
42        1: 20.96996
43    is_location_exact: true
44...
45
46SCORE: 2.238388776779175  _id:  "10266175"
47listing_url: "https://www.airbnb.com/rooms/10266175"
48name: "Makaha Valley Paradise with OceanView"
49summary: "A beautiful and comfortable 1 Bedroom Air Conditioned Condo in Makaha …"
50...
51property_type: "Condominium"
52...
53address: Object
54    street: "Waianae, HI, United States"
55    suburb: "Leeward Side"
56    government_area: "Waianae"
57    market: "Oahu"
58    country: "United States"
59    country_code: "US"
60    location: Object
61    type: "Point"
62    coordinates: Array
63        0: -158.20291
64        1: 21.4818
65    is_location_exact: true
66...
67
68SCORE: 2.238388776779175  _id:  "1042446"
69listing_url: "https://www.airbnb.com/rooms/1042446"
70name: "March 2019 availability! Oceanview on Sugar Beach!"
71summary: ""
72...
73property_type: "Condominium"
74...
75address: Object
76    street: "Kihei, HI, United States"
77    suburb: "Maui"
78    government_area: "Kihei-Makena"
79    market: "Maui"
80    country: "United States"
81    country_code: "US"
82    location: Object
83    type: "Point"
84    coordinates: Array
85        0: -156.46881
86        1: 20.78621
87    is_location_exact: true
88...
89
90SCORE: 2.238388776779175  _id:  "10527243"
91listing_url: "https://www.airbnb.com/rooms/10527243"
92name: "Tropical Jungle Oasis"
93summary: "2 bedrooms, one with a queen sized bed, one with 2 single beds. 1 and …"
94...
95property_type: "Condominium"
96...
97address: Object
98    street: "Hilo, HI, United States"
99    suburb: "Island of Hawaiʻi"
100    government_area: "South Hilo"
101    market: "The Big Island"
102    country: "United States"
103    country_code: "US"
104    location: Object
105    type: "Point"
106    coordinates: Array
107        0: -155.09259
108        1: 19.73108
109    is_location_exact: true
110...
111
112SCORE: 2.238388776779175  _id:  "1104768"
113listing_url: "https://www.airbnb.com/rooms/1104768"
114name: "2 Bdrm/2 Bath  Family Suite Ocean View"
115summary: "This breathtaking 180 degree view of Waikiki is one of a kind. You wil…"
116...
117property_type: "Condominium"
118...
119address: Object
120    street: "Honolulu, HI, United States"
121    suburb: "Waikiki"
122    government_area: "Primary Urban Center"
123    market: "Oahu"
124    country: "United States"
125    country_code: "US"
126    location: Object
127    type: "Point"
128    coordinates: Array
129        0: -157.82696
130        1: 21.27971
131    is_location_exact: true
132...
133
134SCORE: 2.238388776779175  _id:  "11207193"
135listing_url: "https://www.airbnb.com/rooms/11207193"
136name: "302 Kanai A Nalu Ocean front/view"
137summary: "Welcome to Kana'i A Nalu a quiet resort that sits on the ocean away fr…"
138...
139property_type: "Condominium"
140...
141address: Object
142    street: "Wailuku, HI, United States"
143    suburb: "Maui"
144    government_area: "Kihei-Makena"
145    market: "Maui"
146    country: "United States"
147    country_code: "US"
148    location: Object
149    type: "Point"
150    coordinates: Array
151        0: -156.5039
152        1: 20.79664
153    is_location_exact: true
154...
155
156SCORE: 2.238388776779175  _id:  "11319047"
157listing_url: "https://www.airbnb.com/rooms/11319047"
158name: "Sugar Beach Resort 1BR Ground Floor Condo !"
159summary: "The Sugar Beach Resort enjoys a beachfront setting fit for a postcard."
160...
161property_type: "Condominium"
162...
163address: Object
164    street: "Kihei, HI, United States"
165    suburb: "Maui"
166    government_area: "Kihei-Makena"
167    market: "Maui"
168    country: "United States"
169    country_code: "US"
170    location: Object
171    type: "Point"
172    coordinates: Array
173        0: -156.46697
174        1: 20.78484
175    is_location_exact: true
176...
177
178SCORE: 2.238388776779175  _id:  "11695887"
179listing_url: "https://www.airbnb.com/rooms/11695887"
180name: "2 BR Oceanview - Great Location!"
181summary: "Location, location, location... This is a great 2 bed, 2 bath condo is…"
182...
183property_type: "Condominium"
184...
185address: Object
186    street: "Kihei, HI, United States"
187    suburb: "Kihei/Wailea"
188    government_area: "Kihei-Makena"
189    market: "Maui"
190    country: "United States"
191    country_code: "US"
192    location: Object
193    type: "Point"
194    coordinates: Array
195        0: -156.44917
196        1: 20.73013
197    is_location_exact: true
198...
199
200SCORE: 2.238388776779175  _id:  "11817249"
201listing_url: "https://www.airbnb.com/rooms/11817249"
202name: "PALMS AT WAILEA #905-2BR-REMODELED-LARGE LANAI-AC"
203summary: "Book with confidence this stunning 2 bedroom, 2 bathroom condo at the …"
204...
205property_type: "Condominium"
206...
207address: Object
208    street: "Kihei, HI, United States"
209    suburb: "Maui"
210    government_area: "Kihei-Makena"
211    market: "Maui"
212    country: "United States"
213    country_code: "US"
214    location: Object
215    type: "Point"
216    coordinates: Array
217        0: -156.4409
218        1: 20.69735
219    is_location_exact: true
220...
db.listingsAndReviews.aggregate([
    {
      "$search": {
        "index": "<INDEX-NAME>",
        "compound": {
          "must": [{
            "geoWithin": {
              "geometry": {
                "type": "Polygon",
                "coordinates": [[[ -161.323242, 22.512557 ],
                              [ -152.446289, 22.065278 ],
                              [ -156.09375, 17.811456 ],
                              [ -161.323242, 22.512557 ]]]
              },
              "path": "address.location"
            }
          }],
          "should": [{
            "text": {
              "path": "property_type",
              "query": "Condominium"
            }
          }]
        }
      }
    },
    {
      "$limit": 10
    },
    {
      $project: {
        "_id": 0,
        "name": 1,
        "address": 1,
        "property_type": 1,
        score: { $meta: "searchScore" }
      }
    }
])
<<<<<<<< HEAD:source/includes/fts/geo/procedures/steps-fts-tutorial-run-geo-query-compass.yaml
stepnum: 1
title: "Connect to your cluster in |compass|."
ref: connect-to-database-deployment-fts-compass
content: |
  Open |compass| and
  connect to your {+cluster+}. For detailed instructions on connecting,
  see :ref:`atlas-connect-via-compass`.
---
stepnum: 2
title: "Use the ``listingsAndReviews`` collection in the ``sample_airbnb`` database."
ref: use-sample-airbnb-compass
content: |
  On the :guilabel:`Database` screen, click the ``sample_airbnb``
  database, then click the ``listingsAndReviews`` collection.
---
stepnum: 3
title: "Run an |fts| query on the ``listingsAndReviews`` collection."
ref: run-geo-query-compass
content: |
  The following query:
  .. include:: /includes/fts/facts/fact-fts-tutorial-run-geo-query-results.rst
  To run this |fts| query in |compass|:
  a. Click the :guilabel:`Aggregations` tab.
  #. Click :guilabel:`Select...`, then configure each of the following 
     pipeline stages by selecting the stage from the dropdown and adding
     the query for that stage. Click :guilabel:`Add Stage` to add 
     additional stages.
     .. list-table::
        :header-rows: 1
        :widths: 25 75
        * - Pipeline Stage
          - Query
        * - ``$search``
          - .. code-block:: javascript
               {
                   'index': 'geo-json-tutorial',
                   'compound': {
                     'must': [
                       {
                         'geoWithin': {
                           'geometry': {
                             'type': 'Polygon', 
                             'coordinates': [
                               [
                                 [
                                   -161.323242, 22.512557
                                 ], [
                                   -152.446289, 22.065278
                                 ], [
                                   -156.09375, 17.811456
                                 ], [
                                   -161.323242, 22.512557
                                 ]
                               ]
                             ]
                           }, 
                           'path': 'address.location'
                         }
                       }
                     ], 
                     'should': [
                       {
                         'text': {
                           'path': 'property_type', 
                           'query': 'Condominium'
                         }
                       }
                     ]
                   }
               }
        * - ``$limit``
          - .. code-block:: javascript
               10
        * - ``$project``
          - .. code-block:: javascript
               {
                '_id': 0, 
                'name': 1, 
                'address': 1, 
                'property_type': 1, 
                'score': {
                  '$meta': 'searchScore'
                }
               }
  If you enabled :guilabel:`Auto Preview`, |compass| displays the 
  following documents next to the ``$project``
  pipeline stage:
  .. code-block:: json
     :copyable: false
     :linenos:
     {
========
[
    {
>>>>>>>> 44b896764 (DOCSP-47238 Performance Options reference section + tutorial example migration):source/includes/fts/geo/shell-query-output.js
       name: 'Ocean View Waikiki Marina w/prkg',
       property_type: 'Condominium',
       address: {
         street: 'Honolulu, HI, United States',
         suburb: 'Oʻahu',
         government_area: 'Primary Urban Center',
         market: 'Oahu',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -157.83919, 21.28634 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: 'LAHAINA, MAUI! RESORT/CONDO BEACHFRONT!! SLEEPS 4!',
       property_type: 'Condominium',
       address: {
         street: 'Lahaina, HI, United States',
         suburb: 'Maui',
         government_area: 'Lahaina',
         market: 'Maui',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -156.68012, 20.96996 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: 'Makaha Valley Paradise with OceanView',
       property_type: 'Condominium',
       address: {
         street: 'Waianae, HI, United States',
         suburb: 'Leeward Side',
         government_area: 'Waianae',
         market: 'Oahu',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -158.20291, 21.4818 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: 'March 2019 availability! Oceanview on Sugar Beach!',
       property_type: 'Condominium',
       address: {
         street: 'Kihei, HI, United States',
         suburb: 'Maui',
         government_area: 'Kihei-Makena',
         market: 'Maui',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -156.46881, 20.78621 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: 'Tropical Jungle Oasis',
       property_type: 'Condominium',
       address: {
         street: 'Hilo, HI, United States',
         suburb: 'Island of Hawaiʻi',
         government_area: 'South Hilo',
         market: 'The Big Island',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -155.09259, 19.73108 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: '2 Bdrm/2 Bath  Family Suite Ocean View',
       property_type: 'Condominium',
       address: {
         street: 'Honolulu, HI, United States',
         suburb: 'Waikiki',
         government_area: 'Primary Urban Center',
         market: 'Oahu',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -157.82696, 21.27971 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: '302 Kanai A Nalu Ocean front/view',
       property_type: 'Condominium',
       address: {
         street: 'Wailuku, HI, United States',
         suburb: 'Maui',
         government_area: 'Kihei-Makena',
         market: 'Maui',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -156.5039, 20.79664 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: 'Sugar Beach Resort 1BR Ground Floor Condo !',
       property_type: 'Condominium',
       address: {
         street: 'Kihei, HI, United States',
         suburb: 'Maui',
         government_area: 'Kihei-Makena',
         market: 'Maui',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -156.46697, 20.78484 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: '2 BR Oceanview - Great Location!',
       property_type: 'Condominium',
       address: {
         street: 'Kihei, HI, United States',
         suburb: 'Kihei/Wailea',
         government_area: 'Kihei-Makena',
         market: 'Maui',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -156.44917, 20.73013 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
     },
     {
       name: 'PALMS AT WAILEA #905-2BR-REMODELED-LARGE LANAI-AC',
       property_type: 'Condominium',
       address: {
         street: 'Kihei, HI, United States',
         suburb: 'Maui',
         government_area: 'Kihei-Makena',
         market: 'Maui',
         country: 'United States',
         country_code: 'US',
         location: {
           type: 'Point',
           coordinates: [ -156.4409, 20.69735 ],
           is_location_exact: true
         }
       },
       score: 2.238388776779175
    }
]

To learn how to run the following queries in the MongoDB Compass, see Define Your Query.

1using MongoDB.Bson;
2using MongoDB.Bson.IO;
3using MongoDB.Bson.Serialization;
4using MongoDB.Bson.Serialization.Attributes;
5using MongoDB.Bson.Serialization.Conventions;
6using MongoDB.Driver;
7using MongoDB.Driver.GeoJsonObjectModel;
8using MongoDB.Driver.Search;
9using System;
10
11public class GeoQuery 
12{
13    private const string MongoConnectionString = "<connection-string>";
14    
15    public static void Main(string[] args) 
16    {
17        // allow automapping of the camelCase database fields to our AirbnbDocument
18        var camelCaseConvention = new ConventionPack { new CamelCaseElementNameConvention() };
19        ConventionRegistry.Register("CamelCase", camelCaseConvention, type => true);
20
21        // connect to your Atlas cluster
22        var mongoClient = new MongoClient(MongoConnectionString);
23        var airbnbDatabase = mongoClient.GetDatabase("sample_airbnb");
24        var airbnbCollection = airbnbDatabase.GetCollection<AirbnbDocument>("listingsAndReviews");
25
26        // declare data for the compound query
27        string property_type = "Condominium";
28        var coordinates = new GeoJson2DCoordinates[]
29        {
30          new(-161.323242, 22.512557),
31          new(-152.446289, 22.065278),
32          new(-156.09375, 17.811456),
33          new(-161.323242, 22.512557)
34        };
35        var polygon = GeoJson.Polygon(coordinates);
36
37        // define and run pipeline
38        var results = airbnbCollection.Aggregate()
39            .Search(Builders<AirbnbDocument>.Search.Compound()
40                .Must(Builders<AirbnbDocument>.Search.GeoWithin(airbnb => airbnb.Address.Location, polygon))
41                .Should((Builders<AirbnbDocument>.Search.Text(airbnb => airbnb.PropertyType, property_type))),
42                indexName: "<INDEX-NAME>")
43            .Limit (10)
44            .Project<AirbnbDocument>(Builders<AirbnbDocument>.Projection
45                .Include(airbnb => airbnb.PropertyType)
46                .Include(airbnb => airbnb.Address.Location)
47                .Include(airbnb => airbnb.Name)
48                .Exclude(airbnb => airbnb.Id)
49                .MetaSearchScore(airbnb => airbnb.Score))
50            .ToList();
51
52        // print results
53        foreach (var x in results) {
54            Console.WriteLine(x.ToJson());
55        }
56    }
57}
58[BsonIgnoreExtraElements]
59public class AirbnbDocument 
60{
61    [BsonIgnoreIfDefault]
62    public ObjectId Id { get; set; }
63    public String Name { get; set; }
64    [BsonElement("property_type")] 
65    public string PropertyType { get; set; }
66    public Address Address { get; set; }
67    public double Score { get; set; }
68}
69[BsonIgnoreExtraElements]
70public class Address 
71{
72    public GeoJsonPoint<GeoJson2DCoordinates> Location { get; set; }
73}
{ 
    "name" : "Ocean View Waikiki Marina w/prkg", 
    "property_type" : "Condominium", 
    "address" : { 
      "location" : { 
        "type" : "Point",
        "coordinates" : [-157.83919, 21.286339999999999],
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "LAHAINA, MAUI! RESORT/CONDO BEACHFRONT!! SLEEPS 4!", 
    "property_type" : "Condominium", 
    "address" : { 
      "location" : { 
        "type" : "Point", 
        "coordinates" : [-156.68011999999999, 20.96996], 
        "is_location_exact" : true 
      }
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "Makaha Valley Paradise with OceanView",
    "property_type" : "Condominium", 
    "address" : { 
      "location" : {
        "type" : "Point", 
        "coordinates" : [-158.20291, 21.4818],
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "March 2019 availability! Oceanview on Sugar Beach!",
    "property_type" : "Condominium", 
    "address" : { 
      "location" : {
        "type" : "Point", 
        "coordinates" : [-156.46880999999999, 20.786210000000001], 
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "Tropical Jungle Oasis", 
    "property_type" : "Condominium", 
    "address" : { 
      "location" : { 
        "type" : "Point",
        "coordinates" : [-155.09259, 19.731079999999999],
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "2 Bdrm/2 Bath  Family Suite Ocean View",
    "property_type" : "Condominium", 
    "address" : { 
      "location" : {
        "type" : "Point", 
        "coordinates" : [-157.82696000000001, 21.279710000000001], 
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "302 Kanai A Nalu Ocean front/view", 
    "property_type" : "Condominium", 
    "address" : { 
      "location" : { 
        "type" : "Point",
        "coordinates" : [-156.50389999999999, 20.79664],
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "Sugar Beach Resort 1BR Ground Floor Condo !",
    "property_type" : "Condominium", 
    "address" : { 
      "location" : {
        "type" : "Point", 
        "coordinates" : [-156.46697, 20.784839999999999], 
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "2 BR Oceanview - Great Location!", 
    "property_type" : "Condominium", 
    "address" : { 
      "location" : { 
        "type" : "Point",
        "coordinates" : [-156.44917000000001, 20.730129999999999],
        "is_location_exact" : true 
      } 
    },
    "score" : 2.2383887767791748
}
{ 
    "name" : "PALMS AT WAILEA #905-2BR-REMODELED-LARGE LANAI-AC",
    "property_type" : "Condominium", 
    "address" : { 
      "location" : {
        "type" : "Point", 
        "coordinates" : [-156.4409, 20.69735],
        "is_location_exact" : true 
      }
    }, 
    "score" : 2.2383887767791748  
}
1package main
2
3import (
4	"context"
5	"fmt"
6
7	"go.mongodb.org/mongo-driver/v2/bson"
8	"go.mongodb.org/mongo-driver/v2/mongo"
9	"go.mongodb.org/mongo-driver/v2/mongo/options"
10)
11
12func main() {
13	// connect to your Atlas cluster
14	client, err := mongo.Connect(options.Client().ApplyURI("<connection-string>"))
15	if err != nil {
16		panic(err)
17	}
18	defer client.Disconnect(context.TODO())
19
20	// set namespace
21	collection := client.Database("sample_airbnb").Collection("listingsAndReviews")
22
23	// define polygon
24	polygon := [][][]float64{{
25		{-161.323242, 22.512557},
26		{-152.446289, 22.065278},
27		{-156.09375, 17.811456},
28		{-161.323242, 22.512557},
29	}}
30
31	// define pipeline
32	searchStage := bson.D{{"$search", bson.M{
33		"index": "<INDEX-NAME>",
34		"compound": bson.M{
35			"must": bson.M{
36				"geoWithin": bson.M{
37					"geometry": bson.M{
38						"type":        "Polygon",
39						"coordinates": polygon,
40					},
41					"path": "address.location",
42				},
43			},
44			"should": bson.M{
45				"text": bson.M{
46					"path":  "property_type",
47					"query": "Condominium",
48				}},
49		},
50	},
51	}}
52	limitStage := bson.D{{"$limit", 10}}
53	projectStage := bson.D{{"$project", bson.D{{"name", 1}, {"address", 1}, {"property_type", 1}, {"_id", 0}, {"score", bson.D{{"$meta", "searchScore"}}}}}}
54
55	// run pipeline
56	cursor, err := collection.Aggregate(context.TODO(), mongo.Pipeline{searchStage, limitStage, projectStage})
57	if err != nil {
58		panic(err)
59	}
60
61	// print results
62	var results []bson.D
63	if err = cursor.All(context.TODO(), &results); err != nil {
64		panic(err)
65	}
66	for _, result := range results {
67		fmt.Println(result)
68	}
69}
package main
import (
	"context"
	"fmt"
	"go.mongodb.org/mongo-driver/v2/bson"
	"go.mongodb.org/mongo-driver/v2/mongo"
	"go.mongodb.org/mongo-driver/v2/mongo/options"
)
func main() {
	// connect to your Atlas cluster
	client, err := mongo.Connect(options.Client().ApplyURI("<connection-string>"))
	if err != nil {
		panic(err)
	}
	defer client.Disconnect(context.TODO())
	// set namespace
	collection := client.Database("sample_airbnb").Collection("listingsAndReviews")
	// define polygon
	polygon := [][][]float64{{
		{-161.323242, 22.512557},
		{-152.446289, 22.065278},
		{-156.09375, 17.811456},
		{-161.323242, 22.512557},
	}}
	// define pipeline
	searchStage := bson.D{{"$search", bson.M{
		"index": "<INDEX-NAME>",
		"compound": bson.M{
			"must": bson.M{
				"geoWithin": bson.M{
					"geometry": bson.M{
						"type":        "Polygon",
						"coordinates": polygon,
					},
					"path": "address.location",
				},
			},
			"should": bson.M{
				"text": bson.M{
					"path":  "property_type",
					"query": "Condominium",
				}},
		},
	},
	}}
	limitStage := bson.D{{"$limit", 10}}
	projectStage := bson.D{{"$project", bson.D{{"name", 1}, {"address", 1}, {"property_type", 1}, {"_id", 0}, {"score", bson.D{{"$meta", "searchScore"}}}}}}
	// run pipeline
	cursor, err := collection.Aggregate(context.TODO(), mongo.Pipeline{searchStage, limitStage, projectStage})
	if err != nil {
		panic(err)
	}
	// print results
	var results []bson.D
	if err = cursor.All(context.TODO(), &results); err != nil {
		panic(err)
	}
	for _, result := range results {
		fmt.Println(result)
	}
}
1import java.util.Arrays;
2import static com.mongodb.client.model.Filters.eq;
3import static com.mongodb.client.model.Aggregates.limit;
4import static com.mongodb.client.model.Aggregates.project;
5import static com.mongodb.client.model.Projections.computed;
6import static com.mongodb.client.model.Projections.excludeId;
7import static com.mongodb.client.model.Projections.fields;
8import static com.mongodb.client.model.Projections.include;
9import com.mongodb.client.MongoClient;
10import com.mongodb.client.MongoClients;
11import com.mongodb.client.MongoCollection;
12import com.mongodb.client.MongoDatabase;
13import org.bson.Document;
14
15public class GeoQuery {
16        public static void main( String[] args ) {
17                Document agg = new Document( "$search",
18                new Document( "index", "<INDEX-NAME>")
19                .append("compound",
20                    new Document("must", Arrays.asList(new Document("geoWithin", 
21                    new Document("geometry", 
22                        new Document("type", "Polygon")
23                            .append("coordinates", Arrays.asList(Arrays.asList(Arrays.asList(-161.323242d, 22.512557d), Arrays.asList(-152.446289d, 22.065278d), Arrays.asList(-156.09375d, 17.811456d), Arrays.asList(-161.323242d, 22.512557d)))))
24                            .append("path", "address.location"))))
25                .append("should", Arrays.asList(new Document("text", 
26                    new Document("path", "property_type")
27                        .append("query", "Condominium"))))));
28        
29                String uri = "<connection-string>";
30
31                try (MongoClient mongoClient = MongoClients.create(uri)) {
32                        MongoDatabase database = mongoClient.getDatabase("sample_airbnb");
33                        MongoCollection<Document> collection = database.getCollection("listingsAndReviews");
34                                        
35                        collection.aggregate(Arrays.asList(agg, 
36                            limit(10), 
37                            project(fields(excludeId(), include("name", "address", "property_type"), computed("score", new Document("$meta", "searchScore"))))))
38                            .forEach(doc -> System.out.println(doc.toJson() + "\n"));    
39                }
40        }
41}

The following code example:

  • Imports mongodb packages and dependencies.

  • Establishes a connection to your Atlas cluster.

  • Prints the documents that match the query from the AggregateFlow instance.

1import com.mongodb.client.model.Aggregates.limit
2import com.mongodb.client.model.Aggregates.project
3import com.mongodb.client.model.Projections.*
4import com.mongodb.kotlin.client.coroutine.MongoClient
5import kotlinx.coroutines.runBlocking
6import org.bson.Document
7
8fun main() {
9    // connect to your Atlas cluster
10    val uri = "<connection-string>"
11    val mongoClient = MongoClient.create(uri)
12
13    // set namespace
14    val database = mongoClient.getDatabase("sample_airbnb")
15    val collection = database.getCollection<Document>("listingsAndReviews")
16
17    runBlocking {
18        // define pipeline
19        val agg = Document(
20            "\$search",
21            Document("index", "<INDEX-NAME>")
22                .append(
23                    "compound",
24                    Document(
25                        "must", listOf(
26                            Document(
27                                "geoWithin",
28                                Document(
29                                    "geometry",
30                                    Document("type", "Polygon")
31                                        .append(
32                                            "coordinates",
33                                            listOf(
34                                                listOf(
35                                                    listOf(-161.323242, 22.512557),
36                                                    listOf(-152.446289, 22.065278),
37                                                    listOf(-156.09375, 17.811456),
38                                                    listOf(-161.323242, 22.512557)
39                                                )
40                                            )
41                                        )
42                                )
43                                    .append("path", "address.location")
44                            )
45                        )
46                    )
47                        .append(
48                            "should", listOf(
49                                Document(
50                                    "text",
51                                    Document("path", "property_type")
52                                        .append("query", "Condominium")
53                                )
54                            )
55                        )
56                )
57        )
58        
59        // run pipeline and print results
60        val resultsFlow = collection.aggregate<Document>(
61            listOf(
62                agg,
63                limit(10),
64                project(fields(
65                    excludeId(),
66                    include("name", "address", "property_type"),
67                    computed("score", Document("\$meta", "searchScore"))
68                ))
69            )
70        )
71        resultsFlow.collect { println(it) }
72    }
73    mongoClient.close()
74}
Document{{name=Ocean View Waikiki Marina w/prkg, property_type=Condominium, address=Document{{street=Honolulu, HI, United States, suburb=Oʻahu, government_area=Primary Urban Center, market=Oahu, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-157.83919, 21.28634], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=LAHAINA, MAUI! RESORT/CONDO BEACHFRONT!! SLEEPS 4!, property_type=Condominium, address=Document{{street=Lahaina, HI, United States, suburb=Maui, government_area=Lahaina, market=Maui, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-156.68012, 20.96996], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=Makaha Valley Paradise with OceanView, property_type=Condominium, address=Document{{street=Waianae, HI, United States, suburb=Leeward Side, government_area=Waianae, market=Oahu, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-158.20291, 21.4818], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=March 2019 availability! Oceanview on Sugar Beach!, property_type=Condominium, address=Document{{street=Kihei, HI, United States, suburb=Maui, government_area=Kihei-Makena, market=Maui, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-156.46881, 20.78621], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=Tropical Jungle Oasis, property_type=Condominium, address=Document{{street=Hilo, HI, United States, suburb=Island of Hawaiʻi, government_area=South Hilo, market=The Big Island, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-155.09259, 19.73108], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=2 Bdrm/2 Bath  Family Suite Ocean View, property_type=Condominium, address=Document{{street=Honolulu, HI, United States, suburb=Waikiki, government_area=Primary Urban Center, market=Oahu, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-157.82696, 21.27971], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=302 Kanai A Nalu Ocean front/view, property_type=Condominium, address=Document{{street=Wailuku, HI, United States, suburb=Maui, government_area=Kihei-Makena, market=Maui, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-156.5039, 20.79664], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=Sugar Beach Resort 1BR Ground Floor Condo !, property_type=Condominium, address=Document{{street=Kihei, HI, United States, suburb=Maui, government_area=Kihei-Makena, market=Maui, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-156.46697, 20.78484], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=2 BR Oceanview - Great Location!, property_type=Condominium, address=Document{{street=Kihei, HI, United States, suburb=Kihei/Wailea, government_area=Kihei-Makena, market=Maui, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-156.44917, 20.73013], is_location_exact=true}}}}, score=2.238388776779175}}
Document{{name=PALMS AT WAILEA #905-2BR-REMODELED-LARGE LANAI-AC, property_type=Condominium, address=Document{{street=Kihei, HI, United States, suburb=Maui, government_area=Kihei-Makena, market=Maui, country=United States, country_code=US, location=Document{{type=Point, coordinates=[-156.4409, 20.69735], is_location_exact=true}}}}, score=2.238388776779175}}

The following code example:

  • Imports mongodb, MongoDB's Node.js driver.

  • Creates an instance of the MongoClient class to establish a connection to your Atlas cluster.

  • Iterates over the cursor to print the documents that match the query.

1const { MongoClient } = require("mongodb");
2
3// connect to your Atlas cluster
4const uri ="<connection-string>";
5
6const client = new MongoClient(uri);
7
8async function run() {
9    try {
10        await client.connect();
11
12        // set namespace
13        const database = client.db("sample_airbnb");
14        const coll = database.collection("listingsAndReviews");
15
16        // define pipeline
17        const agg = [
18            {
19              '$search': {
20                'index': '<INDEX-NAME>',
21                'compound': {
22                  'must': [
23                    {
24                      'geoWithin': {
25                        'geometry': {
26                          'type': 'Polygon', 
27                          'coordinates': [
28                            [
29                              [
30                                -161.323242, 22.512557
31                              ], [
32                                -152.446289, 22.065278
33                              ], [
34                                -156.09375, 17.811456
35                              ], [
36                                -161.323242, 22.512557
37                              ]
38                            ]
39                          ]
40                        }, 
41                        'path': 'address.location'
42                      }
43                    }
44                  ], 
45                  'should': [
46                    {
47                      'text': {
48                        'path': 'property_type', 
49                        'query': 'Condominium'
50                      }
51                    }
52                  ]
53                }
54              }
55            }, {
56              '$limit': 10
57            }, {
58              '$project': {
59                '_id': 0, 
60                'name': 1, 
61                'address': 1, 
62                'property_type': 1, 
63                'score': {
64                  '$meta': 'searchScore'
65                }
66              }
67            }
68          ];
69        // run pipeline
70        const result = await coll.aggregate(agg);
71
72        // print results
73        await result.forEach((doc) => console.log(doc));
74    } finally {
75        await client.close();
76    }
77}
78run().catch(console.dir);

The following code example:

  • Imports pymongo, MongoDB's Python driver, and the dns module, which is required to connect pymongo to Atlas using a DNS seed list connection string.

  • Creates an instance of the MongoClient class to establish a connection to your Atlas cluster.

    • Uses a compound $search stage to:

      • Specify that results must be within a Polygon defined by a set of coordinates.

      • Give preference to results for properties of type condominium.

    • Uses a $project stage to:

      • Exclude all fields except name, address and property_type.

      • Add a relevance score to each returned document.

  • Iterates over the cursor to print the documents that match the query.

1import pymongo
2
3# connect to your Atlas cluster
4client = pymongo.MongoClient('<connection-string>')
5
6# define pipeline
7pipeline = [
8    {
9        '$search': {
10            'index': '<INDEX-NAME>',
11            'compound': {
12                'must': [
13                    {
14                        'geoWithin': {
15                            'geometry': {
16                                'type': 'Polygon', 
17                                'coordinates': [
18                                    [
19                                        [
20                                            -161.323242, 22.512557
21                                        ], [
22                                            -152.446289, 22.065278
23                                        ], [
24                                            -156.09375, 17.811456
25                                        ], [
26                                            -161.323242, 22.512557
27                                        ]
28                                    ]
29                                ]
30                            }, 
31                            'path': 'address.location'
32                        }
33                    }
34                ], 
35                'should': [
36                    {
37                        'text': {
38                            'path': 'property_type', 
39                            'query': 'Condominium'
40                        }
41                    }
42                ]
43            }
44        }
45    }, {
46        '$limit': 10
47    }, {
48        '$project': {
49            '_id': 0, 
50            'name': 1, 
51            'address': 1, 
52            'property_type': 1, 
53            'score': {
54                '$meta': 'searchScore'
55            }
56        }
57    }
58]
59# run pipeline
60result = client["sample_airbnb"]["listingsAndReviews"].aggregate(pipeline)
61
62# print results
63for i in result:
64    print(i)
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Primary Urban Center",
        "location": {
            "coordinates": [
                -157.83919,
                21.28634
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Oahu",
        "street": "Honolulu, HI, United States",
        "suburb": "O\u02bbahu"
    },
    "name": "Ocean View Waikiki Marina w/prkg",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Lahaina",
        "location": {
            "coordinates": [
                -156.68012,
                20.96996
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Maui",
        "street": "Lahaina, HI, United States",
        "suburb": "Maui"
    },
    "name": "LAHAINA, MAUI! RESORT/CONDO BEACHFRONT!! SLEEPS 4!",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Waianae",
        "location": {
            "coordinates": [
                -158.20291,
                21.4818
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Oahu",
        "street": "Waianae, HI, United States",
        "suburb": "Leeward Side"
    },
    "name": "Makaha Valley Paradise with OceanView",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Kihei-Makena",
        "location": {
            "coordinates": [
                -156.46881,
                20.78621
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Maui",
        "street": "Kihei, HI, United States",
        "suburb": "Maui"
    },
    "name": "March 2019 availability! Oceanview on Sugar Beach!",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "South Hilo",
        "location": {
            "coordinates": [
                -155.09259,
                19.73108
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "The Big Island",
        "street": "Hilo, HI, United States",
        "suburb": "Island of Hawai\u02bbi"
    },
    "name": "Tropical Jungle Oasis",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Primary Urban Center",
        "location": {
            "coordinates": [
                -157.82696,
                21.27971
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Oahu",
        "street": "Honolulu, HI, United States",
        "suburb": "Waikiki"
    },
    "name": "2 Bdrm/2 Bath  Family Suite Ocean View",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Kihei-Makena",
        "location": {
            "coordinates": [
                -156.5039,
                20.79664
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Maui",
        "street": "Wailuku, HI, United States",
        "suburb": "Maui"
    },
    "name": "302 Kanai A Nalu Ocean front/view",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Kihei-Makena",
        "location": {
            "coordinates": [
                -156.46697,
                20.78484
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Maui",
        "street": "Kihei, HI, United States",
        "suburb": "Maui"
    },
    "name": "Sugar Beach Resort 1BR Ground Floor Condo !",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Kihei-Makena",
        "location": {
            "coordinates": [
                -156.44917,
                20.73013
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Maui",
        "street": "Kihei, HI, United States",
        "suburb": "Kihei/Wailea"
    },
    "name": "2 BR Oceanview - Great Location!",
    "property_type": "Condominium",
    "score": 2.238388776779175
}
{
    "address": {
        "country": "United States",
        "country_code": "US",
        "government_area": "Kihei-Makena",
        "location": {
            "coordinates": [
                -156.4409,
                20.69735
            ],
            "is_location_exact": true,
            "type": "Point"
        },
        "market": "Maui",
        "street": "Kihei, HI, United States",
        "suburb": "Maui"
    },
    "name": "PALMS AT WAILEA #905-2BR-REMODELED-LARGE LANAI-AC",
    "property_type": "Condominium",
    "score": 2.238388776779175
}

The following examples use the geoWithin operator with the geometry field to search for properties in Hawaii. The type field specifies whether the area is a GeoJSON Polygon or MultiPolygon.

The query includes a:

  • $limit stage to limit the output to 3 results.

  • $project stage to exclude all fields except name and address.

Note

You don't need to specify indexes named default in your Atlas Search query. If your index has any other name, you must specify the index field.

1.. input::
2   :language: json
3   :linenos:
4
5   db.listingsAndReviews.aggregate([
6     {
7       "$search": {
8         "geoWithin": {
9           "geometry": {
10             "type": "MultiPolygon",
11             "coordinates": [
12                   [[[-157.8412413882,21.2882235819],
13                   [-157.8607925468,21.2962046205],
14                   [-157.8646640634,21.3077019651],
15                   [-157.862776699,21.320776283],
16                   [-157.8341758705,21.3133826738],
17                   [-157.8349985678,21.3000822569],
18                   [-157.8412413882,21.2882235819]]],
19                   [[[-157.852898124,21.301208833],
20                   [-157.8580050499,21.3050871833],
21                   [-157.8587346108,21.3098050385],
22                   [-157.8508811028,21.3119240258],
23                   [-157.8454308541,21.30396767],
24                   [-157.852898124,21.301208833]]]
25             ]
26           },
27           "path": "address.location"
28         }
29       }
30     },
31     {
32       $limit: 3
33     },
34     {
35       $project: {
36         "_id": 0,
37         "name": 1,
38         "address": 1
39       }
40     }
41   ])
42
43.. output::
44   :language: javascript
45   :visible: false
46
47   {
48       "name" : "Heart of Honolulu, 2BD gem! Free Garage Parking!",
49       "address" : {
50         "street" : "Honolulu, HI, United States",
51         "suburb" : "Makiki/Lower Punchbowl/Tantalus",
52         "government_area" : "Primary Urban Center",
53         "market" : "Oahu",
54         "country" : "United States",
55         "country_code" : "US",
56         "location" : {
57           "type" : "Point",
58           "coordinates" : [ -157.84343, 21.30852 ],
59           "is_location_exact" : false
60         }
61       }
62     }
63     {
64       "name" : "Private Studio closed to town w/ compact parking",
65       "address" : {
66         "street" : "Honolulu, HI, United States",
67         "suburb" : "Oʻahu",
68         "government_area" : "Primary Urban Center",
69         "market" : "Oahu",
70         "country" : "United States",
71         "country_code" : "US",
72         "location" : {
73           "type" : "Point",
74           "coordinates" : [ -157.85228, 21.31184 ],
75           "is_location_exact" : true
76         }
77       }
78     }
79     {
80       "name" : "Comfortable Room (2) at Affordable Rates",
81       "address" : {
82         "street" : "Honolulu, HI, United States",
83         "suburb" : "Oʻahu",
84         "government_area" : "Primary Urban Center",
85         "market" : "Oahu",
86         "country" : "United States",
87         "country_code" : "US",
88         "location" : {
89           "type" : "Point",
90           "coordinates" : [ -157.83889, 21.29776 ],
91           "is_location_exact" : false
92         }
93       }
94     }

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