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2. Use Operators & Collectors

geoWithin

On this page

  • Definition
  • Syntax
  • Options
  • Examples
  • box Example
  • circle Example
  • geometry Examples

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. See Path Construction.
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.

Tip

If you've already loaded the sample dataset, follow the Get Started with Atlas Search tutorial to create an index definition and run Atlas Search queries.

You can use any of the following sample datasets for running Atlas Search queries with the geoWithin operator:

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    }
13  }
14}

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.

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])

The query returns the following results:

1{
2  "name" : "Surry Hills Studio - Your Perfect Base in Sydney",
3  "address" : {
4    "street" : "Surry Hills, NSW, Australia",
5    "suburb" : "Darlinghurst",
6    "government_area" : "Sydney",
7    "market" : "Sydney",
8    "country" : "Australia",
9    "country_code" : "AU",
10    "location" : {
11      "type" : "Point",
12      "coordinates" : [ 151.21554, -33.88029 ],
13      "is_location_exact" : true
14    }
15  }
16}
17{
18  "name" : "Sydney Hyde Park City Apartment (checkin from 6am)",
19  "address" : {
20    "street" : "Darlinghurst, NSW, Australia",
21    "suburb" : "Darlinghurst",
22    "government_area" : "Sydney",
23    "market" : "Sydney",
24    "country" : "Australia",
25    "country_code" : "AU",
26    "location" : {
27      "type" : "Point",
28      "coordinates" : [ 151.21346, -33.87603 ],
29      "is_location_exact" : false
30    }
31  }
32}
33{
34  "name" : "THE Place to See Sydney's FIREWORKS",
35  "address" : {
36    "street" : "Rozelle, NSW, Australia",
37    "suburb" : "Lilyfield/Rozelle",
38    "government_area" : "Leichhardt",
39    "market" : "Sydney",
40    "country" : "Australia",
41    "country_code" : "AU",
42    "location" : {
43      "type" : "Point",
44      "coordinates" : [ 151.17956, -33.86296 ],
45      "is_location_exact" : true
46    }
47  }
48}

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])

The query returns the following results:

1{
2  "name" : "Ligne verte - à 15 min de métro du centre ville.",
3  "address" : {
4    "street" : "Montréal, Québec, Canada",
5    "suburb" : "Hochelaga-Maisonneuve",
6    "government_area" : "Mercier-Hochelaga-Maisonneuve",
7    "market" : "Montreal",
8    "country" : "Canada",
9    "country_code" : "CA",
10    "location" : {
11      "type" : "Point",
12      "coordinates" : [ -73.54949, 45.54548 ],
13      "is_location_exact" : false
14    }
15  }
16}
17{
18  "name" : "Belle chambre à côté Metro Papineau",
19  "address" : {
20    "street" : "Montréal, QC, Canada",
21    "suburb" : "Gay Village",
22    "government_area" : "Ville-Marie",
23    "market" : "Montreal",
24    "country" : "Canada",
25    "country_code" : "CA",
26    "location" : {
27      "type" : "Point",
28      "coordinates" : [ -73.54985, 45.52797 ],
29      "is_location_exact" : false
30    }
31  }
32}
33{
34  "name" : "L'IDÉAL, ( à 2 min du métro Pie-IX ).",
35  "address" : {
36    "street" : "Montréal, Québec, Canada",
37    "suburb" : "Mercier-Hochelaga-Maisonneuve",
38    "government_area" : "Mercier-Hochelaga-Maisonneuve",
39    "market" : "Montreal",
40    "country" : "Canada",
41    "country_code" : "CA",
42    "location" : {
43      "type" : "Point",
44      "coordinates" : [ -73.55208, 45.55157 ],
45      "is_location_exact" : true
46    }
47  }
48}

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.

1 db.listingsAndReviews.aggregate([
2   {
3     "$search": {
4       "geoWithin": {
5         "geometry": {
6           "type": "Polygon",
7           "coordinates": [[[ -161.323242, 22.512557 ],
8                          [ -152.446289, 22.065278 ],
9                          [ -156.09375, 17.811456 ],
10                          [ -161.323242, 22.512557 ]]]
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 ])

The query returns the following results:

1{
2  "name" : "Ocean View Waikiki Marina w/prkg",
3  "address" : {
4    "street" : "Honolulu, HI, United States",
5    "suburb" : "Oʻahu",
6    "government_area" : "Primary Urban Center",
7    "market" : "Oahu",
8    "country" : "United States",
9    "country_code" : "US",
10    "location" : {
11      "type" : "Point",
12      "coordinates" : [ -157.83919, 21.28634 ],
13      "is_location_exact" : true
14    }
15  }
16}
17{
18  "name" : "Kailua-Kona, Kona Coast II 2b condo",
19  "address" : {
20    "street" : "Kailua-Kona, HI, United States",
21    "suburb" : "Kailua/Kona",
22    "government_area" : "North Kona",
23    "market" : "The Big Island",
24    "country" : "United States",
25    "country_code" : "US",
26    "location" : {
27      "type" : "Point",
28      "coordinates" : [ -155.96445, 19.5702 ],
29      "is_location_exact" : true
30    }
31  }
32}
33{
34  "name" : "LAHAINA, MAUI! RESORT/CONDO BEACHFRONT!! SLEEPS 4!",
35  "address" : {
36    "street" : "Lahaina, HI, United States",
37    "suburb" : "Maui",
38    "government_area" : "Lahaina",
39    "market" : "Maui",
40    "country" : "United States",
41    "country_code" : "US",
42    "location" : {
43      "type" : "Point",
44      "coordinates" : [ -156.68012, 20.96996 ],
45      "is_location_exact" : true
46    }
47  }
48}
1db.listingsAndReviews.aggregate([
2  {
3    "$search": {
4      "geoWithin": {
5        "geometry": {
6          "type": "MultiPolygon",
7          "coordinates": [
8                [[[-157.8412413882,21.2882235819],
9                [-157.8607925468,21.2962046205],
10                [-157.8646640634,21.3077019651],
11                [-157.862776699,21.320776283],
12                [-157.8341758705,21.3133826738],
13                [-157.8349985678,21.3000822569],
14                [-157.8412413882,21.2882235819]]],
15                [[[-157.852898124,21.301208833],
16                [-157.8580050499,21.3050871833],
17                [-157.8587346108,21.3098050385],
18                [-157.8508811028,21.3119240258],
19                [-157.8454308541,21.30396767],
20                [-157.852898124,21.301208833]]]
21          ]
22        },
23        "path": "address.location"
24      }
25    }
26  },
27  {
28    $limit: 3
29  },
30  {
31    $project: {
32      "_id": 0,
33      "name": 1,
34      "address": 1
35    }
36  }
37])

The query returns the following results:

1{
2  "name" : "Heart of Honolulu, 2BD gem! Free Garage Parking!",
3  "address" : {
4    "street" : "Honolulu, HI, United States",
5    "suburb" : "Makiki/Lower Punchbowl/Tantalus",
6    "government_area" : "Primary Urban Center",
7    "market" : "Oahu",
8    "country" : "United States",
9    "country_code" : "US",
10    "location" : {
11      "type" : "Point",
12      "coordinates" : [ -157.84343, 21.30852 ],
13      "is_location_exact" : false
14    }
15  }
16}
17{
18  "name" : "Private Studio closed to town w/ compact parking",
19  "address" : {
20    "street" : "Honolulu, HI, United States",
21    "suburb" : "Oʻahu",
22    "government_area" : "Primary Urban Center",
23    "market" : "Oahu",
24    "country" : "United States",
25    "country_code" : "US",
26    "location" : {
27      "type" : "Point",
28      "coordinates" : [ -157.85228, 21.31184 ],
29      "is_location_exact" : true
30    }
31  }
32}
33{
34  "name" : "Comfortable Room (2) at Affordable Rates",
35  "address" : {
36    "street" : "Honolulu, HI, United States",
37    "suburb" : "Oʻahu",
38    "government_area" : "Primary Urban Center",
39    "market" : "Oahu",
40    "country" : "United States",
41    "country_code" : "US",
42    "location" : {
43      "type" : "Point",
44      "coordinates" : [ -157.83889, 21.29776 ],
45      "is_location_exact" : false
46    }
47  }
48}

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