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Search Geospatially
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Overview
You can query data based on geographical location using geospatial query operators. You can format geospatial queries using one of the following coordinate systems:
This section contains examples of geospatial queries using different query operators that you can run against your Atlas sample dataset.
Coordinates on an Earth-like Sphere
For geospatial queries using longitude and latitude coordinates on an Earth-like sphere, use the GeoJSON query format. While GeoJSON has multiple types, all GeoJSON data types use some form of the following structure:
<field> : { type: <GeoJSON type>, coordinates: [ [longitude_1, latitude_1], ... [longitude_n, latitude_n] ] }
The object type determines the number of coordinates. For instance, a
Point
requires only one coordinate: a longitude and a latitude.
A Line
uses two coordinates: a longitude and a latitude for each end.
A Polygon
consists of a list of coordinates in which the first and last
coordinate are the same, effectively closing the polygon. To learn more
about the GeoJSON shapes you can use in MongoDB, consult the
GeoJSON manual entry.
To enable querying GeoJSON data, you must add the field to a 2dsphere
index. The following snippet creates an index on the location.geo
field in
the theaters
collection using the createIndex()
method:
db.theaters.createIndex({location.geo: "2dsphere"})
Coordinates on a 2D Plane
You can also express geospatial queries using x
and y
coordinates in
a two-dimensional Euclidean plane. Until MongoDB, this was the only format
compatible with geospatial queries, and are now referred to as
"legacy coordinate pairs".
Legacy coordinate pairs use the following structure:
<field> : [ x, y ]
The field should contain an array of two values in which the first represents
the x
axis value and the second represents the y
axis value.
To enable querying using legacy coordinate pairs, create a 2d
index on
the field on the collection. The following snippet creates an index on the
coordinates
field in the shipwrecks
collection using the
createIndex()
method:
db.shipwrecks({coordinates: "2d"})
See the MongoDB server manual page on legacy coordinate pairs for more information.
Note
Spherical (2dsphere
) and flat (2d
) indexes support some, but
not all, of the same query operators. For a full list of operators
and their index compatibility, consult the
manual entry for geospatial queries.
Examples
The following examples use the MongoDB Atlas sample dataset. You can learn how to set up your own free-tier Atlas cluster and how to load the sample dataset in our quick start guide.
The examples use the theaters
collection in the sample_mflix
database
from the sample dataset. The theaters
collection contains a 2dsphere
index
on the location.geo
field.
Query by Proximity
The $near
operator accepts a set of longitude-latitude coordinates and returns
documents ordered from nearest to farthest. To limit the results to a
maximum distance in meters, use the $maxDistance
option. For a
complete list of options, see the reference documentation for $near
.
The following example queries for theaters within 10,000
meters of
[ -73.9667, 40.78 ]
.
const query = { "location.geo": { $near: { $geometry: { type: "Point", coordinates: [-73.9667, 40.78] }, $maxDistance: 10000, }, }, }; // find documents based on our query const cursor = theaters.find(query);
Query Within a Range
The $geoWithin operator selects documents with geospatial data that exist within a specified shape. The following example searches for movie theaters in the New England area:
const query = { "location.geo": { $geoWithin: { $geometry: { type: "Polygon", coordinates: [ [ [-72, 40], [-74, 41], [-72, 39], [-72, 40], ], ], }, }, }, }; // find documents based on our query const cursor = theaters.find(query);
See the MongoDB server manual page on geospatial query operators for more information on the operators you can use in your query.