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MongoDB GeoSpatial Feature
Hüseyin BABAL@huseyinbabal
What is MongoDB GeoSpatial Feature?
MongoDB allows you to create index and queries to make operations on geospatial
(location information) data
In order to define index, or execute query, you need to determine surface
first
Surfaces
Spherical
To calculate geometry over an Earth-like
sphere, store your location data on a
spherical surface and use 2dsphere
index.
MongoDB Reference
Store your location data as GeoJSON objects with this coordinate-axis order: longitude, latitude. The coordinate reference system for GeoJSON uses the WGS84 datum.
MongoDB Reference
GeoJSON
Example Usage
Example Usage
Flat
To calculate distances on a Euclidean plane, store your location data as legacy coordinate pairs and use a 2d index.
MongoDB Reference
Query Operations
Inclusion
MongoDB can query for locations contained entirely within a specified polygon. Inclusion queries use the $geoWithin operator. No index required, 2d and 2dsphere supports
MongoDB Reference
Intersection
MongoDB can query for locations that intersect with a specified geometry. These queries apply only to data on a spherical surface. These queries use the $geoIntersects operator. Index required, only 2dsphere supports
MongoDB Reference
Proximity
MongoDB can query for the points nearest to another point. Proximity queries use the $near operator. 2d or 2dsphere required
MongoDB Reference
Index Types
2d
● Calculations using flat geometry
● Legacy coordinate pairs (i.e.,
geospatial points on a flat coordinate
system)
● Compound indexes with only one
additional field, as a suffix of the 2d
index field
2d Index Creation
db.collection.createIndex( { <location field> : "2d" } ,
{ min : <lower bound> , max : <upper bound> } )
db.collection.createIndex( { loc : "2d" } ,
{ min : -45 , max : 45 } )
2d Query
db.<collection>.find( { <location field> :
{ $geoWithin :
{ $box|$polygon|$center : <coordinates>
} } } )
db.places.find( { loc :
{ $geoWithin :
{ $box : [ [ 0 , 0 ] ,
[ 100 , 100 ] ]
} } } )
db.places.find( { loc: { $geoWithin :
{ $center : [ [-74, 40.74 ] , 10 ]
} } } )
db.<collection>.find( { <location field> :
{ $near : [ <x> , <y> ]
} } )
db.<collection>.find( { loc: [ <x> , <y> ] } )
2dsphere Index Creation
db.collection.createIndex( { <location field> : "2dsphere" } )
db.collection.createIndex( { loc : "2dsphere" } )
2dsphere Query
db.<collection>.find( { <location field> :
{ $geoWithin :
{ $geometry :
{ type : "Polygon" ,
coordinates : [ <coordinates> ]
} } } } )
db.places.find( { loc :
{ $geoWithin :
{ $geometry :
{ type : "Polygon" ,
coordinates : [ [[ 0 , 0 ] ,[ 3 , 6 ] ,[ 6 , 1 ] ,[ 0 , 0 ]] ]} } } } )
Intersection
db.<collection>.find( { <location field> :
{ $geoIntersects :
{ $geometry :
{ type : "<GeoJSON object type>" ,
coordinates : [ <coordinates> ]
} } } } )
db.places.find( { loc :
{ $geoIntersects :
{ $geometry :
{ type : "Polygon" ,
coordinates: [ [[ 0 , 0 ] ,[ 3 , 6 ] ,[ 6 , 1 ] ,[ 0 , 0 ]] ]} } } } )
Proximity
db.<collection>.find( { <location field> :
{ $near :
{ $geometry :
{ type : "Point" ,
coordinates : [ <longitude> , <latitude> ] } ,
$maxDistance : <distance in meters>
} } } )
2dsphere
● Calculations on a sphere
● GeoJSON objects and include
backwards compatibility for legacy
coordinate pairs
● Compound indexes with scalar index
fields (i.e. ascending or descending) as
a prefix or suffix of the 2dsphere index
field
geoHaystack
An index is a special index that is
optimized to return results over small
areas. geoHaystack indexes improve
performance on queries that use flat
geometry.
Any Questions
