MongoDB allows for geospatial queries on location data stored in collections. There are two main index types - 2d for flat geometry and 2dsphere for spherical geometry. Queries include proximity queries to find nearest points, intersection queries to find intersections with shapes, and inclusion queries to find points within shapes. The appropriate index type and query operators depend on whether location data is represented as legacy coordinate pairs or GeoJSON objects and whether distances are calculated on a flat plane or sphere.

1. MongoDB GeoSpatial
Feature
Hüseyin BABAL
@huseyinbabal

2. What is MongoDB GeoSpatial
Feature?

3. MongoDB allows you to create index and
queries to make operations on geospatial
(location information) data

4. In order to define index, or execute query, you
need to determine surface first

5. Surfaces

6. Spherical
To calculate geometry over an Earth-like
sphere, store your location data on a spherical
surface and use 2dsphere index.
MongoDB Reference

7. 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

8. GeoJSON

9. Example Usage

10. Example Usage

11. Flat
To calculate distances on a Euclidean plane,
store your location data as legacy coordinate
pairs and use a 2d index.
MongoDB Reference

12. Query Operations

13. 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

14. 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

15. Proximity
MongoDB can query for the points nearest to
another point. Proximity queries use the $near
operator. 2d or 2dsphere required
MongoDB Reference

16. Index Types

17. 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

18. 2d Index Creation
db.collection.createIndex( { <location field> : "2d" } ,
{ min : <lower bound> , max : <upper bound> } )
db.collection.createIndex( { loc : "2d" } ,
{ min : -45 , max : 45 } )

19. 2d Query
db.<collection>.find( { <location field> :
{ $geoWithin :
{ $box|$polygon|$center : <coordinates>
} } } )
db.places.find( { loc :
{ $geoWithin :
{ $box : [ [ 0 , 0 ] ,
[ 100 , 100 ] ]
} } } )

20. db.places.find( { loc: { $geoWithin :
{ $center : [ [-74, 40.74 ] , 10 ]
} } } )
db.<collection>.find( { <location field> :
{ $near : [ <x> , <y> ]
} } )
db.<collection>.find( { loc: [ <x> , <y> ] } )

21. 2dsphere Index Creation
db.collection.createIndex( { <location field> : "2dsphere" } )
db.collection.createIndex( { loc : "2dsphere" } )

22. 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 ]] ]} } } } )

23. 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 ]] ]} } } } )

24. Proximity
db.<collection>.find( { <location field> :
{ $near :
{ $geometry :
{ type : "Point" ,
coordinates : [ <longitude> , <latitude> ] } ,
$maxDistance : <distance in meters>
} } } )

25. 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

26. 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.

27. Any Questions