Indexes: Indexing Spatial Data
To support the ability to retrieve the data based on spatial coordinates, the spatial search has been introduced.
Information
This article describes how to setup a spatial field in static index. If you are interested in an automatic approach, please visit relevant spatial querying article that can be found here.
Creating Indexes
To take an advantage of the spatial search, first we need to create an index with a spatial field. To mark field as the spatial field, we need to use the CreateSpatialField
method:
object CreateSpatialField(double? lat, double? lng);
object CreateSpatialField(string shapeWkt);
Where:
- lat/lng are latitude/longitude coordinates
- shapeWKT is a shape in the WKT format
Example
public class Event
{
public string Id { get; set; }
public string Name { get; set; }
public double Latitude { get; set; }
public double Longitude { get; set; }
}
public class Events_ByNameAndCoordinates : AbstractIndexCreationTask<Event>
{
public Events_ByNameAndCoordinates()
{
Map = events => from e in events
select new
{
Name = e.Name,
Coordinates = CreateSpatialField(e.Latitude, e.Longitude)
};
}
}
public class EventWithWKT
{
public string Id { get; set; }
public string Name { get; set; }
public string WKT { get; set; }
}
public class EventsWithWKT_ByNameAndWKT : AbstractIndexCreationTask<EventWithWKT>
{
public EventsWithWKT_ByNameAndWKT()
{
Map = events => from e in events
select new
{
Name = e.Name,
WKT = CreateSpatialField(e.WKT)
};
}
}
Options
RavenDB supports both the Geography
and Cartesian
systems and multiple strategies for each one of them.
public class SpatialOptionsFactory
{
public GeographySpatialOptionsFactory Geography;
public CartesianSpatialOptionsFactory Cartesian;
}
// GeohashPrefixTree strategy with maxTreeLevel set to 9
SpatialOptions Default(SpatialUnits circleRadiusUnits = SpatialUnits.Kilometers);
SpatialOptions BoundingBoxIndex(SpatialUnits circleRadiusUnits = SpatialUnits.Kilometers);
SpatialOptions GeohashPrefixTreeIndex(int maxTreeLevel, SpatialUnits circleRadiusUnits = SpatialUnits.Kilometers);
SpatialOptions QuadPrefixTreeIndex(int maxTreeLevel, SpatialUnits circleRadiusUnits = SpatialUnits.Kilometers);
SpatialOptions BoundingBoxIndex();
SpatialOptions QuadPrefixTreeIndex(int maxTreeLevel, SpatialBounds bounds);
Changing Default Behavior
By default, if no action is taken, the GeohashPrefixTree
strategy is used with GeohashLevel
set to 9. This behavior can be changed by using the Spatial
method from AbstractIndexCreationTask
public class Events_ByNameAndCoordinates_Custom : AbstractIndexCreationTask<Event>
{
public Events_ByNameAndCoordinates_Custom()
{
Map = events => from e in events
select new
{
Name = e.Name,
Coordinates = CreateSpatialField(e.Latitude, e.Longitude)
};
Spatial("Coordinates", factory => factory.Cartesian.BoundingBoxIndex());
}
}
Spatial search strategies
GeohashPrefixTree
E.g. The location of 'New York' in the United States is represented by the following geohash: DR5REGY6R and it represents the 40.7144 -74.0060
coordinates. Removing characters from the end of geohash will decrease the precision level.
More information about geohash uses, decoding algorithm and limitations can be found here.
QuadPrefixTree
More information about QuadTree can be found here.
BoundingBox
Warning
GeohashPrefixTree
is a default SpatialSearchStrategy
. Doing any changes to the strategy after an index has been created will trigger the re-indexation process.
Precision
By default, the precision level (maxTreeLevel
) for GeohashPrefixTree is set to 9 and for QuadPrefixTree the value is 23. This means that the coordinates are represented by a 9 or 23 character string. The difference exists because the QuadTree
representation would be much less precise if the level would be the same.
Geohash precision values
Level | E-W Distance at Equator | N-S Distance at Equator |
---|---|---|
12 | ~3.7cm | ~1.8cm |
11 | ~14.9cm | ~14.9cm |
10 | ~1.19m | ~0.60m |
9 | ~4.78m | ~4.78m |
8 | ~38.2m | ~19.1m |
7 | ~152.8m | ~152.8m |
6 | ~1.2km | ~0.61km |
5 | ~4.9km | ~4.9km |
4 | ~39km | ~19.6km |
3 | ~157km | ~157km |
2 | ~1252km | ~626km |
1 | ~5018km | ~5018km |
Quadtree precision values
Level | Distance at Equator |
---|---|
30 | ~4cm |
29 | ~7cm |
28 | ~15cm |
27 | ~30cm |
26 | ~60cm |
25 | ~1.19m |
24 | ~2.39m |
23 | ~4.78m |
22 | ~9.56m |
21 | ~19.11m |
20 | ~38.23m |
19 | ~76.23m |
18 | ~152.92m |
17 | ~305.84m |
16 | ~611.67m |
15 | ~1.22km |
14 | ~2.45km |
13 | ~4.89km |
12 | ~9.79km |
11 | ~19.57km |
10 | ~39.15km |
9 | ~78.29km |
8 | ~156.58km |
7 | ~313.12km |
6 | ~625.85km |
5 | ~1249km |
4 | ~2473km |
3 | ~4755km |
2 | ~7996km |
1 | ~15992km |
Remarks
Information
You can read more about spatial search in a dedicated querying article available here.
Warning
Distance by default is measured in kilometers.