Need performance on postGIS with GeoDjango

Question

This is the first time I'm using GeoDjango with postGIS. After installation and some tests with everything running fine I am concerned about query performance when table rows will grow.

I'm saving in a geometry point longitudes and latitudes that I get from Google geocoding (WGS84, or SRID 4326). My problem is that distance operations are very common in my application. I often need to get near spots from a landmark. Geometry maths are very complex, so even if I have an spatial index, it will probably take too long in the future having more than 1000 spots in a nearby area.

So is there any way to project this geometry type to do distance operations faster? does anyone know a Django library that can render a Google map containing some of these points?

Any advices on how to speed up spatial queries on GeoDjango?

Answer 1

If you can fit your working area into a map projection, that will always be faster, as there are fewer math calls necessary for things like distance calculations. However, if you have truly global data, suck it up: use geography. If you only have continental USA data, use something like EPSG:2163 http://spatialreference.org/ref/epsg/2163/

The more constrained your working area, the more accurate results you can get in a map projection. See the state plane projections for highly constrained, accurate projections for regional areas in the USA. Or UTM projections for larger sub-national regions.

Answer 2

I'm researching on this topic. As far as I have found, coordinates that you get from geopy library are in SRID 4326 format, so you can store them in a geometry field type without problems. This would be an example of a GeoDjango model using geometry:

class Landmark(models.Model):
   point = models.PointField(spatial_index = True,
                           srid = 4326,
                           geography = True)

   objects = models.GeoManager()

By the way, be very careful to pass longitude / latitude to the PointField, in that exact order. geopy returns latitude / longitude coordinates, so you will need to reverse them.

For transforming points in one coordinate system to another we can use GEOS with GeoDjango. In the example I will transform a point in 4326 to the famous Google projection 900913:

from django.contrib.gis.geos import Point
punto = Point(40,-3)
punto.set_srid(900913)
punto.transform(4326)
punto.wkt
Out[5]: 'POINT (0.0003593261136478 -0.0000269494585230)'

This way we can store coordinates in projection systems, which will have better performance maths. For showing points in a Google map in the admin site interface. We can use this great article.

I have decided to go on with geography types, and I will convert them in the future, in case I need to improve performance.