I am using the following Nearest Neighbor Query in PostGIS :
SELECT g1.gid g2.gid FROM points as g1, polygons g2
WHERE g1.gid <> g2.gid
ORDER BY g1.
You can do it with KNN index and lateral join.
SELECT v.gid, v2.gid,st_distance(v.the_geom, v2.the_geom)
FROM geonames v,
lateral(select *
from geonames v2
where v2.id<>v.id
ORDER BY v.the_geom <-> v2.the_geom LIMIT 10) v2
where v.gid in (...) - or other filtering condition
Assuming you have p point and g polygons, your original query:
SELECT g1.gid, g2.gid FROM points as g1, polygons g2
WHERE g1.gid <> g2.gid
ORDER BY g1.gid, ST_Distance(g1.the_geom,g2.the_geom)
LIMIT k;
Is returning the k nearest neighbours in the p x g set. The query may be using indexes, but it still has to order the entire p x g set to find the k rows with the smallest distance. What you instead want is the following:
SELECT g1.gid,
(SELECT g2.gid FROM polygons g2
--prevents you from finding every nearest neighbour twice
WHERE g1.gid < g2.gid
--ORDER BY gid is erroneous if you want to limit by the distance
ORDER BY ST_Distance(g1.the_geom,g2.the_geom)
LIMIT k)
FROM points as g1;
Just a few thoughts on your problem:
st_distance as well as st_area are not able to use indices. This is because both functions can not be reduced to questions like "Is a within b?" or "Do a and b overlap?". Even more concrete: GIST-indices can only operate on the bounding boxes of two objects.
For more information on this you just could look in the postgis manual, which states an example with st_distance and how the query could be improved to perform better.
However, this does not solve your k-nearest-neighbour-problem. For that, right now I do not have a good idea how to improve the performance of the query. The only chance I see would be assuming that the k nearest neighbors are always in a distance of below x meters. Then you could use a similar approach as done in the postgis manual.
Your second query could be speeded up a bit. Currently, you compute the area for each object in table 1 as often as table has rows - the strategy is first to join the data and then select based on that function. You could reduce the count of area computations significantly be precomputing the area:
WITH polygonareas AS (
SELECT gid, the_geom, st_area(the_geom) AS area
FROM polygons
)
SELECT g1.gid, g2.gid
FROM polygonareas as g1 , polygonareas as g2
WHERE g1.area > g2.area;
Your third query can be significantly optimized using bounding boxes: When the bounding boxes of two objects do not overlap, there is no way the objects do. This allows the usage of a given index and thus a huge performance gain.
Since late September 2011, PostGIS has supported indexed nearest neighbor queries via a special operator(s) usable in the ORDER BY clause:
SELECT name, gid
FROM geonames
ORDER BY geom <-> st_setsrid(st_makepoint(-90,40),4326)
LIMIT 10;
...will return the 10 objects whose geom
is nearest -90,40
in a scalable way. A few more details (options and caveats) are in that announcement post and use of the <-> and the <#> operators is also now documented in the official PostGIS 2.0 reference. (The main difference between the two is that <->
compares the shape centroids and <#>
compares their boundaries — no difference for points, other shapes choose what is appropriate for your queries.)
What you may need is the KNN index which is hopefully available soon in PostGIS 2.x and PostgreSQL 9.1: See http://blog.opengeo.org/tag/knn/