On Mar 7, 2010, at 7:45 AM, KshamaPai wrote: > > Hi, > > Inorder to understand - cartessian tiers,how are they contributing in > location based search - What is happening internally when we give query to > solr like http://localhost:8983/solr/select/?q=name:Minneapolis AND > _val_:"recip(hsin(0.78, -1.6, lat_rad, lon_rad, 3963.205), 1, 1, 0)"^100 and > other functions like ghhsin(),sqedist(),dist() .how is it working to > retrieve relevent records? >
This query says to me: Find all documents that have the word Minneapolis in the name and boost the scores based on not only the term scores (i.e. Minneapolis) but also add in a boost based on 1 over the haversine distance between the point 0.78, -1.6 (in radians) and the values contained in the lat_rad and lon_rad fields (for each document that matched Minneapolis) and boost that resulting score by 100. In other words, 1 over the distance. The other functions are just different ways of calculating distance. GHSin is the Haversine distance applied to a GeoHash field. A geohash field encodes lat/lon into a single field. Haversine is generally more accurate for measurements on a Sphere. Dist and sqedist are the traditional distances used in a Rectangular Coordinate System (aka the stuff you learned about way back when as a kid). Even Haversine isn't as accurate as one could get, since the Earth is not actually a Sphere. For most situations, however, it is more than sufficient. If you really need the utmost accuracy, you could implement Vincenty's formula. > Can any one suggest me any link that will help me understand all these > concepts better. Here's the Solr wiki page: http://wiki.apache.org/solr/SpatialSearch Here's an article I wrote on spatial: http://www.ibm.com/developerworks/opensource/library/j-spatial/index.html
