On 12/12/13 14:02, Vivek Pathak wrote:
I just mentioned my approach since it is a common misconception that multidimensional can not be efficiently mapped to single dimension. I found the solution to work very well, and it is conceptually simple also.
Back in the day, Oracle came up with Helical Hyperspatial Codes, which were supposed to be used for multi-dimensional data (including geo-spatial ones); more modestly what you devised is called GeoHash http://en.wikipedia.org/wiki/Geohash
Alas, GeoHash is not a powerful way of indexing geo-spatial data; GeoCouch uses R-trees instead, which are better (any serious geo-spatial index uses either grids or R-trees).
As per using multiple dimensions in the same view, Volker (the main developer of GeoCouch) has it on his to-do list: his idea is to use n-dimensional R-trees.
Regards, Luca Morandini Data Architect - AURIN project Melbourne eResearch Group Department of Computing and Information Systems University of Melbourne Tel. +61 03 903 58 380 Skype: lmorandini
