Hi Max, I'm the author of this post: http://blog.notdot.net/2009/11/Damn-Cool-Algorithms-Spatial-indexing-with-Quadtrees-and-Hilbert-Curves
You're right that this will likely have problems when dealing with arbitrary data rather than geospatial indexing. Hilbert curves work well at returning results with a minimum of false-positives and minimal queries when the region you're searching is (in coordinates on the curve) roughly square, or at least no more than 2:1. With arbitrary indexes, you could easily have queries that don't fit that approximation. At the very least, it would require some tuning. -Nick Johnson On Tue, Jul 5, 2011 at 12:22 PM, Max <[email protected]> wrote: > Hi all, > > Would like to know if there are any of you guys ever tried to use space > filling curve like Hilbert curve to build index for multiple inequality > filters. > > Seems like for any continuous field like long or date, the number of ranges > (to be merged) to perform a accurate query is increasing rapidly, which > makes this approach not scale. > > Any thought? or shall I build / model like this > sample<http://code.google.com/appengine/articles/geosearch.html> app? > Query by partitions of all data and do an in-memory merge? > > -- > You received this message because you are subscribed to the Google Groups > "Google App Engine" group. > To view this discussion on the web visit > https://groups.google.com/d/msg/google-appengine/-/MipYkQ1_pvYJ. > To post to this group, send email to [email protected]. > To unsubscribe from this group, send email to > [email protected]. > For more options, visit this group at > http://groups.google.com/group/google-appengine?hl=en. > -- Nick Johnson, Developer Programs Engineer, App Engine -- You received this message because you are subscribed to the Google Groups "Google App Engine" group. To post to this group, send email to [email protected]. To unsubscribe from this group, send email to [email protected]. For more options, visit this group at http://groups.google.com/group/google-appengine?hl=en.
