Optimum search with geospatial coordinates

Grant Shipley gshipley at gmail.com
Wed Mar 19 18:17:22 MDT 2014


Just out of curiosity, does the said device have a network connection?  If
not, how you are going to update the data points of interests (you
mentioned stores)?  I can imagine a list of stores will become quickly
outdated.

--
gs


On Wed, Mar 19, 2014 at 4:42 PM, Levi Pearson <levipearson at gmail.com> wrote:

> On Wed, Mar 19, 2014 at 4:57 PM, S. Dale Morrey <sdalemorrey at gmail.com>
> wrote:
> > Agreed, an rtree was not what I was balking about and loading into an
> rtree
> > is an expensive one time process but it can be serialized to the device
> > storage for quick loading.
> >
> > I was balking at using a full on database solution :D
> > Although I did just find out that the device OS uses SQLite for
> preferences
> > storage, so maybe there is room for a DB in there.
> >
> > FYI this is just a RAD app that, like you mentioned is a list of stores
> and
> > we want to hit the user with the closest store when they open the app.
> > Imagine pressing a button on your phone and being presented with the
> > nearest gas station to your current location already loaded into GPS &
> > nav.  That's pretty close to what I'm trying to achieve here.
>
> Unless there's some massive number of stores in the data set, the
> asymptotics probably aren't going to matter all that much to your
> usability case. Load up a sample set and see how the naive search
> works.  If it's good enough, it's good enough.
>
> But because it's really interesing, I'll point out this technique for
> sorting/linearizing a multi-dimensional data set into a single
> dimension while preserving locality:
> http://en.wikipedia.org/wiki/Z-order_curve
>
> If you look down to the section on "Use with one-dimensional data
> structures for range searching" you should be able to use that
> algorithm to cut down the portion of the array you need to walk
> through to find the nearest points.  Here's a direct link to the
> referenced paper that describes the algorithm in detail:
> http://www.vision-tools.com/h-tropf/multidimensionalrangequery.pdf
>
>     --Levi
>
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