[postgis-devel] Windowing Functions for Clustering

[Daniel Baston]

Hi Paul,

It's been a while since I thought about this.  I don't remember a specific
technical barrier to implementing the clustering as a window function.  I
suspect that I went the aggregate route because it seemed simpler at the
time (the API for writing aggregates being better documented than that of
window functions), and in my personal use cases it wasn't a problem to get
the cluster geometries without knowing which inputs contributed to each
cluster.  It doesn't feel completely clean though; in particular, I don't
like how you have to wrap the output with an unnest() to get anything
useful.

Maybe the best case is to implement the core clustering functionality in
such a way that it can be exposed either as an aggregate or a window
function?

I recently put in a ticket to implement the DBSCAN clustering algorithm, of
which the existing clustering functions are a special case (
https://trac.osgeo.org/postgis/ticket/3362).  If I find some time to work
on that, it might be a good occasion to explore the window approach further.

Thanks,
Dan

On Fri, Dec 18, 2015 at 2:02 PM, Paul Ramsey <pramsey at cleverelephant.ca>
wrote:

> Hey Dan,
> I've been reading up on the k-means cluster implementation already out
> there, thinking about adding one to PostGIS (makes sense, I figure)
> and one thing I've been trying to figure out is what the right API for
> a clustering function is.
>
> The k-means guy decided to do a windowing function, which I kind of like...
>
> https://github.com/umitanuki/kmeans-postgresql/blob/master/kmeans.c#L298
>
> So we'd put do something like,
>
>   select gid, st_clusterkmeans(geom, 4) from geotable;
>
> and get back a list of unique ids and cluster ids. If the user wanted
> to so something after that in terms of unioning, or collecting, or
> whatever, that would be up to the user to decide.
>
> What do you think of the windowing approach, compared to the approach you
> took?
>
> P
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