[postgis-users] Strategies for rapid application development using PostGIS
Pierre.Racine at sbf.ulaval.ca
Fri Jul 30 07:46:06 PDT 2010
I would suggest to do everything with SQL views and pl/pgSQL functions. From what I read, ORM seems to add an unnecessary, inefficient layer unless you want to get involved in complex OO design and develop a portable solution (http://en.wikipedia.org/wiki/Object-relational_mapping).
My two cents.
>From: postgis-users-bounces at postgis.refractions.net [mailto:postgis-users-
>bounces at postgis.refractions.net] On Behalf Of William Furnass
>Sent: 30 juillet 2010 08:40
>To: PostGIS Users Discussion
>Subject: [postgis-users] Strategies for rapid application development using PostGIS
>I wish to use PostGIS/PostgreSQL for data mining exercise (MSc
>project) rather than developing fully-fledged GIS app, the goal being
>to determine the causes of water quality issues in a water
>distribution network. I need to:
> - filter and pre-process several datasets (each containing ~10^5
>records) describing water quality issue events and possible cause
> - associate the events in different cause and effect datasets with
>edges/nodes in my distribution network model to produce an 'integrated
> - traverse the network model, giving consideration to the network
>hydraulics, in an attempt to associate one or more possible causes
>with each water quality issue.
>I believe I can achieve most of this using 'standard' SQL, PostGIS
>functions and possibly some recursive PL/pgSQL functions to traverse
>my network structures and then visually verify that the region of
>influence determined for each water quality event is sane using
>Quantum GIS. However, I would very much like to automate aspects of
>the dataset processing, integrated model construction and model
>analysis to allow me to more easily perform sensitivity analysis on
>certain parameters, to reduce the amount of ugly adhoc snippets of
>(say) Python that I need to write and to perhaps allow the analysis
>parameters to be set and the results viewed from a QGIS plugin.
>I've considered baking lots of SQL into pyodbc cursor.execute(sql)
>calls but think that such an approach could get rather messy. I've
>also taken a look at the SQLAlchemy/GeoAlchemy ORM framework, which
>initially seems to be rather too heavy for my needs and would require
>me to spend much time finding ways to rewrite complex queries
>involving many joins and much nesting. I should also mention that I
>have little time to devise an analysis tool and generate some results
>and that I haven't done much programming (OOP or otherwise) for a
>number of years.
>How do other list subscribers manage data analysis projects (as
>opposed to full-on GIS application development projects) using
>PostGIS? How far into writing ORM code or integrating an existing ORM
>framework have people gone when undertaking similar tasks?
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