From: | "John D(dot) Burger" <john(at)mitre(dot)org> |
---|---|
To: | "Evandro's mailing lists (Please, don't send personal messages to this address)" <listasjr(at)gmail(dot)com> |
Cc: | pgsql-general <pgsql-general(at)postgresql(dot)org> |
Subject: | Re: Beyond the 1600 columns limit on windows |
Date: | 2005-11-08 19:14:58 |
Message-ID: | ef5f06ce42ae2d3ad304504be6d5b7fc@mitre.org |
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Lists: | pgsql-general |
Evandro's mailing lists (Please, don't send personal messages to this
address) wrote:
> It has nothing to do with normalisation. It is a program for
> scientific applications.
> Data values are broken into column to allow multiple linear regression
> and multivariate regression trees computations.
Having done similar things in the past, I wonder if your current DB
design includes a column for every feature-value combination:
instanceID color=red color=blue color=yellow ... height=71
height=72
-------------------------------------------------
42 True False False
43 False True False
44 False False True
...
This is likely to be extremely sparse, and you might use a sparse
representation accordingly. As several folks have suggested, the
representation in the database needn't be the same as in your code.
> Even SPSS the most well-known statistic sw uses the same approach and
> data structure that my software uses.
> Probably I should use another data structure but would not be as
> eficient and practical as the one I use now.
The point is that, if you want to use Postgres, this is not in fact
efficient and practical. In fact, it might be the case that mapping
from a sparse DB representation to your internal data structures is
=more= efficient than naively using the same representation in both
places.
- John D. Burger
MITRE
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