Re: So what's null then if it's not nothing?

vc wrote:
> JOG wrote:
> > I don't quite understand this, perhaps you could expand vc. My
> > stumbling block is that Null is simply incomparable with an integer for
> > example - it is like asking whether a sound is less than the colour
> > blue.
>
> I do not think anyone suggested questions like that should be asked
> (sound vs. color).

well, null vs. integer (the property of absence vs. a number) is no different to sound vs. colour - they are both incomparable items. Yet an RDBMS does potentially allow null values to be part of a columns domain, and as such they are subject to comparison when none can be made. This contradiction is the centre of the problem that generates these gargantuan threads.

> The question is rather whether it makes sense to
> compare values belonging to the *same* domain if some of those 'values'
> happen to be unknown/inapplicable/missing for a particular set of rows.
> Or whether it makes sense to deal with such
> unknown/inapplicable/missing at all. That's up to you to decide.

I disagree, predicate logic decides in this case. Inapplicable data obviously violates the RM's theoretical underpinnings which define a table as a set of tuples that make up the extension of a predicate intension. Missing data is no different. If you don't have it, well you just don't have a proposition that fulfills the table header. That's predicate logic for you. The question is whether you want to address this at the model level, incorporating the fact that we live in a world where data is always going to be missing, or to employ a 3VL to serve as a a bandaid to allow reasonable querying.

> >It seems to
> > me that this would be an attempt to alleviate a symptom as opposed to
> > the underlying ill. I am of course open to convincing otherwise.
> >
>
> Then, you need to come up with an alternative suggestion that would
> have a better way to handle those nebulous values,

indeed.

> or just stick with the 2VL and convince yourself that you do not need to deal with
> unknown/inapplicable/missing/etc. in your data modelling life.

or hidden option c, use RM and 2VL and let human interpretation act as the band aid. I am aware however that we are agreeing on the central problem, and just coming at it from opposite directions. Received on Tue Dec 13 2005 - 20:28:31 CET