Normalized Tables & SELECT [was: Find "smallest common year"]

>> What would you recommend for say, 500 global national statistical
>> variables,
>> 500 regional and 500 subregional and 500 global aggregations?
>> Years being
>> covered having something between 10 and 60 years for each of these
>> variables. All available for 240 countries/territories.
>
> I generally approach such problems by putting the data right
> (normalized) at the start, then munging the data into summary tables
> to handle the problems you're seeing now.
>
> I find it far easier to maintain normalized tables that produced
> non-normalized ones (for things like data warehousing) than it is to
> maintain non-normalized tables and trying to produce normalized data
> from that.

Ok, I do understand that.

So, instead of the earlier mentioned database design, I would have
something like this:

    - one table for the country names/ids/etc. (Afghanistan, 1;
Albania, 2....)
    - one table for the variable names/ids/etc. (GDP, 1; Population,
2; Fish Catch, 3;....)
    - one table for the years names/ids/etc. (1970, 1; 1971, 2; 1973,
3; ....)
and
    - one table for all "statistical data" with four fields -
id_variable, id_country, id_year, and the actual value

You say

> I find it far easier to maintain normalized tables that produced
> non-normalized ones (for things like data warehousing) than it is to
> maintain non-normalized tables and trying to produce normalized data
> from that.

It seems to me more difficult now to produce a non-normalized output
based on the normalized table. How would look a query like, if I need
now to SELECT, say 100 countries and 20 years? Something like this
(simplified and without joins):

    SELECT
            value,
            id.year
    FROM
            main_table
    WHERE
            year = '1970' OR
            year = '1971' OR
            ....
            country_name = 'Afghanistan' OR
              country_name = 'Albania' OR
            ...

Actually, last time we came up with SubSelects for each year. So,
does this make sense?

Thanks a lot for your help!

Stef

  ____________________________________________________________________

   Stefan Schwarzer

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