> Maybe "group by", "order by", "distinct on" and hand-written functions
> and aggregates (like first() or best()) may help.
We use these - we have lexical analysis functions which assign a rating to
each row in a set, and the likelyhood that the data is a match, and then we
sort our results.
I thought this would be the cause of the slowdowns - and it is, but a very
small part of it. I have identified the problem code, and the problems are
within some very simple joins. I have posted the code under a related topic
header. I obviously have a few things to learn about optimising SQL joins.
Carlo
>
> You could combine all relevant columns into an user-defined compund
> type, then group by entity, and have a self-defined aggregate generate
> the accumulated tuple for each entity.
>
> Markus
> --
> Markus Schaber | Logical Tracking&Tracing International AG
> Dipl. Inf. | Software Development GIS
>
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