> 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 > > Fight against software patents in Europe! www.ffii.org > www.nosoftwarepatents.org > > ---------------------------(end of broadcast)--------------------------- > TIP 6: explain analyze is your friend > ---------------------------(end of broadcast)--------------------------- TIP 6: explain analyze is your friend
