2009/12/1 Rüdiger Sörensen <r.soerensen@mpic.de>:
> dear all,
>
> I am building a database that will be really huge and grow rapidly. It holds
> data from satellite observations. Data is imported via a java application.
> The import is organized via files, that are parsed by the application; each
> file hods the data of one orbit of the satellite.
> One of the tables will grow by about 40,000 rows per orbit, there are
> roughly 13 orbits a day. The import of one day (13 orbits) into the database
> takes 10 minutes at the moment. I will have to import data back to the year
> 2000 or even older.
> I think that there will be a performance issue when the table under question
> grows, so I partitioned it using a timestamp column and one child table per
> quarter. Unfortunately, the import of 13 orbits now takes 1 hour instead of
> 10 minutes as before. I can live with that, if the import time will not
> grow sigificantly as the table grows further.
I'm gonna guess you're using rules instead of triggers for
partitioning? Switching to triggers is a big help if you've got a
large amount of data to import / store. If you need some help on
writing the triggers shout back, I had to do this to our stats db this
summer and it's been much faster with triggers.
