On the DB side of things, you will want to make sure that your caching as much as possible - putting a front-end like memcached could help. I assume you have indexes on the appropriate tables? What does the EXPLAIN ANALYZE on that query look like? Not necessarily a "postgres" solution, but I'd think this type of solution would work really, really well inside of say a a mixed integer or integer solver ... something like glpk or cbc. You'd need to reformulate the problem, but we've built applications using these tools which can crunch through multiple billions of combinations in under 1 or 2 seconds. (Of course, you still need to store the results, and feed the input, using a database of some kind). -- Anthony Presley On Tue, 2009-06-16 at 14:35 -0400, Hartman, Matthew wrote: > Good afternoon. > > I have developed an application to efficiently schedule chemotherapy > patients at our hospital. The application takes into account several > resource constraints (available chairs, available nurses, nurse coverage > assignment to chairs) as well as the chair time and nursing time > required for a regimen. > > The algorithm for packing appointments in respects each constraint and > typically schedules a day of treatments (30-60) within 9-10 seconds on > my workstation, down from 27 seconds initially. I would like to get it > below 5 seconds if possible. > > I think what's slowing is down is simply the number of rows and joins. > The algorithm creates a scheduling matrix with one row per 5 minute > timeslot, per unit, per nurse assigned to the unit. That translates to > 3,280 rows for the days I have designed in development (each day can > change). > > To determine the available slots, the algorithm finds the earliest slot > that has an available chair and a count of the required concurrent > intervals afterwards. So a 60 minute regimen requires 12 concurrent > rows. This is accomplished by joining the table on itself. A second > query is ran for the same range, but with respect to the nurse time and > an available nurse. Finally, those two are joined against each other. > Effectively, it is: > > Select * > From ( > Select * > From matrix m1, matrix m2 > Where m1.xxxxx = m2.xxxxx > ) chair, > ( > Select * > From matrix m1, matrix m2 > Where m1.xxxxx = m2.xxxxx > ) nurse > Where chair.id = nurse.id > > With matrix having 3,280 rows. Ugh. > > I have tried various indexes and clustering approachs with little > success. Any ideas? > > Thanks, > > Matthew Hartman > Programmer/Analyst > Information Management, ICP > Kingston General Hospital > (613) 549-6666 x4294 > > -- Sent via pgsql-performance mailing list (pgsql-performance@xxxxxxxxxxxxxx) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-performance