On Sat, May 2, 2009 at 11:37 AM, Tom Lane <t...@sss.pgh.pa.us> wrote: > Tobias Zahn <tobias-z...@arcor.de> writes: >> I didn't not get any response to my initial message below. Now I am >> wondering if nobody is into the optimizer or if my question was just too >> stupid. Could you please give me some clues? Your help would really be >> appreciated. > > Well, nobody's into GEQO very much. I took a quick look and didn't > think that deleting the ERX support would save anything noticeable, > but you're welcome to try it if you think different. > > The real problem with working on GEQO, in my humble opinion, is that > it's throwing good effort after bad. That module doesn't need marginal > fixing, it needs throwing away and rewriting from scratch. Bad enough > that it's convoluted and full of dead (experimental?) code; but I don't > even believe that it's based on a good analogy. The planning problem > is not all that much like traveling salesman problems, so heuristics > designed for TSP are of pretty questionable usefulness to start with. > That complaint could have been refuted if the module performed well, > but in fact if you check the archives you'll find many many complaints > about it --- its ability to find good plans seems to be mostly dependent > on luck. > > My knowledge of AI search algorithms is about 20 years obsolete, but > last I heard simulated annealing had overtaken genetic algorithms for > many purposes. It might be interesting to try a rewrite based on SA; > or maybe there's something better out there now.
There's a 1997 article on this topic that's pretty interesting. Heuristic and randomized optimization for the join ordering problem http://reference.kfupm.edu.sa/content/h/e/heuristic_and_randomized_optimization_fo_87585.pdf Here's the basic conclusion: "If good solutions are of highest importance, Two-Phase Optimization, the algorithm that performed best in our experiments, is a very good choice; other Simulated Annealing variants, for instance Toured Simulated Annealing (TSA, LVZ93]), that we did not implement, are likely to achieve quite similar results. The 'pure' Simulated Annealing algorithm has a much higher running time without yielding significantly better solutions. If short running time is more important, Iterative Improvement (IIIO), the genetic algo- rithm (BushyGenetic), and, to a lesser extent, Two-Phase Optimization (2PO) are feasible alternatives." I'm not sure if there's anything more recent out there. ...Robert -- Sent via pgsql-hackers mailing list (pgsql-hackers@postgresql.org) To make changes to your subscription: http://www.postgresql.org/mailpref/pgsql-hackers
