Hello, thank you for posting the paper, it was quite interesting to read. I think it would be a good idea to give the two-phase optimization a try. As far as I know and understand the current (geqo) optimizer source, many important parts are already there. For example, we can calculate the costs of a given join order. Therefore, it would only be necessary to write an algorithm witch chooses the right input for the cost function. I would be interested in your opinion.
Regards, Tobias Robert Haas schrieb: > 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
