Re: Review remove {join,from}_collapse_limit, add enable_join_ordering
От | Kenneth Marshall |
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Тема | Re: Review remove {join,from}_collapse_limit, add enable_join_ordering |
Дата | |
Msg-id | 20090716202230.GA1452@it.is.rice.edu обсуждение исходный текст |
Ответ на | Re: Review remove {join,from}_collapse_limit, add enable_join_ordering (Andres Freund <andres@anarazel.de>) |
Список | pgsql-hackers |
On Thu, Jul 16, 2009 at 06:49:08PM +0200, Andres Freund wrote: > On Thursday 16 July 2009 17:59:58 Tom Lane wrote: > > Andres Freund <andres@anarazel.de> writes: > > > The default settings currently make it relatively hard to trigger geqo at > > > all. > > > > Yes, and that was intentional. One of the implications of what we're > > discussing here is that geqo would get used a lot more for "typical > > complex queries" (if there is any such thing as a typical one). So > > it's fully to be expected that the fallout would be pressure to improve > > geqo in various ways. > > > > Given that we are at the start of the development cycle, that prospect > > doesn't scare me --- there's plenty of time to fix whatever needs > > fixing. However, I am leaning to the feeling that I don't want to be > > putting people in a position where they have no alternative but to use > > geqo. So adjusting rather than removing the collapse limits is seeming > > like a good idea. > Hm. I see a, a bit more fundamental problem with geqo: > I tried several queries, and I found not a single one, where the whole > genetical process did any significant improvments to the 'worth'. > It seems that always the best variant out of the pool is either the path > choosen in the end, or at least the cost difference is _really_ low. > > > Andres > Hi Andres, From some of my reading of the literature on join order optimization via random sampling, such as what would establish the initial GEQO pool, there is a very good possibility of having a "pretty good" plan in the first pool, especially for our larger initial pool sizes of 100-1000. And in fact, the final plan has a good chance of being of approximately the same cost as a member of the initial pool. Uniform sampling alone can give you a close to optimum plan 80% of the time with an initial sample size of 100. And using biased sampling raises that to 99% or better. Regards, Ken
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