čt 11. 12. 2025 v 18:07 odesílatel Tomas Vondra <tomas@vondra.me> napsal:
On 12/11/25 07:12, Pavel Stehule wrote: > > > čt 11. 12. 2025 v 3:53 odesílatel John Naylor <johncnaylorls@gmail.com > <mailto:johncnaylorls@gmail.com>> napsal: > > On Wed, Dec 10, 2025 at 5:20 PM Tomas Vondra <tomas@vondra.me > <mailto:tomas@vondra.me>> wrote: > > I did however notice an interesting thing - running EXPLAIN on the 99 > > queries (for 3 scales and 0/4 workers, so 6x 99) took this much time: > > > > master: 8s > > master/geqo: 20s > > master/goo: 5s > > > It's nice that "goo" seems to be faster than "geqo" - assuming the > plans > > are comparable or better. But it surprised me switching to geqo > makes it > > slower than master. That goes against my intuition that geqo is > meant to > > be cheaper/faster join order planning. But maybe I'm missing > something. > > Yeah, that was surprising. It seems that geqo has a large overhead, so > it takes a larger join problem for the asymptotic behavior to win over > exhaustive search. > > > If I understand correctly to design - geqo should be slower for any > queries with smaller complexity. The question is how many queries in the > tested model are really complex. >
Depends on what you mean by "really complex". TPC-DS queries are not trivial, but the complexity may not be in the number of joins.
Of course, setting geqo_threshold to 2 may be too aggressive. Not sure.
I checked the TPC-H queries and almost all queries are simple - 5 x JOIN -- 2x nested subselect
