| From: | Andrei Lepikhov <lepihov(at)gmail(dot)com> |
|---|---|
| To: | Alexandra Wang <alexandra(dot)wang(dot)oss(at)gmail(dot)com>, Corey Huinker <corey(dot)huinker(at)gmail(dot)com> |
| Cc: | Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us>, Tomas Vondra <tomas(at)vondra(dot)me>, pgsql-hackers(at)lists(dot)postgresql(dot)org, hs(at)cybertec(dot)at, Jeff Davis <pgsql(at)j-davis(dot)com> |
| Subject: | Re: Is there value in having optimizer stats for joins/foreignkeys? |
| Date: | 2026-01-31 11:18:43 |
| Message-ID: | 8df3d212-5d60-4e30-9606-d8849f7d37ae@gmail.com |
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| Lists: | pgsql-hackers |
On 29/1/26 06:04, Alexandra Wang wrote:
> Hi hackers,
>
> As promised in my previous email, I'm sharing a proof-of-concept patch
> exploring join statistics for correlated columns across relations.
> This is a POC at this point, but I hope the performance numbers below
> give a better idea of both the potential usefulness of join statistics
> and the complexity of implementing them.
I wonder why you chose the JOIN operator only?
It seems to me that any relational operator produces relational output
that can be treated as a table. The extended statistics code may be
adopted to such relations.
I think it may be a VIEW that you can declare (manually or
automatically) and allow Postgres to build statistics on this 'virtual'
table. So, the main focus may shift to the question: how to provably
match a query subtree to a specific statistic.
--
regards, Andrei Lepikhov,
pgEdge
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