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From: Andrei Lepikhov <[email protected]>
To: Alexandra Wang <[email protected]>
To: Corey Huinker <[email protected]>
Cc: Tom Lane <[email protected]>
Cc: Tomas Vondra <[email protected]>
Cc: [email protected]
Cc: [email protected]
Cc: Jeff Davis <[email protected]>
Subject: Re: Is there value in having optimizer stats for joins/foreignkeys?
Date: Sat, 31 Jan 2026 12:18:43 +0100
Message-ID: <[email protected]> (raw)
In-Reply-To: <CAK98qZ0LwJbUoiZjjFXitojHy4UskkjYDiSd_JZfGE9LbfZm9w@mail.gmail.com>
References: <CADkLM=cUwMftPLFq0iD6-qKRyNiRM2HZGYVp6=0noxA8GfuEtA@mail.gmail.com>
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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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