Re: New GUC autovacuum_max_threshold ?

Frédéric Yhuel <frederic.yhuel@dalibo.com>

From: Frédéric Yhuel <frederic.yhuel@dalibo.com>
To: Robert Haas <robertmhaas@gmail.com>, Nathan Bossart <nathandbossart@gmail.com>
Cc: Melanie Plageman <melanieplageman@gmail.com>, PostgreSQL Hackers <pgsql-hackers@lists.postgresql.org>, David Rowley <dgrowleyml@gmail.com>, Laurenz Albe <laurenz.albe@cybertec.at>
Date: 2024-04-26T08:10:20Z
Lists: pgsql-hackers

Le 25/04/2024 à 22:21, Robert Haas a écrit :
> The analyze case, I feel, is really murky.
> autovacuum_analyze_scale_factor stands for the proposition that as the
> table becomes larger, analyze doesn't need to be done as often. If
> what you're concerned about is the frequency estimates, that's true:
> an injection of a million new rows can shift frequencies dramatically
> in a small table, but the effect is blunted in a large one. But a lot
> of the cases I've seen have involved the histogram boundaries. If
> you're inserting data into a table in increasing order, every new
> million rows shifts the boundary of the last histogram bucket by the
> same amount. You either need those rows included in the histogram to
> get good query plans, or you don't. If you do, the frequency with
> which you need to analyze does not change as the table grows. If you
> don't, then it probably does. But the answer doesn't really depend on
> how big the table is already, but on your workload. So it's unclear to
> me that the proposed parameter is the right idea here at all. It's
> also unclear to me that the existing system is the right idea. 🙂

This is very interesting. And what about ndistinct? I believe it could 
be problematic, too, in some (admittedly rare or pathological) cases.

For example, suppose that the actual number of distinct values grows 
from 1000 to 200000 after a batch of insertions, for a particular 
column. OK, in such a case, the default analyze sampling isn't large 
enough to compute a ndistinct close enough to reality anyway. But 
without any analyze at all, it can lead to very bad planning - think of 
a Nested Loop with a parallel seq scan for the outer table instead of a 
simple efficient index scan, because the index scan of the inner table 
is overestimated (each index scan cost and number or rows returned).



Commits

Same data as JSON: GET /api/v1/messages/:b64id/commits the thread's linked commits as JSON, with link sources. API reference →
  1. Introduce autovacuum_vacuum_max_threshold.

  2. Consolidate docs for vacuum-related GUCs in new subsection