From: | Tom Lane <tgl(at)sss(dot)pgh(dot)pa(dot)us> |
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To: | Marco Colli <collimarco91(at)gmail(dot)com> |
Cc: | pgsql-performance(at)lists(dot)postgresql(dot)org |
Subject: | Re: Statistics on array values |
Date: | 2020-02-02 17:11:05 |
Message-ID: | 2661.1580663465@sss.pgh.pa.us |
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Lists: | pgsql-performance |
Marco Colli <collimarco91(at)gmail(dot)com> writes:
> Let's say that you have a simple query like the following on a large table
> (for a multi-tenant application):
> SELECT "subscribers".* FROM "subscribers" WHERE "subscribers"."project_id"
> = 123 AND (tags @> ARRAY['de']::varchar[]);
> If you run EXPLAIN ANALYZE you can see that stats are completely wrong.
> For example I get an expected count of 3,500 rows whereas the actual
> result is 20 rows. This also results in bad query plans...
> In a previous discussion someone said that this wrong estimate is because
> @> uses a fixed selectivity of 0.001, **regardless of actual data**!!
> Is that true?
Hasn't been true since 9.2.
You might get some insight from looking into the most_common_elems,
most_common_elem_freqs, and elem_count_histogram fields of the pg_stats
view.
It seems likely to me that increasing the statistics target for this array
column would help. IIRC, estimates for values that don't show up in
most_common_elems are going to depend on the lowest frequency that *does*
show up there ... so if you want better resolution for non-common values,
you need more entries.
regards, tom lane
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