Slow query in table where many rows were deleted. VACUUM FULL fixes it

From: Pavlos Kallis <pkallis(at)yourhero(dot)com>
To: pgsql-performance(at)postgresql(dot)org
Subject: Slow query in table where many rows were deleted. VACUUM FULL fixes it
Date: 2024-01-30 09:40:19
Message-ID: CABzFZgHm0=9ibE-6-85+Fy+BxcTLDOob4VrzJ0+eOqQXSze7gw@mail.gmail.com
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Hi all,

I have the following table:

CREATE TABLE IF NOT EXISTS public.shortened_url
(
id character varying(12) COLLATE pg_catalog."default" NOT NULL,
created_at timestamp without time zone,
expires_at timestamp without time zone,
url text COLLATE pg_catalog."default" NOT NULL,
CONSTRAINT shortened_url_pkey PRIMARY KEY (id)
)

The table contains only the following index on PRIMARY KEY:

CREATE UNIQUE INDEX IF NOT EXISTS shortened_url_pkey
ON public.shortened_url USING btree
(id COLLATE pg_catalog."default" ASC NULLS LAST)
TABLESPACE pg_default;

This table has approximately 5 million rows of expired URLs (expires_at <
now()), and 5 thousand rows of non-expired URLs (expires_at > now())

I deleted all expired URLs with this query:

DELETE FROM shortened_url WHERE expires_at < now().

Then, I tried to query the table for expired URLs:

SELECT * FROM shortened_url WHERE expires_at < now();

This query was very slow. It took around 1-2 minutes to run, while it had
to fetch only 5000 rows (the non-expired URLs, since the other ones were
deleted).

After that, I tried to run VACUUM ANALYZE and REINDEX to the table.
The query was still slow.

Finally, I ran VACUUM FULL and re-executed the query. Only then, it started
running fast (1-2 seconds).

Do you have observed a similar behavior with VACUUM ANALYZE / VACUUM FULL
and why this can happen?
Is this because data is compacted after VACUUM FULL and sequential disk
reads are faster?
Shouldn't VACUUM ANALYZE reclaim the disk space and make the query run fast?
Is this because RDS might do some magic? Is it something I am missing?

*Additional details*
PostgreSQL version: 14.7 on db.t3.micro RDS
PG configuration: Default of RDS

Kind Regards,
Pavlos

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