Postgresql – Check lock count for PostgreSQL

It sounds like the code might be using SAVEPOINTs to handle errors, and not releasing the savepoints before proceeding. That would explain the large number of virtual xid locks.

RELEASE SAVEPOINT after you're done with a step.

You might also want to consider batching the work into smaller chunks, as the:

• SAVEPOINT
• Try it
• ROLLBACK TO SAVEPOINT if it fails, RELEASE SAVEPOINT if it succeeds

pattern works, but has some performance costs that scale with number of savepoints in a transaction.

This applies to PL/PgSQL BEGIN ... EXCEPTION blocks too.

Do tables with only fixed width values perform read queries better than those with varying widths?

Basically no. There are very minor costs when accessing columns, but you won't be able to measure any difference. Details:

• Does the order of columns in a Postgres table impact performance?

In particular:

• There is no difference in performance between character varying(255) and text at all. You seem to be under the impression that varchar(255) (unlike text) might be a "fixed-width" type, but that is not so. Both are variable-length types, varchar(255) just adds a maximum length check:
• Would index lookup be noticeably faster with char vs varchar when all values are 36 chars

_{The use of varchar(255) in a table definition typically indicates a lack of understanding of the Postgres type system. The architect behind it is most probably not a native speaker - or the layout has been carried over from another RDBMS like SQL Server where this used to matter.}

• Your most expensive query SELECT COUNT(*) FROM articles does not even consider row data at all, only the total size matters indirectly. Counting all rows is costly in Postgres due to its MVCC model. Maybe an estimate is good enough, which can be had very cheaply?
• Fast way to discover the row count of a table

(Pretend disk space isn't an issue.)

Disk space is always an issue, even if you have plenty. The size on disk (number of data pages that have to be read / processed / written) is one of the most important factors for performance.

Where can I learn more about the internals of the Postgres DB engine?

The info page for the tag postgres has the most important links to more information, including books, the Postgres Wiki and the excellent manual. The latter is my personal favorite.

Your third query has issues

SELECT * FROM articles WHERE user_id = $1 ORDER BY published_date DESC LIMIT 1;

ORDER BY published_date DESC, but published_date can be NULL (no NOT NULL constraint). That's a loaded foot-gun if there can be NULL values, unless you prefer NULL values over the latest actual published_date.

Either add a NOT NULL constraint. Always do that for columns that can't be NULL.
Or make that ORDER BY published_date DESCNULLS LAST and adapt the index accordingly.

"articles_user_id_published_date_idx" btree (user_id, published_date DESC NULLS LAST)

Details in this recent, related answer:

• Extremely slow query on indexed column in Postgres

Convert published_date to an actual date

While 'published_date' is always rounded, it's effectively just a date which occupies 4 bytes instead of 8 for the timestamp. You would best move that up in the table definition to come before the two timestamp columns, so you don't lose the 4 bytes to padding:

...
body           | text
published_date | date   --     <---- here
created_at     | timestamp without time zone
updated_at     | timestamp without time zone

Smaller on-disk storage does make a difference for performance.

• Configuring PostgreSQL for read performance

More importantly, your index on (user_id, published_date) would now just occupy 32 bytes per index entry instead of 40, because 2x4 bytes do not incur extra padding. And that would make a noticeable difference for performance.

Aside: this index is not relevant to the demonstrated queries. Delete unless indexes unless used elsewhere:

"index_articles_on_published_date" btree (published_date)