Do fixed-width rows improve PostgreSQL read performance?

I have a table articles:

                                                       Table "articles"
     Column     |            Type             |                     Modifiers                      | Storage  | Stats target | Description
----------------+-----------------------------+----------------------------------------------------+----------+--------------+-------------
 id             | integer                     | not null default nextval('articles_id_seq'::regclass) | plain    |              |
 user_id        | integer                     |                                                    | plain    |              |
 title          | character varying(255)      |                                                    | extended |              |
 author         | character varying(255)      |                                                    | extended |              |
 body           | text                        | default '--- []                                   +| extended |              |
                |                             | '::text                                            |          |              |
 created_at     | timestamp without time zone |                                                    | plain    |              |
 updated_at     | timestamp without time zone |                                                    | plain    |              |
 published_date | timestamp without time zone |                                                    | plain    |              |

Indexes:
    "articles_pkey" PRIMARY KEY, btree (id)
    "index_articles_on_published_date" btree (published_date)
    "index_rents_on_user_id" btree (user_id)
    "index_articles_on_user_id_and_published_date" btree (user_id, published_date)

We’re on Postgres 9.4.4. The machine has 3.5 GB of memory and 150 GB of disk space on an SSD.

_{Note: The ‘published_date’ is always rounded, by the application, to the nearest date. All hours/minutes/seconds are always 00. Legacy. Needs fixed. Etc.}

This table has hundreds of millions of articles. The table receives a great deal of read queries from (as many as 16) concurrent processes performing the following queries as quickly as our system will respond:

• a count of the total number of articles

  SELECT COUNT(*) FROM articles;
  

• a select of all articles published for a given user

  SELECT * FROM articles WHERE user_id = $1;
  

• a select of the most recently published article for a given user

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

I am finding that, with a large number of workers, these queries are quite slow. (At peak load, the first takes minutes to complete; the other two are on the order of 10 seconds.) In particular, it seems that queries are being enqueued.

The question

In the abstract, do tables with only fixed width values perform read queries better than those with varying widths? (Pretend disk space isn’t an issue.) In my case, I’m wondering if I would see a performance improvement if I were to extract the ‘body’ text field to a separate table and transform the character varying fields into fixed width character fields.

I admit the question is a bit cargo cult-y. I simply don’t know enough about the internals of the Postgres DB engine to construct an informed hypothesis. I do intend to perform real experiments with different schemas and configurations but I’d like to have a solid mental model of how Postgres actually works before I go much further.

Related question

Where can I learn more about the internals of the Postgres DB engine? I’ve Googled variations of the above question with little success. What are the correct terms to use for this search? Does this level of documentation exist only in source and the minds of Postgres DBAs? I also humbly invite the suggestion of good books on the topic.

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 2×4 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)