Blog , p.3

May 13, 2021   •   PostgreSQL

So, we got acquainted with the structure of the buffer cache and in this context concluded that if all the RAM contents got lost due to failure, the write-ahead log (WAL) was required to recover. The size of the necessary WAL files and the recovery time are limited thanks to the checkpoint performed from time to time.

In the previous articles we already reviewed quite a few important settings that anyway relate to WAL. In this article (being the last in this series) we will discuss problems of WAL setup that are unaddressed yet: WAL levels and their purpose, as well as the reliability and performance of write-ahead logging.

April 23, 2021   •   PostgreSQL

We already got acquainted with the structure of the buffer cache — one of the main objects of the shared memory — and concluded that to recover after failure when all the RAM contents get lost, the write-ahead log (WAL) must be maintained.

The problem yet unaddressed, where we left off last time, is that we are unaware of where to start playing back WAL records during the recovery. To begin from the beginning, as the King from Lewis Caroll's Alice advised, is not an option: it is impossible to keep all the WAL records from the server start — this is potentially both a huge memory size and equally huge duration of the recovery. We need such a point that is gradually moving forward and that we can start the recovery at (and safely remove all the previous WAL records, accordingly). And this is the checkpoint, to be discussed below.

April 15, 2021   •   PostgreSQL

Last time we got acquainted with the structure of an important component of the shared memory — the buffer cache. A risk of losing information from RAM is the main reason why we need techniques to recover data after failure. Now we will discuss these techniques.

April 1, 2021   •   PostgreSQL
WAL in PostgreSQL: 1. Buffer Cache
March 19, 2021   •   PostgreSQL

We started with problems related to isolation, made a digression about low-level data structure, discussed row versions in detail and observed how data snapshots are obtained from row versions.

Then we covered different vacuuming techniques: in-page vacuum (along with HOT updates), vacuum and autovacuum.

Now we've reached the last topic of this series. We will talk on the transaction id wraparound and freezing.

Transaction ID wraparound

PostgreSQL uses 32-bit transaction IDs. This is a pretty large number (about 4 billion), but with intensive work of the server, this number is not unlikely to get exhausted. For example: with the workload of 1000 transactions a second, this will happen as early as in one month and a half of continuous work.

But we've mentioned that multiversion concurrency control relies on the sequential numbering, which means that of two transactions the one with a smaller number can be considered to have started earlier. Therefore, it is clear that it is not an option to just reset the counter and start the numbering from scratch.

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March 12, 2021   •   News

PGConf.Online 2021 wrap-up: 57 talks, 30 international speakers, 2000+ registrants!

PGConf.Online wrapped up 10 days ago, and we want to share some important stats with you. We were glad to have welcomed 2000+ registrants this year with 700-900 of them joining us online each day! The total attendance/registration rate for all three days was near 75%, which is amazing!

March 8, 2021   •   News

Celebrating Women Who Code in Postgres Pro

In early March, before International Women’s Day, we asked our female tech professionals a few questions and were surprised by some of them providing us answers :) Let’s celebrate women who code working here at Postgres Pro and have a look at what they are up to!

 

February 18, 2021   •   News

Postgres Professional is now sponsoring Psycopg development!

Postgres Professional has become one of the main sponsors backing the development of the Psycopg library, the most popular PostgreSQL adapter for the Python programming language.

February 9, 2021   •   PostgreSQL

To remind you, we started with problems related to isolation, made a digression about low-level data structure, discussed row versions in detail and observed how data snapshots are obtained from row versions.

Then we explored in-page vacuum (and HOT updates) and vacuum. Now we'll look into autovacuum.

Autovacuum

We've already mentioned that normally (i. e., when nothing holds the transaction horizon for a long time) VACUUM usually does its job. The problem is how often to call it.

If we vacuum a changing table too rarely, its size will grow more than desired. Besides, a next vacuum operation may require several passes through indexes if too many changes were done.

If we vacuum the table too often, the server will constantly do maintenance rather than useful work — and this is no good either.

Note that launching VACUUM on schedule by no means resolves the issue because the workload can change with time. If the table starts to change more intensively, it must be vacuumed more often.

Autovacuum is exactly the technique that enables us to launch vacuuming depending on how intensive the table changes are.

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February 3, 2021   •   News

Postgres Professional at FOSDEM 2021

It’s this time of the year again, and FOSDEM is coming! In 2021, Postgres Professional is really well-represented in the PostgreSQL devroom, as we have 5 talks accepted by the Committee. Let’s take a look at all presentations to be given by our team at this conference.

January 18, 2021   •   PostgreSQL

We started with problems related to isolation, made a digression about low-level data structure, then discussed row versions and observed how data snapshots are obtained from row versions.

Last time we talked about HOT updates and in-page vacuuming, and today we'll proceed to a well-known vacuum vulgaris. Really, so much has already been written about it that I can hardly add anything new, but the beauty of a full picture requires sacrifice. So keep patience.

Vacuum

What does vacuum do?

In-page vacuum works fast, but frees only part of the space. It works within one table page and does not touch indexes.

The basic, "normal" vacuum is done using the VACUUM command, and we will call it just "vacuum" (leaving "autovacuum" for a separate discussion).

So, vacuum processes the entire table. It vacuums away not only dead tuples, but also references to them from all indexes.

Vacuuming is concurrent with other activities in the system. The table and indexes can be used in a regular way both for reads and updates (however, concurrent execution of commands such as CREATE INDEX, ALTER TABLE and some others is impossible).

Only those table pages are looked through where some activities took place. To detect them, the visibility map is used (to remind you, the map tracks those pages that contain pretty old tuples, which are visible in all data snapshots for sure). Only those pages are processed that are not tracked by the visibility map, and the map itself gets updated.

The free space map also gets updated in the process to reflect the extra free space in the pages.

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January 12, 2021   •   News

Postgres Pro Standard 13.1.1 was released by the Postgres Professional team on December 18, 2020. This release is based on the corresponding version of the upstream PostgreSQL DBMS and includes a number of enhancements listed in this announcement.

December 18, 2020   •   PostgreSQL

Just to remind you, we already discussed issues related to isolation, made a digression regarding low-level data structure, and then explored row versions and observed how data snapshots are obtained from row versions.

Now we will proceed to two closely connected problems: in-page vacuum и HOT updates. Both techniques can be referred to optimizations; they are important, but virtually not covered in the documentation.

In-page vacuum during regular updates

When accessing a page for either an update or read, if PostgreSQL understands that the page is running out of space, it can do a fast in-page vacuum. This happens in either of the cases:

  1. A previous update in this page did not find enough space to allocate a new row version in the same page. Such a situation is remembered in the page header, and next time the page is vacuumed.
  2. The page is more than fillfactor percent full. In this case, vacuum is performed right away without putting off till next time.
December 7, 2020   •   PostgreSQL

Hacking PostgreSQL 13 Webinar: Questions & Answers

To get things done before 2020 is over, I decided to publish my blog post with answers to your questions from our webinar on PostgreSQL 13 that we hosted in October. I’m still looking into release 13 and will soon give another talk on PG13 monitoring-related features that became available in this version of PostgreSQL. For now, let’s go through the webinar questions.

December 4, 2020   •   PostgreSQL

After having discussed isolation problems and having made a digression regarding the low-level data structure, last time we explored row versions and observed how different operations changed tuple header fields.

Now we will look at how consistent data snapshots are obtained from tuples.

What is a data snapshot?

Data pages can physically contain several versions of the same row. But each transaction must see only one (or none) version of each row, so that all of them make up a consistent picture of the data (in the sense of ACID) as of a certain point in time.

Isolation in PosgreSQL is based on snapshots: each transaction works with its own data snapshot, which "contains" data that were committed before the moment the snapshot was created and does not "contain" data that were not committed by that moment yet. We've already seen that although the resulting isolation appears stricter than required by the standard, it still has anomalies.