PgConf.Russia 2019

Shared_buffers = 25% – is it too much or not enough? Or it's the right value?

How can we ensure that this – pretty much outdated – recommendation suit well our needs?

It is time to start apply enterprise-level approach to tuning postgresql.conf. Not using various blind auto-tuners or advices from old articles and blog posts, but based on the following two aspects:

1. comprehensive database experiments, conducted in automated fashion, repeated multiple times in conditions as close to production as possible, and
2. deep understanding of DBMS and OS internals.

Using Nancy CLI (https://gitlab.com/postgres.ai/nancy) we will consider a concrete example: infamous shared_buffers, under various circumstances, in various projects. We will try to figure out, how to optimize this settings for given infrastructure, database, and workload.

A major responsibility of a database engine is to convert a declarative SQL query to an efficient execution plan, employing various methods to scan and join the relations. There is always a development effort to improve this area. What clever execution plans can PostgreSQL generate, what's new in version 11 and what is in development? To name a few things, the joins are optimized by removing unneeded outer and inner joins, and reducing joins from outer and semi to inner. There is work to enable merge joins on inequality and range overlap, and to improve join selectivity estimates with multi-column statistics. When it comes to scanning a single relation, covering indexes allow to use index-only scans more often. Incremental sort and more precise estimation of sorting costs help generate better paths when sorted output is required, e.g. when using GROUP BY and ORDER BY or performing merge joins. This talk aims to give an overview of such optimizations that already exist and that are being developed now.

In this master class, I will take you step-by step through a major upgrade of PostgreSQL. Through our practice we see a lot of different PostgreSQL servers in production environment and often, almost too often teams who once made PostgreSQL their database of choice never update it following the initial installation. The are many different reasons for it, the result, however, is the same - they all miss out on the new useful features of the newer releases and reduced database performance.
The goal of my masterclass is to equip attendees with necessary tools for performing PostgreSQL upgrade. I will take you through each step of the major upgrade and will dive into each executed command. I will also explain the particular order in which I perform an upgrade and explain the consequences of not following this order or missing a particular step. We will perform an upgrade of PostgreSQL 9.0 to 11. My hope is that following this masterclass number of outdated PostgreSQL database will reduce since participants will then go back to their databases and make sure that they are running the most recent version.

In this talk we will have a look at the details of autovacuum's implementation and see what kind of practical implications they have. The talk will also provide a short overview of patches for autovacuum that are currently being considered by the developer community and that may be included in newer versions of PostgreSQL.