PgConf.Russia 2019

To migrate to a PostgreSQL/Postgres Pro we need multi-core servers to be carefully tuned for correct parallelism. What settings make multi-terabyte installations work fast and correctly?

We will share our PostgreSQL/Postgres Pro on BullSequana S and Bullion S servers testing experience.

The features of this hardware platform which are crucial for high-loaded configurations
• Multi-core Scale-up servers and PostgreSQL/Postgres Pro
• Results of stress testing of PostgreSQL/Postgres Pro running on the equipment.

This case study walks participants through a case where we decided to embark on a data recovery effort. This talk is applicable to all users, from novices to advanced PostgreSQL database administrators. Beginners will get an understanding of what data recovery is and is not, what expectations to have going into it, and how to work with contracted experts in order to ensure the best possible outcome, while more advanced users and experts will also get a fair bit out of the technical aspects of the case study.

While the talk will emphasize non-technical operational aspects of data recovery, it will also include discussions of the internals of PostgreSQL we had to work with, as well as how we went about approaching difficulties so that we could retrieve the data we hoped to.

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.

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.