PgConf.Russia 2019

While doing development of one of our project we were asked to build HA database using Postgres, geographically distributed.

First our choice was obvious, we started to work with big 3 cloud providers, but soon it was quite understand that everything costs big enough for us. Also there were a bunch of incompatibilities with unsupported extensions as well as londiste replication we were heavily used.

I will talk about why we chose patroni, what types of problem we faced with and patroni's special features can dramatically simplify deploy and everyday usage.

As is often seen in OLAP and batch processing workloads, the more complex a query (containing many joins, filters, aggregates), the more there is a possibility of row count estimation errors, which leads to planner choosing an inefficient execution plan.

To address that problem, I developed a tool called pg_plan_advsr as a PostgreSQL extension, which corrects the estimation errors by repeatedly feeding back the information collected during query execution to the planner.

The tool has three features:

1. Automatic plan tuning by repeatedly feeding execution information to planner
2. Preserve all plans generated during plan tuning in a history table
3. Create and store optimizer hints to be able to reproduce plans generated during tuning process

I verified the effectiveness of pg_plan_advsr by enabling it when running the join order benchmark (JOB) against PG 10.4 and observed its execution time shortening to 50% of the original. Therefore, it is useful for user who would like to do plan tuning for OLAP and batch processing.

I will talk about the following things in this presentation:

• Principles behind pg_plan_advsr and its architecture
• Detailed information about the measurements done with JOB
• Possible future enhancements
• Using aqo and pg_plan_advsr together (experimental)

Postgres is known for it extensibility, which made it the universal database, that means it can meet the requirements of practically any project. Many extensions are well-known and widely used, for example, PostGIS extension - de-facto standard of open source GIS, hstore - an extension for storing and manipulation of arbitrary key/value pairs. I will talk about less known but useful PostgreSQL extensions, which provides a new functionaliy and/or improve the performance of PostgreSQL.

PostgreSQL was designed to be extensible, it provides an API to application developers to extend PostgreSQL functionality and/or improve the performance for specific data and workloads. It is important that there is no need of having expertise of core developers, and these new functionality could be added online without restarting of database server. Application developer can create various database objects, such as functions, data types, operators, indexes, and even new access methods.

I will present my choice of two extensions out of hundreds:

vops - greatly improves the performance of Postgres for OLAP queries using vector operations, pg_variables - provides session variables for storing scalars and relations, useful for generating reports on read-only replicas.

Wide usage of Common Table Expression queries considered as a core paradigm for implementing the Business Logic for high loaded web applications development based on PostgreSQL functions.