Готовим PostgreSQL в эпоху DevOps. Опыт 2ГИС

The dark age for PostgreSQL started at 2GIS after transitioning to the microservice architecture. Every team tried to cook database on their own — by installing instances, juggling versions, trying to code deployments with numerous tools or using manual operations. It was the right time to develop a “silver bullet” — a common set of tools to solve all the problems at once. We created our own cluster solution based on well-known PostgreSQL, repmgr, pgbouncer and Barman. Despite of the complexity of our final solution, we developed a repeatable flexible deployment to accelerate postgresql cluster deployment and management. Also we deployed the our own cluster to consolidate all databases. It helped to eliminate team efforts for database management and focus on their main goals. Failover works, we tried it :-)

Обучение и сертификация: что нового и ближайшие планы

The first training course "DBA1. PostgreSQL Administration. Basic Course" was introduced by Postgres Professional in September 2015. The course was based on the then up-to-date version of PostgreSQL 9.4. A set of new courses has been introduced since then. In turn, the PostgreSQL database didn't stand still either.

The report will present the current line of courses for administrators and application developers. We will also show the roadmap for the near future, which includes specialist certification.

Настройка автопланировщика с использованием цикла обратной связи

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)

Секреты работы со службой Amazon RDS для PostgreSQL

Managed database services are gaining in popularity. In this session we look at how best to configure Amazon RDS for PostgreSQL and also look at common user operations of using RDS for PostgreSQL. We will also look beyond common user operations and into some specific optimizations related to upgrade, logical replication, performance, and reducing downtime.