PGConf.Russia 2018

DBeaver is the Universal Databases Manager. We creating DBeaver using Open Source Software model. We pay special attention to the PotgreSQL because of its capabilities, popularity and OSS nature. We will talk about DBeaver evolution and structure, will demonstrate the basic functionality. We are going to cover challenges of PostgreSQL client creation. Also we will discuss requirements management model and interaction with the PostgreSQL community. We will show in details how to debug the PL/pgSQL stored procedures interactively. We are going to introduce some new features of the nearest DBeaver release and to share our plans.

Developers are often challenged to deliver results that are hard to implement using simple SQL queries. Fortunately, complex SQL capabilities exist in the SQL standards — common table expressions and window functions.

SQL is a declarative language, meaning the user submits an SQL command and the database determines the optimal execution. Common Table Expressions (CTEs) allow queries to be more imperative, allowing looping and processing hierarchical structures that are normally associated only with imperative languages.

Normal SQL queries return rows where each row is independent of the other returned rows. SQL window functions allow queries to return computed columns based on values in other rows in the result set.

This tutorial will help developers use CTE queries in their applications and allow operations that normally could only be done in application code to be done via SQL queries. It also explains the many window function facilities and how they can be used to produce useful SQL query results.

Video

Part I «Programming the SQL Way with CTE»

Part II «Postgres Window Magic»

The speaker will share his experience of transferring high-loaded game projects that were originally developed to work with MySQL into PostgreSQL. Problems that had been expected and ones that were actually faced. Tricky bugs that were found in production servers after the migration. Solutions that were used to deal with problems. PostgreSQL features that were very useful and desirable ones that were missing.

I would like to share experience in runing PostgreSQL in dockerized environments, describe the specific issues and tools you will need to solve them.

• Which problems could be solved by Docker for PostgreSQL, e.g. PostgreSQLPro.9.6
• Work of IT team with Docker in development, testing and production environments
  • Using image repository and build servers for image testing
• Issues in production environment:
  • With network activity
  • With persistent repositories for Docker
  • With additional services
  • With load balancing and fail-safety
• Running PostgreSQL-base applications, such as:
  • SonarQube
  • Gitlab
  • 1С platform