PgConf.Russia 2017

The talk will describe how we have implemented storage of large tables (+1 billion rows per day). The project exists in production 2 years. The total amount of data - 300 Tb (25 PostgreSQL servers * 2 Data Center). I'll tell about mistakes in organization of large tables storage in the initial phase of the project, and how these mistakes were corrected. I'll also talk about how to organize the data rotation and archiving. I voiced questions about what we were missing in PostgreSQL 9.4 out of what appeared in the 9.5 and 9.6. And also, what new features we are waiting for new releases of PostgreSQL.

Currently, to execute SQL queries PostgreSQL uses interpreter, which implements Volcano-style iteration model. At the same time it’s possible to get significant speedup by dynamically JIT-compiling query “on-the-fly”. In this case it’s possible to generate code that is specialized for given SQL query, and perform compiler optimizations using the information about table structure and data types that is already known at run time. This approach is especially important for complex queries, which performance is CPU-bound.

A summary of what the Postgres Professional company has achieved in its two-year history:

• Our achievements in PostgreSQL development.
• What is the Russian Postgres Pro DBMS, and how is it related to PostgreSQL?
• What is Postgres Pro Enterprise, and why Enterprise?
• What about trainings and certification?

VIDEO

We will discuss some tricks and patterns while developing web-application architecture based on ORM technology with Postgresql functions implementation with Python Django as an example. Also we will consider some ways of building the business logic inside a database with keeping Django framework opportunities and implementation of it's built-in admin panel.

VIDEO