PgConf.Russia 2019

As any ordinary software developers, we just pursued a goal to develop a system robust for high loads, and even succeeded. The system architecture was fine, but the data volume was keeping increased and revealed the painful issues and errors that nobody had expected. We faced very strange queries seemed to be unbelievable. In my short talk I would like to share sad experience of arised-from-nothing high loads in DBMS and solving the challenge.

At pgconf’17 I talked about our analytics systems based on PostgreSQL. Afterwards we looked at hadoop, s3, presto, vertica, and other frights. Finally we stopped to suffer nonsense and just completed PostgreSQL with ready Greenplum and Clickhouse. As a result, we achieved amazing performance, fast migration, easy maintenance, reliability and horizontal scalability. We enabled to recover the system after fault in two commands, decreased infrastructure costs and expanded functionality due to ANSI SQL, MPP and In-memory. All within the open-source and full SQL paradigm. We called the product GreenHouseSQL, which is our inner whole cycle data platform. In the talk we will show the beauty of solution internals, explain the advantages and flaws, tips and tricks of starting with Greenplum, as well as why do we need Clickhouse, what is left to PostgreSQL, and eventually how does it all work.

IIn the world of programming, the creation of source code for databases "procedural extensions" is something solitary. Most DBMS offers procedural languages and "stored procedures" to create procedural extensions. In Postgres the number of supported procedural languages has already exceeded a dozen.

Traditionally, stored procedures have many applications: it is difficult to resist the attraction to perform a data operation directly in the storage, especially in the Enterprise development. This approach quickly leads to the spreading of the business logic and dramatically increases the cost of support and development of the system as a whole.

The life cycle of stored procedures makes it difficult to use standard Change Management tools and practices. It is necessary to adapt the operations upon the stored procedures to the standards of Change Management, yet staying within the comfortable development practices.

We'll look at the typical tasks of the procedural extensions development and discuss the solutions we are implementing in the Xobot IDE.

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 :-)