PGConf.Russia 2018

Liquibase is a very convenient tool for sequential database migration, used both on our projects and in a large number of other projects and frameworks. It allows you to keep the code of the database together with the application code in VSC, track the attempts of repeated migrations and much, much more. But sooner or later the project grows, the data occupy terabytes, and liquibase still rolls the migration sequentially.

We could not afford to deploy migrations for 100 hours and came up with a framework for liquibase that expanded its capabilities and allowed to execute a whole series of scripts in parallel or to split one large migration into small partitions and migrate them in parallel.

PostGIS is a spatial extension to PostgreSQL that enables spatial datatypes, access methods and a set of functions to perform geometric operations on them.

Typically PostGIS is used to select a small subset of a big static dataset. In this talk I'll cover issues that arise when working with big dynamic data flows, and ways to resolve them, on examples that we've met developing Juno ride sharing service backend.

It's not a secret for anyone that statistics can not be transferred with a major upgrade. For small and not heavily loaded databases this is not a problem, you can quickly collect new statistics. But we have databases with a volume of about 5TB and a load of about 100k rps, for which it became a big problem: taking off without statistics, the replicas could not even replay WAL. In my report I'll tell you what tricks we went to upgrade these databases with requirements of 100% read only availability, about what mistakes were made, and about how these errors were painfully corrected. The result of these errors was the extension called "pg_dirty_hands", in which we will collect various hacks, which can be last resort to repair data corruption.

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.