PGConf.Russia 2018

«KNOPKA» («The button»), the largest outsourcing of accounting, will tell you about your experience of transferring 500Gb of 1C Fresh databases to PostgreSQL. The report touches on the choice of DBMS and the fight against stereotypes, where we started and how developed the use of PostgreSQL, the approaches to backup and recovery of information security, our current performance of DBMS and 1C, a look into the future. Let us share why we believe that 1C + PostgreSQL is simple, reliable and fast.

PostgreSQL looks very competitive with other mainstream databases on OLTP workload (execution of large number of simple queries). But on OLAP queries, requiring processing of larger volumes of data, DBMS-es oriented on analytic queries processing can provide an order of magnitude better speed. The following factors limit Postgres OLAP performance:

• Unpacking tuple overhead (tuple_deform)
• Interpretation overhead (Postgres executor has to interpret query execution plan)
• Abstraction penalty (support of abstract data types)
• Pull model overhead (operators are pulling tuples from heap page one-by-one, resulting numerous repeated accesses to the page)
• MVCC overhead (extra per-tuple storage + visibility check cost)

All this issues can be solved using vectorized executor, which proceed bulk of values at once. In this presentation I will show how vector operations can be implemented in Postgres as standard Postgres extension, not affecting Postgres core. The approach is based on introducing special types: tile types, which can be used instead of normal (scalar) types and implement vector operations. Postgres extension mechanism, such as UDT (user-defined type), FDW (foreign data wrappers), executor hooks are used to let users work with vectorized tables almost in the same way as with normal tables. But more than 10 times faster because of vector operations.

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

It’s 3am. Your phone rings. PostgreSQL is down, you need to promote a replica to master. Why the h**l isn’t this automatic?

If you thought of this before, you want automatic High Availability (HA). Don’t miss this talk! We will enter the world of Modern PostgreSQL HA.

Good news, there are several new, “modern” solutions for PostgreSQL HA. However, there are several solutions and it's not easy to pick one. Most require non-trivial setups, and there are many small caveats about HA like how to provide entry points to the application, HA correctness, HA vs. read scaling, external dependencies, interaction with cloud environments, and so forth.

Join this talk to master PostgreSQL HA and how to deploy it on current times.