PgConf.Russia 2019

To migrate to a PostgreSQL/Postgres Pro we need multi-core servers to be carefully tuned for correct parallelism. What settings make multi-terabyte installations work fast and correctly?

We will share our PostgreSQL/Postgres Pro on BullSequana S and Bullion S servers testing experience.

The features of this hardware platform which are crucial for high-loaded configurations
• Multi-core Scale-up servers and PostgreSQL/Postgres Pro
• Results of stress testing of PostgreSQL/Postgres Pro running on the equipment.

So you finally have your database model for your application and you fill it in with current data. How do you keep it up to date? While INSERT may still be transparent, UPDATE and DELETE will overwrite your previous data, so you won't be able to reproduce them. Cloning the whole huge content for each minor update is not an option. For rich and complex data about hundreds of thousands of power generators in Germany and worldwide, I built a model using range data types in recent PostgreSQL which allows me to insert, update and delete data while granting the full access to the whole state of the database at any historical moment. I'll present a very simplified version of the database so the audience will be immediately able to apply it for their cases. I'll also show a few tricks in Python and Psycopg2 that will allow a whole team to prepare, review, and deploy all revisions to this database without merge conflicts. And I'll give a few ideas on how to retrieve this data efficiently.

This case study walks participants through a case where we decided to embark on a data recovery effort. This talk is applicable to all users, from novices to advanced PostgreSQL database administrators. Beginners will get an understanding of what data recovery is and is not, what expectations to have going into it, and how to work with contracted experts in order to ensure the best possible outcome, while more advanced users and experts will also get a fair bit out of the technical aspects of the case study.

While the talk will emphasize non-technical operational aspects of data recovery, it will also include discussions of the internals of PostgreSQL we had to work with, as well as how we went about approaching difficulties so that we could retrieve the data we hoped to.

This talk will represent a new platform of Distributed Control System for Nuclear Power Plant operation. Participants will learn about control system for very complicated automation objects. In a hard real time node more than 150 special subsystems are operating in order to control various technological processes of nuclear power plant (NPP), such as reactor control system for more than 1000 MW power unit with a turbine weighing more than 2000 tons. More than 100K of data gained from sensors are resulting in up to 500K of parameters representing 5 branches of physical processes: neutron kinetics, hydrodynamics, chemistry and radiochemistry, and physics of strength. Deviations may cause the whole system to become a huge DDoS source made of useful diagnostic information which is always much larger than the network and hardware are capable to manage. This may lead to normal operation failure. The talk will reveal the approaches to solve the issue.

You will learn about hardware and software architecture of such systems, about backup and replication, data redundancy and technological diversity. How to manage high loads, what is QoS, and what will happen in case of normal operation system failure, as for example was at Fukushima. But, hey, there should be a talk about coding! So, no SSD and HDDs, only InMemory, data structures from tens of millions of elements, and forget about processor cache as it does not work. Imagine your newest 4-generation Xeon has lost all the advantages and turned into a "pumpkin", so let's roll up your sleeves and examine timings, synchronicity, and try to make the most of your hardware, discovering the weakest link from processor, operating system and a network.