PgConf.Russia 2019

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.

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.

This report focuses on the continuation of transferring our ECM “Priority” from MS SQL to Postgres. Technical solutions, issues of rewriting from T-SQL to plpgsql, optimization of the effective code and moving data will be covered. Additionally, there will be considered aspects of pgplsql performance testing to find the “bad code” of pgplsql as a candidate for optimization. The main objective of the presentation is to answer the question: "We have it in T-SQL - how to transfer it in PG?". The report is intended for junior Postgres developers and is a continuation of the previous report made at the conference in 2017(https://youtu.be/v6_4Szr8t14).

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.