PgConf.Russia 2017

Alexey will present technical details and share hands-on experience of extreme data normalization application for data infrastructure with exceptional parameters design and development. Extreme normalization-based data infrastructures has the following competitive advantages in comparison with market leaders: - Real-time data processing for 10 PB of data and more - 2-6 times better overall performance - 100% data consistency through total data landscape - Almost linear scalability - 4-10 lower cost of ownership - etc The abovementioned approach has been successfully utilized out of Russian market in telecommunication, retail, fin-tech, manufacturing (Industry 4.0, industrial IoT), and government institutions.

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In the data persistence layer, using PostgreSQL from the very start of development, we went all the way from a small cluster on a virtual machine to a multi-host system that provides near real-time processing of mixed OLTP/OLAP load. In this talk, I’m going to tell you about the main development stages of our analytical solution at the application and infrastructure levels, and describe the specifics of using PG that we encountered.

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It often happens that you already have PosgtreSQL in production, but you don’t have a DBA. To demystify the PostgreSQL database, I’ll tell you how to troubleshoot various problems while working with PosgtreSQL. We will try to understand how to answer "routine" questions of a typical system administrator: - Is everything OK with the database? - What consumes DB server resources? - What to optimize first to reduce resource consumption?

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I will tell you about why Postgres is first-choice product as a foundation for your BI system with classical OLAP workload. Briefly it will be said about existing open source BI solutions.

I will also describe specific of our architecture, why we chose snowflake scheme and how we are doing extract, transformation and load procedures. It will be mentioned about special Postgres tuning for OLAP and massive data bulkload workloads. Also I will let you know about Postgres usage as a column database with cstore_fdw by Citus and results achieved. Cons and problems of our approach will be described in the end of the talk.

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