PgConf.Russia 2017

Often it is enforced by the customer or even by law, to document the circumstances of the production of parts or lots. This talk is about the automated generation and storage of the corresponding administrative data and their correlation to measurements. Administrative data are entities like suppliers batch, article, serial number or production date. They are often to be exchanged with ERP systems.

Most of the main Skype services use a database platform based on PostgreSQL and other open-source technologies, such as Skytools, plProxy, pgBouncer, etc. This platform consists of several hundreds of servers with thousands of databases, which process hundreds of thousands of transactions per second. At the same time, the platform architecture allows its users (applications and their developers) to work with "logical" databases, without any worries about their real “physical” structure.

Our Skype Database Platform team is responsible for the database platform infrastructure. We develop automation systems for various processes that help us ensure service reliability and facilitate development, testing, and deployment of code. In this presentation, I will outline the database platform architecture, review its main components, and tell you about the methods we use in our every-day work to ensure high availability, scalability, replication, fault tolerance, and more.

Debugging, profiling, and tracing of the executed commands play an important role in development of any applications. This is also true for developing stored procedures in DBMS.

PostgreSQL offers various tools (both built-in and external) for these purposes.

In this talk, we will provide an overview of the available tools and their advantages and disadvantages, as well as a detailed demo of their use cases.

This talk is a part of a basic course for backend application developers (DEV1), which “Postgres Professional” company plans to announce in the near future.

Query optimization is an important problem, which solution has a great influence on DBMS performance, especially for complex queries. In this talk we consider PostgreSQL query optimizer and specifically cardinality estimation problem for correlated clauses, which is one of the most well-known drawbacks of query optimizers in general. In the talk we propose our solution for this problem which involves machine learning methods and is available for PostgreSQL 9.6 as an extension with a patch. We discuss the experimental evaluation, advantages, disadvantages, and fields of application of the proposed approach as well.

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