PgConf.Russia 2017

Using PostgreSQL since 2003, we went all the way from a database of a couple of GB to a cluster of more than 5TB. At the moment, we have more than 700 tables and about 1500 stored procedures. We are ready to share with you the following: - Problems encountered at different development stages and how we resolved them. - Best practices in database administration. - Our own extension to work with several closely related databases. - Best known methods and tools that enable our several teams to work together without interference. - How we set up test equipment of different types. And, of course, we'll talk about optimization, and how we identify bottlenecks and high-load use cases.

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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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Full text search in PostgreSQL is probably the most advanced one among relational DBMS. This tutorial will explain how to setup full text search configurations and dictionaries and how to build a ful text search system using an example of a simple popular science web site, with demonstration of various ranking functions. Also I will tell about new RUM index, which allows to accelerate execution of some kinds of full text queries and implements a new improved ranking function.

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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