PgConf.Russia 2017

The talk will describe how we have implemented storage of large tables (+1 billion rows per day). The project exists in production 2 years. The total amount of data - 300 Tb (25 PostgreSQL servers * 2 Data Center). I'll tell about mistakes in organization of large tables storage in the initial phase of the project, and how these mistakes were corrected. I'll also talk about how to organize the data rotation and archiving. I voiced questions about what we were missing in PostgreSQL 9.4 out of what appeared in the 9.5 and 9.6. And also, what new features we are waiting for new releases of PostgreSQL.

Java is one of the most used languages when programming with PostgreSQL databases. Join this tutorial to learn or review the techniques to connect to postgres, best programming practices with JDBC, and to explore jOOQ, a mapper software that allows you to use the full power of SQL and postgres advanced query features while avoiding all the boilerplate code.

This tutorial is very practical: most of the time will be dedicated to iterate through code samples. It will cover:

• Introduction to Java and PostgreSQL
• Ways of connecting to PostgreSQL from Java (not only JDBC!)
• Introduction to JDBC. JDBC types. PostgreSQL JDBC
• Code demo: JDBC with PostgreSQL. From Java 1.4 to Java 8, best practices and code samples
• Code demo: jOOQ, a great mapper for PostgreSQL
• Java inside PostgreSQL
• The future of Java and PostgreSQL

About two-thirds of the tutorial will be dedicated to iterate over code samples and demos. All the code would be available from public open-source repositories and built with maven, so that any attendee may download it and build easily to play with it during the tutorial (although not required).

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Part 1

Part 2

Part 3

Part 4

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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MoySklad online service includes important component - semiautomatic database conversion framework. Its history and supported conversions are subject of this speech.

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