PgConf.Russia 2017

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.

This tutorial shows how to properly monitor PostgreSQL. We will discuss the mamonsu utility, see how to configure it, examine its hidden features and learn how to extend them.

Currently, to execute SQL queries PostgreSQL uses interpreter, which implements Volcano-style iteration model. At the same time it’s possible to get significant speedup by dynamically JIT-compiling query “on-the-fly”. In this case it’s possible to generate code that is specialized for given SQL query, and perform compiler optimizations using the information about table structure and data types that is already known at run time. This approach is especially important for complex queries, which performance is CPU-bound.

Partitioning is a long-awaited feature in PostgreSQL. Although Postgres supports partitioning via inheritance, this approach has some disadvantages, such as the need to manually create partitions and support triggers, significant planning overhead, and no query execution optimizations. In this talk, we’ll tell you about the pg_pathman extension we are developing. pg_pathman supports HASH and RANGE partitioning, performs planning and execution optimizations, supports fast insert by using Custom Node instead of triggers, provides functions for partition management (add, split, merge, etc.), supports FDW, non-blocking data migration, and more. We'll also speak about pg_pathman integration with Postgres Pro Enterprise Edition and Oracle-like syntax support for partitioning. Finally, we'll discuss new partitioning capabilities in PostgreSQL 10, the already implemented features and further development plans.

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