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.

1. Why is it time to consider switching to PostgreSQL?
2. 1С and PostgreSQL interoperability.
3. Why should we start with Windows?
4. The first experience of migrating big enough 1С databases to Postgres.
5. Large-scale projects on high-load systems, in figures.

We will discuss some tricks and patterns while developing web-application architecture based on ORM technology with Postgresql functions implementation with Python Django as an example. Also we will consider some ways of building the business logic inside a database with keeping Django framework opportunities and implementation of it's built-in admin panel.

VIDEO

1. 1C:Enterprise 8 and PostgreSQL 9 interoperability 1.1 Changes in new 1C platform versions 1.2 v81c_data and v81c_index schemas 1.3 Sending 1C queries to SQL 1.4 Using 1C technological log events for PostgreSQL diagnostics
2. Analyzing queries that affect PostgreSQL performance 2.1 A free tool for automating log parsing 2.2 Pareto principle in action 2.3 Installation and configuration of the tool 2.4 A case study of query optimization 2.4.1 An issue in a PostgreSQL query 2.4.2 Finding non-optimal operations in a query 2.4.3 Resolving inefficiencies
3. PostgreSQL statistics for performance diagnostics 3.1 Comparing Postgres with MS SQL Server 3.2 Troubleshooting locks 3.3 Operating load diagnostics 4 Case studies by the gilev.ru team