PgConf.Russia 2019

Python may not be the fastest programming language on the CPU, but its fast and easy development saves a lot of costs between the keyboard and the chair. Since database clients spend most of their time waiting for a response from the database server, Python's asynchronous functionality available in the recent versions (3.5+) may help to optimize the application's runtime considerably by working on something else while server's response is being prepared. The asynchronous interface between Python and PostgreSQL is called "asyncpg". In the workshop we'll explore this library and write a short application using some of its useful features.

PostgreSQL provides possibility to create temporary tables. Though a temporary table is accessible only to a single session and is removed at the end of the session, all information about it is stored in the system catalogs of PostgreSQL. This is related to several issues, which make it difficult or impossible to use temporary tables in some cases. There are attempts to solve this feature, including in our company. But they have not yet succeeded, mainly because of the PostgreSQL engine. In the talk I want to tell about simple and small pg_variables extension. It allows you to create table variables along with scalar ones. I will tell how it can replace temporary tables, what advantages and disadvantages it has.

Sometimes problems arise during Postgres operation, and the faster they are identified and resolved, the happier users eventually will be. pgCenter is a set of CLI powerful utilities for troubleshooting in the "here and now" mode. In the talk I will show how to use pgCenter for efficient troubleshooting, the directions in which to search, and how to respond to certain problems, in particular how to:

• check if Postgres is in the normal state;
• identify promptly the faulty clients and stop them;
• reveal too heavy queries;
• and other tips and tricks of pgCenter.

Magic tricks followed by exposure (1C+PG):

• Focus number one. How to convince the accounting department to buy a new server.
• Focus number two. How to show that MS SQL is faster than PostgreSQL.
• Focus number three. How to show that PostgreSQL is faster than MS SQL Server.