PgConf.Russia 2017

Tencent, based in China, is one of the world's largest companies in the social networking space. This talk discusses how Tencent modified the code of Postgres-XC to meet their internal payment system requirements

Nowadays one can make a decent urban research based simply on public datasets, making interesting and unexpected insights. In the presentation, I'll show examples of these calculations in PostGIS, the industry standard de-facto.

But just PostGIS is not enough. You need tools to import, verify and visualize the data. It's critically important to visualize the data live, to debug your calculations and shorten iterations. I'll describe all these steps:

1. Collecting the data: public API, OpenStreetMap; direct user input.
2. 3rd party APIs for calculations.
3. Visualization of GIS and other sorts of data: QGIS, Matplotlib, Zeppelin integrated with PostGIS.
4. Debugging the calculations: live visualization (Arc, QGIS, NextGIS Web)
5. Scripting and minimizing the chores: Makefile, Gulp

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).

VIDEO

Part 1

Part 2

Part 3

Part 4

Input-output (IO) performance issues have been on DBAs’ agenda since the beginning of databases. The volume of data grows rapidly and time is of an essence when one needs to get necessary data fast from the disk and, more importantly, to the disk.

For most databases it is relatively easy to find checklist of recommended Linux settings to maximize IO throughput and, in most cases, this checklist is indeed good enough. It is however essential always to understand how the optimisation of those settings actually works, especially, if you run into corner cases.