PgConf.Russia 2016

B-tree is the most widely used index type in PostgreSQL. This data structure and concerned algorithms are developed about forty years ago. But there is still an area for optimisations. In this presentation I'm going to talk about B-tree data structure, and its features important for the optimal index usage. Furthermore, I'll present a couple of new features which are expected to be included in PostgreSQL 9.6 release.

When new versions of Postgres are released most of the attention is focused on new features. Inevitably a release note claiming speed improvements seems relatively mundane and doesn't provide the compelling argument for upgrading. However the reality is that these speed improvements represent pain points that have been identified and solved.

Reviewing the changes to the sort code in Postgres over the last 10 years clearly shows the kinds of problems users have run into. As usage patterns changed over years, databases scaled up, and hardware changed new problems arose and drove further development to solve them.

Upcoming changes in 9.5 and 9.6 will dramatically change the experience further. Making sorting UTF8 and other encodings less of a problem and handling scaling to larger machines with many processors and memory cache more effectively.

Multicorn is a generic Foreign Data Wrapper which goal is to simplify development of FDWs by writing them in Python.

We will see:

• what is an FDW what Multicorn is trying to solve how to use it, with a brief tour of the FDWs shipping with Multicorn.
• how to write your own FDW in python, including the new 9.5 IMPORT FOREIGN SCHEMA api.
• the internals: what Multicorn is doing for you behind the scenes, and what it doesn't

After a presentation of FDWs in general, and what the Multicorn extension really is, we will take a look at some of the FDWs bundled with Multicorn.

Then, a complete tour of the Multicorn API will teach you how to write a FDW in python, including the following features:

• using the table definition
• WHERE clauses push-down
• output columns restrictions
• influencing the planner
• writing to a foreign table
• IMPORT FOREIGN SCHEMA
• ORDER BY clauses pushdown
• transaction management

This will be a hands-on explanation, with code snippets allowing you to build your own FDW in python from scratch.