PgConf.Russia 2016

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.

Common Java wisdom is to use PreparedStatements and Batch DML in order to achieve top performance. It turns out one cannot just blindly follow the best practices. In order to get high throughput, you need to understand the specifics of the database in question, and the content of the data.

In the talk we will see how proper usage of PostgreSQL protocol enables high performance operation while fetching and storing the data. We will see how trivial application and/or JDBC driver code changes can result in dramatic performance improvements. We will examine how server-side prepared statements should be activated, and discuss pitfalls of using server-prepared statements.

Postgresql's buffer manager has parts where it's showing its age. We'll discuss how it currently works, what problems there are, and what attempts are in progress to rectify its weaknesses.

• Lookups in the buffer cache are expensive
• The buffer mapping table is organized as a hash table, which makes efficient implementations of prefetching, write coalescing, dropping of cache contents hard
• Relation extension scales badly
• Cache replacement is inefficient
• Cache replacement replaces the wrong buffers

More than 300.000 developers use technology platform "1C:Enterprise" as a main development tool. I'll tell you about architecture and features that made "1C:Enterprise" one of the most popular development environment in Russia and CIS and about growing popularity of PostgreSQL amongst 1C users.