PgConf.Russia 2017

Database sharding enables a distribution of the database over a large number of machines, greatly improving performance. With the advent of Foreign Data Wrappers (FDW), it's possible to consider a database sharding in PostgreSQL with acceptable level of code changes using FDW. We've been working on enhancing around FDW infrastructure such as foreign table inheritance and pushing down so that PostgreSQL can execute the distributed query efficiently using FDW. In this talk, I'll cover what FDW-based sharding is and what use-cases it can cover. And then I'll demonstrate how to build sharding and describe our achievement of a FDW-based sharding in PostgreSQL community. Finally, I'll describe further enhancements to FDW such as Async Execution and Distributed Transaction Support.

With big data threads, even the upload of data to a database can often be problematic – apart from the data upload itself, you need to create indexes, perform VACUUM after the upload for correct Index-only scans, etc. From this talk, you will learn how to avoid most of such problems (if not all of them).

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This tutorial is about various applied JSON usage patterns and the related PostgreSQL functionality. We will discuss data storage in the JSON format, retrieving, changing, and searching such data, JSON features for simple SQL queries, as well as using JSON in stored procedures in different languages. You’ll get hands-on experience with some of the discussed problems on the provided virtual machines.

Experience we've got after 5 years of developing, deploying and improving BI system http://colibri365.ru used in government. I would talk about government IT reality and our way over it. Postgres performance improvements, using of latest features, overwriting of user generated queries to help query optimizer and other tweaks and hacks to tackle limited hardware problems. These lead us to number of computer science papers and (now committed) patches to Postgres (see Andrey Borodin talks for details).

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