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March 15 – 17 , 2017

Postrelease

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Talks

Talks archive

PgConf.Russia 2017
  • Илья Космодемьянский
    Илья Космодемьянский Data Egret

    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.

  • Arthur Zakirov
    Arthur Zakirov PostgresPro
    Teodor Sigaev
    Teodor Sigaev PostgresPro

    Full text search in PostgreSQL is probably the most advanced one among relational DBMS. This tutorial will explain how to setup full text search configurations and dictionaries and how to build a ful text search system using an example of a simple popular science web site, with demonstration of various ranking functions. Also I will tell about new RUM index, which allows to accelerate execution of some kinds of full text queries and implements a new improved ranking function.

  • Dmitry Beloborodov
    Dmitry Beloborodov UIS, CoMagic

    Using PostgreSQL since 2003, we went all the way from a database of a couple of GB to a cluster of more than 5TB. At the moment, we have more than 700 tables and about 1500 stored procedures. We are ready to share with you the following: - Problems encountered at different development stages and how we resolved them. - Best practices in database administration. - Our own extension to work with several closely related databases. - Best known methods and tools that enable our several teams to work together without interference. - How we set up test equipment of different types. And, of course, we'll talk about optimization, and how we identify bottlenecks and high-load use cases.

    VIDEO

  • Masahiko Sawada
    Masahiko Sawada NTT OSS Center

    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.

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