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March 15 – 17 , 2017

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Talks

Talks archive

PgConf.Russia 2017
  • Michael Kagan
    Michael Kagan Mellanox Technologies

    Modern high-performance and scale-out Database solutions need to move huge amounts of data between the system components. They need to perform it quickly and without delay for the end-user. While developing interconnect technologies Mellanox focuses on highest bandwidth, ultra-low latency, and advanced CPU offload capabilities. In this session Michael will tell about fast interconnect value for Database and Big Data solutions and will share Mellanox experience in building such systems in cooperation with leading global vendors.

    VIDEO

  • Andrey Fefelov
    Andrey Fefelov Mastery.pro

    I will tell you about why Postgres is first-choice product as a foundation for your BI system with classical OLAP workload. Briefly it will be said about existing open source BI solutions.

    I will also describe specific of our architecture, why we chose snowflake scheme and how we are doing extract, transformation and load procedures. It will be mentioned about special Postgres tuning for OLAP and massive data bulkload workloads. Also I will let you know about Postgres usage as a column database with cstore_fdw by Citus and results achieved. Cons and problems of our approach will be described in the end of the talk.

    VIDEO

  • Ivan Frolkov
    Ivan Frolkov PostgresPro

    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).

    VIDEO

  • Ildar Musin
    Ildar Musin PostgresPro
    Dmitry Ivanov
    Dmitry Ivanov PostgresPro

    Partitioning is a long-awaited feature in PostgreSQL. Although Postgres supports partitioning via inheritance, this approach has some disadvantages, such as the need to manually create partitions and support triggers, significant planning overhead, and no query execution optimizations. In this talk, we’ll tell you about the pg_pathman extension we are developing. pg_pathman supports HASH and RANGE partitioning, performs planning and execution optimizations, supports fast insert by using Custom Node instead of triggers, provides functions for partition management (add, split, merge, etc.), supports FDW, non-blocking data migration, and more. We'll also speak about pg_pathman integration with Postgres Pro Enterprise Edition and Oracle-like syntax support for partitioning. Finally, we'll discuss new partitioning capabilities in PostgreSQL 10, the already implemented features and further development plans.

    VIDEO

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