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March 15 – 17 , 2017

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Talks

Talks archive

PgConf.Russia 2017
  • Alexander Korotkov
    Alexander Korotkov PostgresPro

    I want to present a new custom access method, which extends the current GIN capabilities using additional information stored in posting tree/list. For example, positional information as an additional information allows new AM returns results in relevance order, which could considerably improve execution time of full text queries.

  • Peter Gribanov
    Peter Gribanov 1C LLC

    "1C:Enterprise" is the most popular in Russia/Eastern Europe business applications development framework supports PostgreSQL for 10+ years. We'll review some cases and pecularities of 1C and PostgreSQL tandem.

  • Алексей Лесовский
    Алексей Лесовский PostgreSQL Consulting LLC

    Streaming replication has been introduced in 2010 and quickly became one of the most popular features of PostgreSQL. Today, it is hard to imagine PostgreSQL installation without streaming replication. With its stability, high efficiency and ease of configuration one would have thought it is an optimal feature. However, while using it you might sometimes enter murky waters. This often can be resolved by using a combination of built-in and third party troubleshooting tools. In my talk I will provide an overview of these tools and explain how with their help one can diagnose, understand and eliminate problems related to streaming replication. I will also go through the most frequent issues occurring when streaming replication is used and will propose possible solutions. This talk is primarily aimed at DBAs and system administrators who use PostgreSQL in their day-to-day.

    VIDEO

  • Oleg Ivanov
    Oleg Ivanov PostgresPro

    Query optimization is an important problem, which solution has a great influence on DBMS performance, especially for complex queries. In this talk we consider PostgreSQL query optimizer and specifically cardinality estimation problem for correlated clauses, which is one of the most well-known drawbacks of query optimizers in general. In the talk we propose our solution for this problem which involves machine learning methods and is available for PostgreSQL 9.6 as an extension with a patch. We discuss the experimental evaluation, advantages, disadvantages, and fields of application of the proposed approach as well.

    VIDEO

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