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February 03 – 05 , 2016

PgConf.Russia 2016

Postrelease

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  • 60 talks
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Talks

Talks archive

PgConf.Russia 2016
  • Vladimir  Sitnikov
    Vladimir Sitnikov Pgjdbc, JMeter committer

    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.

  • Kamil Islamov
    Kamil Islamov Stickeroid Ai

    Method of automated refresh of preprocessed results of analytis reports is provided. Preprocessing and caching of reports allows ability for fast response for big data reports. Author describes the way of reports cache refreshing with minimum server loads and tuned actualization rate.

  • Anastasia Lubennikova
    Anastasia Lubennikova PostgresPro

    B-tree is the most widely used index type in PostgreSQL. This data structure and concerned algorithms are developed about forty years ago. But there is still an area for optimisations. In this presentation I'm going to talk about B-tree data structure, and its features important for the optimal index usage. Furthermore, I'll present a couple of new features which are expected to be included in PostgreSQL 9.6 release.

  • Dmitry Dolgov
    Dmitry Dolgov Zalando SE

    Schema-less is definitely a trend in the data storage nowadays, and it's not only about NoSQL, but also about traditional RDBMS. Many relational databases (e.g. PostgreSQL, Oracle, db2, Mysql) allow to storing data in the schema-less json format and use their own more or less unique way to do that.

    This talk contains two parts:

    • Comparison of the json support in PostgreSQL and different relational databases, namely Mysql, Oracle, db2, MSSql in terms of supported features, functions and so on.
    • Performance benchmarks for databases with the advanced json support, namely PostgreSQL and Mysql, and the MongoDB on different workload types and configurations.

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