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February 03 – 05 , 2016

PgConf.Russia 2016

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Talks

Talks archive

PgConf.Russia 2016
  • Lev Laskin
    Lev Laskin Electron

    In late 2006, the 1C company has implemented to work 1C:Enterprise platform with DBMS PostgreSQL, which can operate under the operating systems Windows or Linux. The talks will attempt to summarize the experience of sharing the platform 1C:Enterprise with PostgreSQL database since 2008. Consideration will be given a few success stories, technical features of the work are examples of specific tasks, offers advice on selecting and cons. The talk may be of interest to employees of companies considering the option of using PostgreSQL for the 1C:Enterprise, DBA, professionals interested in the possibility of extensibility PostgreSQL.

  • Guangzhou  Zhang
    Guangzhou Zhang AliBaba

    Alibaba has provided a relational database service (RDS) for postgres in our public cloud platform (aliyun.com, the currently biggest public cloud in China). We are also enabling internal applications to use postgres in our other internet business and we can share our experience

  • Dmitry Melnik
    Dmitry Melnik ISP RAS

    Currently, PostgreSQL uses the interpreter to execute SQL-queries. This yields an overhead caused by indirect calls to handler functions and runtime checks, which could be avoided if the query were compiled into the native code "on-the-fly" (i.e. JIT-compiled): at a run time the specific table structure is known as well as data types used in the query. This is especially important for complex queries, which performance is CPU-bound. At the moment there are two major projects that implement JIT-compilation in PostgreSQL: a commercial database Vitesse DB and an open-source project PGStorm. The former uses LLVM JIT to achieve up to 8x speedup on selected TPC-H benchmarks, while the latter JIT-compiles the query using CUDA and executes it on GPU, which allows to speed up execution of specific query types by an order.

    Our work is dedicated to adding support for SQL query JIT-compilation to PostgreSQL using LLVM compiler infrastructure. In the presentation we'll discuss how JIT-compilation can be used to speed up various stages of query execution in PostgreSQL, and the specifics of translating an SQL query into LLVM bitcode to achieve good performing native code. Also we'll present preliminary results for our JIT-compiler on TPC-H benchmark.

  • 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.

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