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February 03 – 05 , 2016

PgConf.Russia 2016

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Talks

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PgConf.Russia 2016
  • Mikhail Tyurin
    Mikhail Tyurin Avito

    My experience of working with PostgreSQL has provided clear understanding of its main advantages, making us choose and recommend choosing it.
    1. Beginning
    2. Documentation
    3. Community
    4.1 Transactional DDL
    4.2 WAL and True Physical Replication
    4.3 Transactional Snapshot and True Logical Replication and PGQ
    4.4 Exciting extensibility
    5. Success

  • 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.

  • Andres  Freund
    Andres Freund Citus Data

    Postgresql's buffer manager has parts where it's showing its age. We'll discuss how it currently works, what problems there are, and what attempts are in progress to rectify its weaknesses.

    • Lookups in the buffer cache are expensive
    • The buffer mapping table is organized as a hash table, which makes efficient implementations of prefetching, write coalescing, dropping of cache contents hard
    • Relation extension scales badly
    • Cache replacement is inefficient
    • Cache replacement replaces the wrong buffers

  • Galy  Lee
    Galy Lee

    Recent Update about Postgres Adoption in China. Postgres is getting its momentum in China, especially in 2015, one of the biggest insurance company is adopting Postgres, and Alibaba is providing Postgres service in their public cloud, also there are a lot of significant progress about the adoption. This talk will give an overview about the Postgres adoption in 2015 in China.

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