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February 03 – 05 , 2016

PgConf.Russia 2016

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Talks

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PgConf.Russia 2016
  • Fabio Telles Rodriguez
    Fabio Telles Rodriguez Timbira

    Challenges and solutions found in documents dematerialization and bank cheque processing system used in the Bank of Brazil.

  • 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.

  • 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.

  • Илья Космодемьянский
    Илья Космодемьянский Data Egret
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