February 05 – 07 , 2018
PGConf.Russia 2018
PGConf.Russia 2018
PGConf.Russia is a leading Russian PostgreSQL international conference, annually taking together more than 500 PostgreSQL professionals from Russia and other countries — core and software developers, DBAs and IT-managers. The 3-day program includes training workshops presented by leading PostgreSQL experts, more than 40 talks, panel discussions and a lightning talk session.
Thems
- PostgreSQL at the cutting edge of technology: big data, internet of things, blockchain
- New features in PostgreSQL and around: PostgreSQL ecosystem development
- PostgreSQL in business software applications: system architecture, migration issues and operating experience
- Integration of PostgreSQL to 1C, GIS and other software application systems.
Talks
Talks archive
-
Valery Kosarev -
Storing binary data in database tables is sometimes a good solution for a particular project. But sometimes, due to changes in conditions or insufficient consideration of decisions, such storage is becoming a real nightmare. If there is an understanding of how and where to place these data, the transition to the new solutions are often very hard, often require modification in the application code and downtime the system for migration. The presentation is a particular solution of such problems. Our extension allows to move binary data from database to the storage Ceph and not only. And does it seamless for the applications.
-
David Fetter PostgreSQL Global Development Group
Transition tables, a new feature in PostgreSQL 10, offer broad new capabilities including new ways to maintain materialized views. At the end of this talk, you will have seen new ways to use this feature and have it in your tool chest for the future.
-
Konstantin Knignik PostgresPro
PostgreSQL looks very competitive with other mainstream databases on OLTP workload (execution of large number of simple queries). But on OLAP queries, requiring processing of larger volumes of data, DBMS-es oriented on analytic queries processing can provide an order of magnitude better speed. The following factors limit Postgres OLAP performance:
- Unpacking tuple overhead (tuple_deform)
- Interpretation overhead (Postgres executor has to interpret query execution plan)
- Abstraction penalty (support of abstract data types)
- Pull model overhead (operators are pulling tuples from heap page one-by-one, resulting numerous repeated accesses to the page)
- MVCC overhead (extra per-tuple storage + visibility check cost)
All this issues can be solved using vectorized executor, which proceed bulk of values at once. In this presentation I will show how vector operations can be implemented in Postgres as standard Postgres extension, not affecting Postgres core. The approach is based on introducing special types: tile types, which can be used instead of normal (scalar) types and implement vector operations. Postgres extension mechanism, such as UDT (user-defined type), FDW (foreign data wrappers), executor hooks are used to let users work with vectorized tables almost in the same way as with normal tables. But more than 10 times faster because of vector operations.
-
Дмитрий Шитов Centre of technical projects
What is a real cost of not paying for Windows for 1C-user? Is there life without COM? Addressing and other issues for the bunch of PostgreSQL. Scheduling disk resources. How to overcome OS CentOS crash.
Photos
Photo archive