PgConf.Russia 2019

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PgConf.Russia 2019

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.

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63 talks
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Aleksander Sheludchenkov GK "Mitra"
Non-standard 1C cluster
- Migration of the standard 1C cluster to MPI environment - "machine to machine migration of services".
- PostgreSQL migration to GPU powered machine.
Presentation materials
Darafei Praliaskouski Juno

PostGIS for Disaster Management

PostGIS is spatial extension for PostgreSQL.

This talk will go in depth on using PostGIS for disaster management: which functions can be used and for what.

Presentation materials
Christopher Travers DeliveryHero SE

Data Recovery in PostgreSQL on a Damaged Filesystem

This case study walks participants through a case where we decided to embark on a data recovery effort. This talk is applicable to all users, from novices to advanced PostgreSQL database administrators. Beginners will get an understanding of what data recovery is and is not, what expectations to have going into it, and how to work with contracted experts in order to ensure the best possible outcome, while more advanced users and experts will also get a fair bit out of the technical aspects of the case study.
While the talk will emphasize non-technical operational aspects of data recovery, it will also include discussions of the internals of PostgreSQL we had to work with, as well as how we went about approaching difficulties so that we could retrieve the data we hoped to.

Presentation materials
Tatsuro Yamada NTT Comware
Auto plan tuning using feedback loop

As is often seen in OLAP and batch processing workloads, the more complex a query (containing many joins, filters, aggregates), the more there is a possibility of row count estimation errors, which leads to planner choosing an inefficient execution plan.
To address that problem, I developed a tool called pg_plan_advsr as a PostgreSQL extension, which corrects the estimation errors by repeatedly feeding back the information collected during query execution to the planner.
The tool has three features:
1. Automatic plan tuning by repeatedly feeding execution information to planner
2. Preserve all plans generated during plan tuning in a history table
3. Create and store optimizer hints to be able to reproduce plans generated during tuning process
I verified the effectiveness of pg_plan_advsr by enabling it when running the join order benchmark (JOB) against PG 10.4 and observed its execution time shortening to 50% of the original. Therefore, it is useful for user who would like to do plan tuning for OLAP and batch processing.
I will talk about the following things in this presentation:
- Principles behind pg_plan_advsr and its architecture
- Detailed information about the measurements done with JOB
- Possible future enhancements
- Using aqo and pg_plan_advsr together (experimental)
Presentation materials