Constraints или о том, как попытаться спокойно жить

There's a common delusion that constraints should never be used as they affect performance in a negative way, interfere with regular work, and are, all in all, useless. The database is commonly perceived as just a storage without any logic. I'll explain why it isn't so and what this careless approach may lead to.

Как переносить данные из Oracle в PostgreSQL и обратно

PostgreSQL has become a reality in a lot of shops today. In most cases PostgreSQL is established beside the current Oracle deployment and quite soon one question pops up regularily: How can we push data from Oracle to PostgreSQL and vice versa? Way back, in March 2001, a new extension to the SQL standard made it's way to define common APIs for managing external data: SQL/MED (ISO/IEC 9075-9:2008). The PostgreSQL community picked that up quite fast and implemented a framework for plugging in so called foreign data wrappers back in 2011 with PostgreSQL 9.1. Since then a wide range of these foreign data wrappers popped up and thanks to those, PostgreSQL today is able to integrate data from almost every external source, no matter if it is coming from flat files, other relational database systems or even unstructured sources. In this talk we will look at the foreign data wrapper for Oracle and how it can be used to get data from Oracle to PostgreSQL. But this is not a one way game: data can also be pushed from PostgreSQL to Oracle, and this might become important depending on the requirements. It is guaranteed that this talk is splitted by half: Slides and a lot of demos.

GPU-версия PostGIS и индекса GiST

This talk introduces GPU version of PostGIS and GiST-Index that we have developed as a new feature of PG-Strom.

Nowadays, our devices (like mobile phones) generate geolocational data time-by-time, and it is often utilized for area-marketing, push-delivery, disaster notification, and so on. People often use GIS technology to pick up users based on their current location. Even if area definitions are complicated polygons, PostGIS functions can generate right intersections, however, it is often highly computing intensive workloads.

GPU is designed for massive parallel computing workloads, with more than thousands cores per chip. And, we have developed PG-Strom extension to run a part of SQL workloads on GPU devices. At the upcoming PG-Strom v3.0, it newly supports several PostGIS functions and GiST-index for the computing intensive geolocational workloads.

In this talk, we will introduce the technology background, usage, implementation and benchmark result of GPU version of PostGIS and GiST-Index.

Построение автоматического консультанта и инструментов настройки производительности в PostgreSQL

PostgreSQL is a mature and robust RDBMS since it has 30 years of history. Over the year, its query optimizer has been enhanced and usually produces good query plans.

However, can it always come up with good query plans? The optimization process has to use some assumptions to produce plans fast enough. Some of those assumptions are relatively easy to check (e.g. statistics are up-to-date), some harder (e.g. correct indexes are created), and some nearly impossible (e.g. making sure that the statistic samples are representative enough even for skewed data repartition). For now, given those various caveats, DBA sometimes can't always realize easily that they miss a chance to get a meaningful performance improvement.

To help DBA to get a truly good query plan, we'll present below some tools that can help to fix some of those problems by providing a missing index adviser, looking for extended statistics to create, and row estimation error correction information to get appropriate join orders with join methods automatically.

• pg_qualstats: provides a new index and extended statistics suggestions to gather many predicate statistics on the production workload.
• pg_plan_advsr: provides alternative good query plans automatically to analyze iterative query executions information to fix estimation rows error.

In this talk, we will explain how those tools work under the hood and see what can be done, how they can work together. Also, we will mention what other tools also exist for related problems. Therefore, it will be useful for DBA who are interested in improving query performance or want to check whether current settings of indexes and statistics are adequate.