Автономные транзакции в Postgres
- What is an autonomous transaction?
- An overview of autonomous transactions in "big" DBMS: Oracle.
- Autonomous transaction logic in Postgres Pro.
- An overview of emulation methods for autonomous transactions in PostgreSQL.
- Comparing performance of the built-in Postgres Pro autonomous transaction mechanism and PostgreSQL emulation methods.
VIDEO
Слайды
Другие доклады
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Igor Chizhevskiy НИИ "Восход"Sergey Korolev МЦСТDmitry Pogibenko ФГБУ "НИИ Восход"Stanislav Merzlyakov ФГБУ НИИ "Восход"Илья Космодемьянский Data EgretИван Богданов НИИ "Восход"
Восход PostgreSQL на Эльбрус
Practical experience of carrying out import substitution with using PostgreSQL in government information system including not only the free software, but also the Russian hardware (Elbrus servers and other).
VIDEO
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Kamil Islamov Stickeroid Ai
Совместное использование хранимых процедур Postgres и ORM на примере Django
We will discuss some tricks and patterns while developing web-application architecture based on ORM technology with Postgresql functions implementation with Python Django as an example. Also we will consider some ways of building the business logic inside a database with keeping Django framework opportunities and implementation of it's built-in admin panel.
VIDEO
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Alexander Alekseev Postgres Professional
ZSON, расширение PostgreSQL для прозрачного сжатия JSONB
ZSON is a PostgreSQL extension for transparent JSONB compression. Compression is based on a shared dictionary of strings most frequently used in specific JSONB documents (not only keys, but also values, array elements, etc). In some cases ZSON can save half of your disk space and give you about 10% more TPS.
VIDEO
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Dmitry Lebedev BestPlace
Исследования геоданных при помощи PostGIS и смежных инструментов
Nowadays one can make a decent urban research based simply on public datasets, making interesting and unexpected insights. In the presentation, I'll show examples of these calculations in PostGIS, the industry standard de-facto.
But just PostGIS is not enough. You need tools to import, verify and visualize the data. It's critically important to visualize the data live, to debug your calculations and shorten iterations. I'll describe all these steps:
- Collecting the data: public API, OpenStreetMap; direct user input.
- 3rd party APIs for calculations.
- Visualization of GIS and other sorts of data: QGIS, Matplotlib, Zeppelin integrated with PostGIS.
- Debugging the calculations: live visualization (Arc, QGIS, NextGIS Web)
- Scripting and minimizing the chores: Makefile, Gulp