PostgreSQLPostgreSQL

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Andreas Scherbaum

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I've just released a new version of pgsql_tweaks, an extension that adds some functions and views, that might help. The main repository is on GitLab at https://gitlab.com/sjstoelting/pgsql-tweaks and a mirror is on GitHub at https://github.com/sjstoelting/pgsql-tweaks . The extension is available over PGXN, see https://pgxn.org/dist/pgsql_tweaks/0.5.0/. Release notes pgsql_tweaks 0.5.0 The following changes have been done: - The extension is tested and does work with PostgreSQL 13 - The view pg_object_ownership has been added. This view shows the ownership of objects and might be useful, if one has to delete a role that still owns objects.

Whether you can use SQL to create a web application. We believe so! We have developed a platform for sql professionals so that they can create web services for their clients and easily maintain them. This is much faster, easier, and cheaper than doing custom development. Please tell me, do you find this approach interesting? https://falconspace.site/docs/vvedenie-v-falcon-space--c-chego-nachat

https://www.realwire.com/releases/EDB-Completes-Acquisition-of-2ndQuadrant-Becomes-Largest-Dedicated-Provider

With recent advances in machine learning driven by large internet companies together with advances in hardware, most database companies companies have begun to adopt machine learning techniques. One angle is from an application point of view towards analyzing user data in order to optimize business. The other is to use machine learning within the database towards managing and optimizing the database system itself.

This presentation is about using machine learning to improve database query optimization. The query optimizer is a critical component in a database system that exists to get optimal performance to return results to queries. Fast and stable query response time requirements are become critical with increasingly complex queries on increasingly large databases and needs to be done with minimum manual tuning. There are many aspects of query optimization that can benefit from using machine learning. In particular, we focus on one important aspect critical to coming up with an optimal query execution plans, namely to estimate cardinalities (the number of rows through various operations in a query execution plan).

Diese Session findet im Rahmen der IT-Tage, der Jahreskonferenz des Fachmagazins "Informatik Aktuell" im Dezember remote statt.

Details zu dieser Session:

https://www.ittage.informatik-aktuell.de/programm/2020/database-query-optimization-using-machine-learning.html

Komplettes Konferenz-Programm:

https://www.ittage.informatik-aktuell.de/programm.html

Anmeldung:

https://www.ittage.informatik-aktuell.de/tickets.html