Neues vom PostgreSQL Planet

On June 17th, I gave a presentation on Postgres Monitoring to the Chicago Postgres User Group. Since MeetUp doesn’t allow uploading slides, I figured I’d convert my presentation into a more comprehensive writeup. Enjoy! Why Monitor So, what are the finer points of Disaster Mitigation? Let’s start with a few questions: What broke? When did […]

For btree and hash indexes to be used for lookups, values being requested must be very restrictive, roughly 3-5% of a table's rows. Let's consider a BOOLEAN column — it can contain only three values: true, false, and NULL.

Binary Objects in PostgreSQL definitely have caveats, and don't behave the way you might expect coming from an Oracle background. This article demystifies the Blob, gives some practical advice for dealing with them, and improves your philosophy.

SQL and especially PostgreSQL provide a nice set of general purpose data types you can use to model your data. However, what if you want to store fewer generic data? What if you want to have more advanced server side check constraints? The way to do that in SQL and in PostgreSQL in particular is to use CREATE DOMAIN.

This blog will show you how to create useful new data types which are commonly needed in many applications.

I released plpgsql_check 1.11.

Now, the functions with arguments of polymorphic types can be checked by plpgsql_check too.

Image from Flickr user fsse8info

Recently the topic of generating random-looking coupon codes and other strings came up on internal chat. My go-to for something like that is always this solution based on Feistel networks, which I didn’t think was terribly obscure. But I was surprised when nobody else seemed to recognize it, so maybe it is. In any case here’s a little illustration of the thing in action.

Postgres indexes can only be defined on single tables. Why would you want to have indexes that reference multiple tables, i.e., global indexes?

A typical database-oriented application setup only must work with single operation SQL or RESTful execution. Your customers might only be sending the INSERT or UPDATE queries one at a time. We have covered this approach in part 2 for our series and have created a simple RESTful API that allows users to perform CRUD operations […]

Recently we had some clients who had the desire to store timeseries in PostgreSQL. One of the questions, which seems to interest people in this area, is related to calculating the difference between values in timeseries data. How can one calculate the difference between the current and the previous row?
To answer this question I have decided to share some simple queries outlining what can be done. Note that this is not a complete tutorial about analytics and windowing functions but just a short introduction to what can be done in general.

Photo by Maxpax, used under CC BY-SA 2.0, cropped from original.

When working with large tables, even simple actions can have high costs to complete. What queries are acceptable for smaller tables can often be less than ideal when applied to large tables, so your specific choice of approach to a given problem becomes more important.

PostgreSQL Person of the Week Interview with Andrew Dunstan: Originally from Australia, now living in North Carolina, USA. Dual citizen. Age 66, making me one of the oldest people in the Postgres community. Principal pastime: walking.

There is a long history of hardware acceleration, i.e., hardware modules helping the CPU. There was the 80287 math coprocessor, sound cards, and video cards. The computer industry is constantly moving things from the CPU to the motherboard and external cards, and back again. Movement is mostly determined by whether the CPU is able to efficiently perform the task, the transfer bandwidth needed to perform the task, and the flexibility of replaceable external cards.

Test Postgres Extensions With GitHub Actions 28 Jun 2020

I first heard about GitHub Actions a couple years ago, but fully embraced them only in the last few weeks. Part of the challenge has been the paucity of simple but realistic examples, and quite a lot of complicated-looking JavaScript-based actions that seem like overkill.

I first heard about GitHub Actions a couple years ago, but fully embraced them only in the last few weeks. Part of the challenge has been the paucity of simple but realistic examples, and quite a lot of complicated-looking JavaScript-based actions that seem like overkill. But through trial-and-error, I figured out enough to update my Postgres extensions projects to automatically test on multiple versions of Postgres, as well as to bundle and release them on PGXN.

Computer tasks are one of the most precise activities we do on a daily basis. Driving, cooking, walking, and reading are fairly imprecise compared to computer interaction.

Computers represent symbols like "a" and "A" precisely and require external facilities to define relationships between them. This email thread makes a convincing argument that you usually want case-preserving, but less-precise case-insensitive behavior.

Today’s blog post is going to be a nice little adventure of learning how to use composite primary keys in a PostgreSQL many-to-many relationship table while building a Django application. Along the way we will talk about some basics of Django and some workarounds you need to use. Let’s dig in and get started.

One of my colleagues at EDB spent some time working on a new extension for PostgreSQL and EDB Postgres Advanced Server as part of a proof of concept that I asked him to look into. I'm pleased to say that we've decided to make that work Open Source, releasing it under the PostgreSQL licence.

This article gives a step by step guide to utilizing Machine Learning capabilities with 2UDA. In this article, we will use examples of Animals to predict whether they are Mammals, Birds, Fish or Insects. Software versions We are going to use 2UDA version 11.6-1 to implement the Machine Learning model. This version 11.6-1 combines: PostgreSQL […]

OmniDB is an open-source, graphical database management tool developed by 2ndQuadrant, a world-leader in PostgreSQL technologies and services. OmniDB is a browser-based, universal client tool that can manage major database engines like PostgreSQL, MariaDB, MySQL, and Oracle. Other soon-to-be-supported engines include SQLite, Firebird, MS SQL Server, and IBM DB2. Like any excellent database client software, OmniDB […]

Overview

It has been a while since I have written about the new features in a major pgpool II release. Well pgpool II 4.2 is in the works and the plan is to release it towards the end of this year. As usual every major release of pgpool II is compatible with the parser of latest PG release so pgpool II 4.2 will be compatible with PG-13 parser. There are many nice features that will be part of next major release however the ones that particularly catches my attention is supporting LDAP authentication with pgpool II.