An apology for the Pycon 9

The 20th of April I was supposed to give the pgchameleon’s talk at the Pycon 9. However personal issues prevented me to come to Florence. This post is an explanation and an apology for the pycon 9 attendees and organisers.

DBA may cry

DBA may cry

Database administrators usually work behind the scenes, over the weekends and in antisocial hours. They strive to look after the database which is at the core of any business with little or no recognition.

The sad truth is that the DBA is one of the most obscure and one of the less appreciated roles within the IT organisations.

The dependency ladder

The dependency ladder

One of the things that distinguish PostgreSQL from other database systems is the way the dependencies between database objects are managed.

PostgreSQL do not allow any invalid object like views or functions. Therefore any action that can invalidate dependent objects results in an error or it’s propagated to the dependent objects.

The mechanism could be confusing at first sight. However the implementation is brilliant and gives great flexibility.

New adventures in time and space

New adventures in time and space

When in February I received the email with the news that my talk was accepted at the pgcon it took me some time, and several espresso coffee, to realise that I wasn’t dreaming. The pgcon email reached me few days after the same talk was accepted at the pycon nove, the Italy’s nationwide Python conference. The Italian Pycon and the Pgcon are great conferences with amazing speakers and fantastic topics. The sole idea of giving my small contribution it makes me proud and a little scared, because I never talked to an audience composed mostly by fine developers.
Build your own aggregate

Build your own aggregate

Before the release of pg_chameleon 2.0 I had to write an upgrade procedure to allow a smooth migration from the version 1.8.

An interesting challenge I faced was to determine the maximum and minimum position for the MySQL’s binary logs belonging to the same server but stored with different values in multiple sources.

The user defined aggregates, a feature pretty unique to PostgreSQL, allowed me to solve the problem in a robust and simple way.