It seems to be usual nowadays to review the previous year, and readers apparently like Top-N Lists — that’s you now, so let’s hope that my understanding works with you too.
Of course 2018 will see its own amount of new and original content added to this blog, with a continuous focus towards how to make the best out of the SQL powerful programming language, and its advanced concurrency semantics.
PostgreSQL ships with an interactive console with the command line tool named psql. It can be used both for scripting and interactive usage and is moreover quite a powerful tool. Interactive features includes autocompletion, readline support (history searches, modern keyboard movements, etc), input and output redirection, formatted output, and more.
Florent Fourcot has read Mastering PostgreSQL in Application Development and has seen tremendous inprovements in his production setup from reading the first chapters and applying the book advices to his use case.
Here’s an interview run with Florent where he explains the context in which such improvements has been made!
The Enterprise Edition of Mastering PostgreSQL in Application Development ships with a docker image that hosts both a PostgreSQL server instance with a pre-loaded database, the one that’s used throughout the book examples, and also with a Jupyter Network notebook that hosts SQL queries thanks to the sql_magic plugin.
In How to Write SQL we saw how to write
SQL queries as separate .sql files, and we learnt about using query
parameters with the psql syntax for that (:variable, :'variable', and
:"identifier").
For writing our database model, the same tooling is all we need. An important aspect of using psql is its capacity to provide immediate feedback, and we can also have that with modeling too.
