Category “YeSQL” — 77 articles

In our article Exploring a Data Set in SQL we discovered a data set related to music: the Chinook sample database.

Our discovery led us to find albums containing tracks of multiple genres, and for the analytics we were then pursuing, we wanted to clean the data set and assign a single genre per album. We did that in SQL of course, and didn’t actually edit the data.

Finding the most frequent input value in a group is a job for the mode() WITHIN GROUP (ORDER BY sort_expression) Ordered-Set Aggregate Function, as documented in the PostgreSQL page about Aggregate Functions.

PostgreSQL 10 is now available for everyone to use, and hinted by David Fetter I had to review my previous article on Json and SQL to adapt to Set Returning Functions changes.

A Set Returning Function is a PostgreSQL Stored Procedure that can be used as a relation: from a single call it returns an entire result set, much like a subquery or a table.

It used to be possible to use SRF in the SELECT clause, with dubious (but useful at times) semantics, and also in scalar contexts. The semantics have been fixed and are now much clearer, and the uses in scalar contexts are forbidden — they were a hack and never made sense anyway.

PostgreSQL has had proper json support for a while now. The unique extensibility approach of the PostgreSQL system allows it to enable native SQL friendly JSON processing.

In this article we’ll play with the Magic: the Gathering card data in JSON format data set, provided with a CC0 licence, and process the information provided. We also see how to normalize a JSON document into a proper database model that benefits from some PostgreSQL advanced features, and how to then inject the JSON documents into the normalized database schema. Finally, we compare some non-trivial processing done against both versions of the database schema.

There’s a very rich set of PostgreSQL functions to process text, you can find them all at the String Functions and Operators documentation chapter, with functions such as overlay, substring, position or trim. Or aggregates such as string_agg. And then regular expression functions, including the very powerful regexp_split_to_table.

In a previous article here we saw How to Write SQL in your application code. The main idea in that article is to maintain your queries in separate SQL files, where it’s easier to maintain them. In particular if you want to be able to test them again in production, and when you have to work and rewrite queries.