Even though it’s improved a lot the testing situation in sql is still not where a more traditional programming language is, modularity comes either in the form of ever nested cte, stored procs or dbt style templates. And sql types are wholly dependent on the sql engine, which can lead to wacky transforms.
Sql is great for adhoc analysis. If something isn’t adhoc, there is almost always a better tool.
Additionally, in this day and age where enriching the data by running it through some ML model isn't that rare, doing it in SQL by exposing it through an API and invoking some UDF on a per-row basis is extremely inefficient due to network RTT. In my opinion it is much better to use something like Apache Beam and load the model in memory of your workers and run predictions "locally" on batches of data at the time.
On the other hand I see the value in expressing "simple" logic in SQL, especially when joining a series of tabular sources. That's why I am super happy with Apache beam SQL extensions (https://beam.apache.org/releases/pydoc/2.30.0/apache_beam.tr...) which, IMHO, has the benefits of both worlds.
I do this using sql
1. Extracting an 'ephemeral model' to different model file
2. Mock out this model in upstream model in unit tests https://github.com/EqualExperts/dbt-unit-testing
3. Write unit tests for this model.
This is not different than regular software development in a language like java.
I would argue its even better better because unit tests are always in tabular format and pretty easy to understand. Java unit tests on other hand are never read by devs in practice.
> in this day and age where enriching the data by running it through some ML model isn't that rare,
Still pretty rare, This constitutes a very minor percentage of ETL in an typical enterprise.
You should get to know better java developers. :-)
sql is so pretty and so very readable and maintable if done by people who know what they are doing.
See my comment here https://news.ycombinator.com/item?id=34580675
I don't use nested cte/stored procedures . I simply extract extract it to a new file and mark it 'ephemeral' in dbt, no different than what you'd do in a regular programming language.