Earlier this year, I implied Postgres was some kind of super middleware for dragging data out of every external resource it could locate. But that example only used the Postgres foreign data wrapper to contact another Postgres server. Why be so unimaginative? The future is as unlimited as it is terrifying.
Meet the new Postgres mascot
Let’s start with a few prerequisites. We want to see the combined functionality of a few different Postgres capabilities, so let’s try and combine data from MySQL, Postgres, and Javascript using V8.
Now that we know how Postgres window functions work, why not play with them a bit to get a better understanding of their capabilities? So long as we understand window functions are applied after data gathering and aggregation steps, much of their mystery and complexity is defanged. Let’s start actually using them for stuff!
Captain Murphy is tired of your nonsense
(Note: I’m a bit under the weather today, so this Phriday will probably be a bit truncated and potentially incoherent thanks to the drugs.
I’ll be the first to admit that I found Postgres window functions fantastically confusing when I first encountered them. They’re a powerful and versatile tool for building reports and summaries, but that functionality hides behind a fairly steep learning curve. One of the ways to combat their inherent complexity is to fully explore how they work, instead of just trying to wrap our heads around the expected results.
Window doggies have gotten decidedly smug
There are a lot of languages available for authoring Postgres functions, but there’s nothing quite like the the classic PL/pgSQL. It’s SQL! It’s not SQL! It’s a kind of horrifying mutant crossbreed suitable only for terrifying small children and generating complex reports from a cavalcade of dubious sources! And deep within its twisted entrails is an often overlooked feature usually only available in far more mature entities.
That’s right, it’s obvious we’re referring to the ASSERT statement.
These days with multiple Postgres database environments a commonality, it’s not unheard of to copy data from one to another. Perhaps a production extract is necessary to properly vet data in a staging environment. Maybe the development environment needs to update its data to reflect an especially pernicious and intractable edge case someone observed. In any of these scenarios, we are likely to extract data from multiple tables to import it elsewhere.
