Category: Misc Languages

Shubham Dangare explains what case classes are in Scala:

Case class is scale way to allow pattern matching on an object without requiring a large amount of boilerplate. All you need to do is add a single case keyword modifier to each class that you want to pattern matching using such modifier makes scala compiler add some syntactic conveniences to your class and compiler add companion object(with the apply method)
Adds factory method with the name of the class this means that for instance, you can write StringValue(“X”) to construct a StringValue object instead of using new StringValue(“X”)

Given how useful case classes are in Spark, it’s good to know how they operate. For more background on the topic, Alessandro Lacava has a post from a few years back describing the topic well.

On the Knoldus blog, Siddhant describes pure and impure functions:

As we can see, a value is pure, if it conforms very strictly to its type. In case of pureFunctionValue the declared type said that it was a function which takes an Int and returns a String, and that was indeed what it did. It could take an Int and it gave us back a reference to a String value and did nothing else.

In case of impureFunctionValue the declared type said that it was a function which takes an Int and returns a String. Indeed we could feed it an Int, but when we did so, it did something else apart from returning us a String. It printed stuff out to the console. This, friends, was not expressed in the type, thus it is a side-effect of the function and thus the value in question is impure, and not exactly a function in the mathematical sense.

Pure functions are great because they’re easy to reason about: you have an input, you have an output, and you can guarantee that nothing else changes in between. Impure functions are great because if we only had pure functions, our programs would add zero value. Impure functions drive I/O, including the ability to see what those pure functions did. The trick in functional programming is to push as much logic into the pure space as possible, making it easier to focus on the impure space and make sure you didn’t goof up there.

Koen Verbeeck takes us through a couple of Snowflake functions which behave quite differently from their SQL Server equivalent:

I’m doing a little series on some of the nice features/capabilities in Snowflake (the cloud data warehouse). In each part, I’ll highlight something that I think it’s interesting enough to share. It might be some SQL function that I’d really like to be in SQL Server, it might be something else.
Let’s start with SPLIT. Splitting string is something most of us have to do from time to time. In SQL Server, we had to wait until SQL Server 2016 when the table-valued function STRING_SPLIT came along. The syntax of both functions is exactly the same. You specify the string to split and the delimiter.

It turns out that SPLIT doesn’t quite split the same way that STRING_SPLIT does in SQL Server. It gets closer when you add FLATTEN but someone coming from a SQL Server background will still need to pay attention.

Niels Berglund learns about Visual Studio Code and writing Java in VS Code:

I mentioned above how Maven is a build automation tool for primarily Java projects. There are other build tools as well, but in this post, I use Maven as it is – which I mentioned above – the de-facto standard for Java-based projects.

Above we saw how we installed Maven as well as the VS Code Maven extension, however before we start to use it let us talk a little about Maven archetypes and naming conventions.

If I were in Java day in and day out, I’d probably go with IntelliJ IDEA but for occasional work, I can see VS Code doing well. That’s the interesting use case for Visual Studio Code: with all of the extensions, it’s a really good multi-purpose IDE while still being worse than the “natural” IDE for almost any single language.