People who work with Python in Spark often hear people discuss Scala and how good it is. If you are wondering whether you should learn Scala, you are probably asking the same question most people asked before they started using Scala: Is it really that better than Python? The answer, you might be surprised to know, is yes – and it is a definite yes.
Usually, the experts always have some caveats, some exceptions where the alternative still proves useful in certain situations. Not so with Scala. Pretty much everyone agrees that for all intents and purposes, it is completely superior compared to Python. What makes it so powerful? Well, it isn’t one thing, more of a collection of things.
1) It is ridiculously fast
If you have worked with Python so far, you will be blown away by how blazing fast Scala is. Your programs may be running at ten times the speed they use to run at. The secret behind this speed? Scala is written in Hadoop, which is what Spark is built on top of. So basically the programs you are writing are in the native language of the environment. Python has to be made understandable for Spark first, but Scala is already native to Spark.
2) It is easier to write programs in it
You will be surprised at how easy it is to make complicated things in Spark once you start using Scala. The fact that Scala is native to Hadoop means there are a lot fewer hoops to jump through. You don’t have to figure out how to make the system do something through Python; you just need to figure out the system and you’ll understand Scala as well. You will be using Hadoop’s native API instead of using middleware like Hadoopy. Scala was made for HDFS systems.
3) The way it handles errors
Here’s something that will be music to your ears if you’ve suffered using Python on Spark: ScalaLanguage will raise any errors it has right in the compilation stage. Through static typing that is strong, it makes development simpler and easier, especially when it comes to big projects. This is just another advantage of the fact that ScalaProgramming Language is perfect for Spark, while Python is a tool that has to be forced into the shape of Spark to run properly.
4) It is easy to learn
Know Python? You’ll know Scala in no time. It is very easy to learn – to the point that there is no reason you shouldn’t be learning it if you are working in Spark. Yes, we know, you don’t really want to focus on languages used in only one place, but trust us; the amount of boost that ScalaLanguage gives you is worth it. Don’t worry about being disconnected from Python and pigeonholing yourself into one architecture; even when you use ScalaLanguage, you never really go too far away from Python. You’ll still be thinking the same way and some developers even find that Python helps them come up with ideas better.
