As a developer, we tend to choose the most elegant tools to get the job done. Scala is one of such tools for Big Data developers and data scientists. Scala shines for data processing and machine learning for a couple of reasons.
- The first reason is the functional paradigm and scripting approach. They are the natural fit for the data transformation requirements.
- Scala is concise and expressive. It keeps your life simple.
Apache Spark is another compelling reason to learn Scala. Spark libraries are available in
other languages, but Scala is
the best fit for using Apache Spark because the Spark creators decided to go with the Scala
Personally, for me, Apache Spark is the most critical reason. So, if you have the same reason to learn Scala, this tutorial will try to cover enough Scala for a potential Spark developer. This tutorial covers enough basics, concepts, and examples to give you a jump start into Scala and help you achieve prerequisite for learning Apache Spark. However, even if you are not interested in Apache Spark, this tutorial should be able to lead you into functional programming using Scala language. I am assuming that you already have some background in programming. Prior knowledge of Java is helpful, but it is not mandatory to follow these tutorials.
So good luck and enjoy watching Learning Journal.