You can use the basic programming features of Scala with the IntelliJ IDE and get useful features like type hints and compile-time checks for free. If you have enough experience with any statically typed programming language like Java, you can stop worrying about not using Scala at all. Learning Scala enriches the programmer's knowledge of several novel abstractions in the type system, new functional programming features and immutable data. Scala was developed to allow common programming patterns to be expressed in a concise, type-safe format.
Scala and Python languages are equally expressive in the context of Spark, so using Scala or Python can achieve the desired functionality. Scala is definitely the better choice for Spark Streaming functionality because Python Spark support is not advanced and mature like Scala. However, when there is significant processing logic, performance is an important factor and Scala definitely offers better performance than Python, for programming against Spark. Its API is intended for data processing and analysis in multiple programming languages such as Java, Python and Scala.
Scala also offers better performance than Python due to its speed and can therefore be the preferred choice of a programming language when it comes to handling large data sets. Scala is also excellent for low-level Spark programming and for easy navigation directly to the underlying source code. Let's explore some important factors to consider before deciding on Scala over Python as the primary programming language for Apache Spark. I'm working on a project called bebe that I hope will provide the community with a secure, high-performance Scala programming interface.
Scala offers a lot of advanced programming features, but you don't need to use any of them when writing Spark code. Many organisations favour the speed and simplicity of Spark, which supports many application programming interfaces (APIs) available from languages such as Java, R, Python and Scala. Scala is a powerful programming language that offers developer-friendly features not available in Python. Using Scala for Spark provides access to the latest features of the Spark framework, as they are first available in Scala and then ported to Python.