Python is easy to learn and use. Scala is less difficult to learn than Python. It creates extra work for the interpreter at runtime. 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.
Data scientists often prefer to learn both Scala for Spark and Python for Spark, but Python is often the second-favourite language for Apache Spark, as Scala came first. Scala allows developers to write efficient, readable and maintainable services without hanging program code in an unreadable web of callbacks. Scala and Python languages are equally expressive in the context of Spark, so using Scala or Python can achieve the desired functionality. Refactoring code from a statically typed language like Scala is much easier and hassle-free than refactoring code from a dynamic language like Python.
Scala was developed to allow common programming patterns to be expressed in a concise, type-safe format. A quick look at the salaries offered by Python and Scala skills shows that Scala as a skill offers more salary in the job market than 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. Choosing a programming language for Apache Spark is a subjective matter because the reasons why a particular data scientist or data analyst likes Python or Scala for Apache Spark may not always apply to others.
Scala is definitely the better choice for the Spark Streaming feature because Python Spark support is not advanced and mature like Scala. Learning Scala enriches the programmer's knowledge of several novel abstractions in the type system, new functional programming features and immutable data. Let's explore some important factors to consider before deciding on Scala over Python as the primary programming language for Apache Spark. Both Python and Scala are general-purpose programming languages that support the object-oriented model for creating applications.
Scala also provides better performance than Python due to its speed and therefore may be the preferred choice of a programming language when it comes to handling large data sets. However, when there is significant processing logic, performance is an important factor and Scala definitely offers better performance than Python, for programming against Spark.