Scala was developed to allow common programming patterns to be expressed in a concise and 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. Before choosing a language for programming with Apache Spark it is necessary for developers to learn Scala and Python to become familiar with their features. 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.
Scala is definitely the best choice for the Spark Streaming feature because Python Spark support is not advanced and mature like Scala. On the other hand, Scala is an open source object-oriented and statically typed programming language where you need to specify objects and variable types when writing code. Scala also provides 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. A quick look at the salaries offered by Python and Scala skills shows us that Scala as a skill offers more salary in the job market than Python.
Scala is a high-calibre and robust programming language that has greatly aided the success of Big Data. 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 a combination of object-oriented and functional programming in a concise, high-level language. Scala allows general programming patterns to be expressed in a very concise and efficient format, minimising the number of lines of code.
Reports have also shown that Scala ranks 30th in the list of the top 50 trendy programming languages. Both Python and Scala are general-purpose programming languages that support the object-oriented model for creating applications. Performance is mediocre when Python programming code is used to make calls to Spark libraries, but if there is a lot of processing involved, Python code becomes much slower than the equivalent Scala code. 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.