Apache Spark is an engine that supports multiple programming languages, including Java, Scala, Python, and R, which are the top 4 highly effective programming languages for Big data on Google. It is used in the fields of data science, data engineering, and machine learning on single node machines or clusters that involve the collection, integration, and implementation of data. When it comes to learning Spark, the first thing that any developer would think about is what language to use and which one to master? The same is true for Solution Architects and Organizations because every problem requires different skill sets to solve. Therefore, it is of utmost importance that in the context of Spark one has the right knowledge about the plethora of programming languages that are supported by Spark.
Two of the most important programming languages, namely Java and Scala, are discussed in this article. Java is one of the oldest languages of all the top 4 highly effective programming languages mentioned above. Therefore, the traditional frameworks and the tools within the ecosystem of Big data are based on this old language. The major pro of java is that it provides the opportunity to use a large ecosystem of tools in the Big data world. On the other hand, Scala is a beautiful crossover between functional and object-oriented programming, invented in 2003 by Martin Odersky, a German Computer Scientist. As the name suggests, it is a highly scalable language. The details about Spark Scala Vs Java have been provided for comparative analysis.
What is Java?
Java is one of the oldest and most popular programming languages that is widely adopted, especially in the Big data world. For a majority of Big data projects, Java is the most suitable and chosen language by Big data developers and tool creators. However, as far as the Spark framework is concerned, various factors decide whether Java is the right fit or not. Some advantages and disadvantages of Java have been listed below for a clear understanding:
The Pros/ Features/ Advantages of Java
- Java is a scalable language just like Scala and it is also a stable and production-ready language that is backward compatible.
- There is a wide range of tried and tested libraries that are supported by Java. Since different libraries perform a variety of functions, the scope of Java is very high.
- Java is a platform-agnostic language, which means that it can run on almost any system. It’s as if it is designed in a way that it adapts itself to any new system.
- Java is portable because of the Java Virtual Machine or JVM. JVM is a foundation of Hadoop ecosystem tools such as Map Reduce, Spark, and Storm to name a few. All these tools have been written in Java and can run on the Java Virtual Machine.
- Java provides a huge variety of communities support as well, like GitHub and stack overflow.
- It is a statically typed language.
The Cons/ Drawbacks/ Disadvantages of Java
- Java is a very verbose language. One needs to know all the long terms and have a good memory to remember them. One error can ruin the whole program and you’ll have to spend hours reading through long codes searching for what went wrong. Even for small functions, the codes are very long (line-wise).
- Java does not support Read-Evaluate-Print-Loop (REPL) which is very essential for Big data processing. Therefore, alternative programming languages are preferred over Java because of this major deal-breaker.
What is Scala?
When compared to Java, Scala is a new programming language that has gained quick popularity. For a Spark framework, Scala is the programming language that is preferred by most experts. The major reason is that Spark was itself written in this language and therefore handling it with Scala becomes easier. Furthermore, the latest APIs need not be converted as they would automatically work on Scala. Scala is an object-oriented programming language to which all OOPs concepts apply. It not only considers every value as an object but also defines and supports functions. It is a machine-compiled language.
The Pros/ Features/ Advantages of Scala
- It is a general-purpose programming language, meaning that it can be used for any purpose related to objects or functions. This two-in-one feature is rare and provides it an edge over other non-general-purpose programming languages. It’s object-oriented as well as a functional programming language.
- Comparatively, Scala is less verbose than Java. So error checking would be easy and one need not type long codes.
- When it comes to Spark, using Scala has plenty of benefits like it is very fast and robust because Spark was written in Scala.
- Java isn’t the only portable language because Scala too can work with the Java Virtual Machine.
- It is a statically typed language just like Java.
- Unlike Java, Scala supports Read-Evaluate-Print-Loop (REPL) which is very essential for Big data processing.
- It can comfortably support APIs of Java.
The Cons/ Drawbacks/ Disadvantages of Scala
- Scala is more complex than Java when it comes to learning due to the functional nature of this programming language.
- Scala doesn’t have mature machine learning languages.
- Scala has a steep learning curve.
Scala and Java are two of the most effective and widely used programming languages that are supported by Spark. Both of them come with their pros and cons. To find out which language is the best in what situation one needs to analyze all the pros and cons. Both Java and Scala run over the Java Virtual Machine which makes these languages framework friendly. Since Scala was created at a later point in time when there was more progress in the field of technology and programming, it can be said that perhaps, Scala is an advanced version of Java. Broadly speaking, when it comes to Big data, Java is more preferred and when it comes to Spark, Scala is more preferable.