Apache Spark: Scala vs Python. Which is better?

The project manager enters the team’s meeting room and asks, “Should we use Python or Scala for this new Apache Spark project?”

You may find yourself wondering if this is a trick question when encountering the enterprise rule book.

  • What does it say about this?
  • Is this an Android or iOS platform?
  • Should you skim over questions until you come to an irrelevant one?

An important decision is selecting a language, even if the answer to the last question was yes. If your idea for a Spark project starts to come together, courses in two popular high-level programming languages can help you get started.

This comparison of Scala versus Python can be a helpful resource if you’re still deciding between the two languages.

About Apache Spark

Apache Spark is a powerful open-source engine for analysing large datasets. It provides a distributed framework to transform and analyse the data using in-memory computing capabilities.

Apache Spark facilitates speedier processing than MapReduce jobs performed on Hadoop using both batch and streaming methods.

The two programming language choices are not mutually exclusive; a single Spark framework can support multiple languages.

The Scala programming language has been used to build data-intensive applications for many years.

With its rich libraries that make it easy to manipulate data sets, the language is also well-suited for writing user interfaces.

On the other hand, Python gives developers access to tools that enable them to handle massive amounts of data and the ability to create frameworks.

 

About Scala

Scala is a multi-paradigm programming language that can be used in various ways, including the following:

  • Functional programming with immutability and support for pattern matching.
  • Object-oriented programming with classes. 
  • The concurrency model in Scala relies on the Java concept of Synchronisation and Communicating Sequential Processes (SCSP).
  • Understanding this, Python and Scala can be viewed as the two primary tools for creating Spark applications.

About Python

Python will continue to be the language of choice for data-intensive applications for many companies, including Facebook, Instagram, Pinterest, and GoDaddy. This popularity is mainly due to its versatility and ease of use.

To illustrate this, let’s look at each point in more detail: 

1) Python is fast and easy  

The code developed using Python can be swift. Moreover, Python is easy to learn and understand. This makes it the preferred language of developers who are just starting in the industry.

Python features optimal readability:

Due to its syntax – which borrows from traditional languages such as C++, Java, and Perl making it easier to adopt for programmers coming from other languages due to its low density of punctuation as compared to JavaScript and Ruby.

Here is a following JavaScript code using XMLHttpRequest:

Our next example shows how to accomplish the same thing in Python:

xhr = new XMLHttpRequest();    xhr.open(“POST”, “http://www.pythonprogramming.com/”);    xhr.send(“test1=test1&test2=test2&test3=this is a test”);   

The main reason for this popularity is also due to its easy portability: you can run Python programs on Linux, Mac OS X, and Windows.

2) Python has a large and vibrant developer community  

Python is constantly evolving as new releases support more powerful language constructs. There are many free online tutorials, books, and other resources available online to help you learn Python.

3) Python has libraries for almost anything  

Libraries help simplify working with specific areas of a language’s functionality.

Python has one of the best libraries out there, covering almost every aspect of the development process; this includes support for networking, data processing, manipulation, web services, and so much more. 

4) Python can work with many databases  

Python can be used to query almost any database manager using SQLAlchemy – this means that it can be used to query MySQL, Oracle, and PostgreSQL databases.

5) Python is scalable  

Python can handle massive amounts of data with its powerful libraries like NumPy, SciPy, and Pandas, a few of the many best in the business for working with arrays and related mathematical operations.

Scala Usage

Scala allows developers to develop applications quickly and easily. Scala has been used by Twitter, Netflix, LinkedIn, SAP Labs, and many other companies that need a programming language with the following features:

  • Support for functional programming
  • Built-in support for Concurrency like Actors and Futures
  • Support for a Class-based Object model

While Java is still a popular programming language, Scala is becoming more and more common with the rise of new technologies. Programmers use Scala because of its seamless integration of object-oriented and functional languages. For example, data analysis using Spark or AWS Lambda expressions can be accomplished with low overhead.

Python Usage

While Python is a general-purpose programming language, it’s most commonly used for the following applications:

  • Web Development
  • Data Science
  • Machine Learning
  • Web Architecture
  • Mobile App Development
  • Configuration Scripts
  • Automation of Tasks
  • System Administration
  • Scientific Computing
  • Software Engineering Games

Comparison Points between Scala and Python

Scala has several advantages over Python, such as lower boilerplate code, a cleaner syntax, and more efficient runtime.

Another good thing about Scala is that even though it has functional programming features, it does not have the same learning curve as Haskell or Lisp.

Scala supports both static and dynamic typing, which can be very useful at times compared to Python’s dynamic typing language.

Python developers love its clear syntax that is perfect for beginners. Python also does not require developers to keep typing while in the middle of a command.

In addition, it is dynamically typed, and hence, errors are caught during run time rather than at compile time.

Unlike Python, Scala is a functional programming language that can also be used to build Java applications. Scala supports both functional and object-oriented paradigms, making it one of the most popular languages in use today.

In addition, Scala allows developers to write concise code since it uses powerful features like immutability. It is a complex language to master, and learning Scala requires an investment in time and effort, especially if you are new to functional programming.

In contrast, Python is the easiest programming language to learn, with several online tutorials available at very affordable prices.

 Python caters to non-programmers since it is easier, simpler, and more flexible to work with than many other programming languages.

Scala’s edge over Python includes: 

It is strongly typed, which means that all variables must be declared before use. This also means that it uses less memory because the interpreter can cache the data types of variables. Some people prefer this feature because it ensures that all input from an outside source has been checked and validated before being accepted by a program.

It is built on top of Java, which means that some language features are inherited from Java. Scala has a different syntax compared to Java. It is based on functional programming, which means that it does not have mutable data types and produces less boilerplate code, making the apps easier to write and debug.

Endnote

This blog gives an idea about the differences and similarities between Scala and Python. 

Python is easier to learn than Scala. However, Scala allows you to write better organised and more readable code than Python. While learning a new language can be difficult, it is quite simple if you already have a foundation in programming.

Do share your thoughts on other advantages of using Scala and Python.

Reference:

Scala vs. Python for Apache Spark. The pros and cons of using Scala vs Python for programming.

Apache Spark : Python vs. Scala