This blog seeks to give you a clear idea on how Scala and Python are the same as well as different when it comes to Apache Spark. First of all let’s try to know what Apache spark is.
Apache spark is an open source, analytics engine used specifically for processing Big Data. Iartt basically does the job of batch and stream processing, large scale SQL and Machine Learning.
All these jobs have their own inbuilt module in the Spark.
Apache possesses high performance ability in many real-world situations as it does not use inbuilt file systems or data storage.
What is Scala?
Scala which stands for Scalable Language is a general purpose programming language that functions to provide both object oriented programming plus functional programming typed statistically.
The source code of Scala is collated into Java Byte Code and then it runs on Java Virtual Machine (JVM), which provides a runtime environment in which java bytecode can be performed.
What is Python?
Python programming language is a widely used interpreted, object oriented, high level general purpose programming language with dynamic semantics. It comes with high level data structures with support for Web API creation. It has excellent support for machine learning, deep learning libraries. Python is applicable across the board, extending beyond web development coding. Python could be advanced and implemented to perform boundless, complex tasks.
Application of Python
- Web Development.
- Game Development
- Machine Learning, Data Visualization and Artificial Intelligence.
- Desktop GUI
- Embedded Applications
- Business Applications
- Web Scrapping
Companies using Python as their first language
Application of Scala
- Data Processing
- Data Pipelines
- Video transcoding systems
- Big Data Projects
- Communication platform
Down here are some of the companies that operates with Scala as their first language:
- The Guardian
- Morgan Stanley
Comparison Between Python and Scala
- Type of Programming Language
Python is a dynamically typed programming language where the data type of a variable is checked during the runtime of the program. While Scala is a static typed programming language wherein first the source code is compiled and later it is sent for execution.
- Declaration of type of variable.
In python the object declaration is not required but in Scala we need to explicitly declare types of variables and objects.
In terms of performance, Scala is 10 times faster than Python.
- Ease of use
Scala is a verbose language while python is less verbose and easy to use.
- Learning Curve
Both Python and Scala are functional and object oriented languages with similar syntax and both have great support communities. Scala is a bit more complex to learn in comparison to Python due to its high-level functional features. Python contains so many libraries and API which makes the coding process efficient.
Python doesn’t support concurrency or multithreading however it supports heavyweight process forking.
Scala allows setting of code with multiple concurrency primitives. Due to its concurrency feature, Scala allows better data processing and memory management.
- Code Restoration and safety
Scala has multiple standard libraries and cores which allows fast integration of the databases in Big Data systems.
Scala is a statically typed language which allows us to notice compile time errors. That means Scala is safer when it comes to production level coding.
Although Python is a dynamically typed language. Python language is highly prone to bugs whenever there is a change in existing code. Hence reengineering the code for Scala is easier than Python.
From the above listed references, we can thus conclude that both Scala and Python have their own individual strengths and limitations. While both the languages are significant for software development as well as building Data Science applications, besides their practicality mostly depends on what they are used for. Scala is faster and gives access to the latest features of Apache Spark when compared to Python. Yet, Python is comparatively easier to use than Scala. Scala is regarded to be more favourable when applied for Big Data Applications but the opinion may vary from person to person.
Hence, concluding this journey, which one you choose is entirely up to you and the requirements for your project. In our view both are a good choice to learn Apache Spark.