Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Scala and Spark for Big Data Analytics

You're reading from   Scala and Spark for Big Data Analytics Explore the concepts of functional programming, data streaming, and machine learning

Arrow left icon
Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781785280849
Length 796 pages
Edition 1st Edition
Languages
Concepts
Arrow right icon
Authors (2):
Arrow left icon
Sridhar Alla Sridhar Alla
Author Profile Icon Sridhar Alla
Sridhar Alla
Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
Arrow right icon
View More author details
Toc

Table of Contents (19) Chapters Close

Preface 1. Introduction to Scala FREE CHAPTER 2. Object-Oriented Scala 3. Functional Programming Concepts 4. Collection APIs 5. Tackle Big Data – Spark Comes to the Party 6. Start Working with Spark – REPL and RDDs 7. Special RDD Operations 8. Introduce a Little Structure - Spark SQL 9. Stream Me Up, Scotty - Spark Streaming 10. Everything is Connected - GraphX 11. Learning Machine Learning - Spark MLlib and Spark ML 12. My Name is Bayes, Naive Bayes 13. Time to Put Some Order - Cluster Your Data with Spark MLlib 14. Text Analytics Using Spark ML 15. Spark Tuning 16. Time to Go to ClusterLand - Deploying Spark on a Cluster 17. Testing and Debugging Spark 18. PySpark and SparkR

Scala: the scalable language

The name Scala comes from a scalable language because Scala's concepts scale well to large programs. Some programs in other languages will take tens of lines to be coded, but in Scala, you will get the power to express the general patterns and concepts of programming in a concise and effective manner. In this section, we will describe some exciting features of Scala that Odersky has created for us:

Scala is object-oriented

Scala is a very good example of an object-oriented language. To define a type or behavior for your objects you need to use the notion of classes and traits, which will be explained later, in the next chapter. Scala doesn't support direct multiple inheritances, but to achieve this structure, you need to use Scala's extension of the subclassing and mixing-based composition. This will be discussed in later chapters.

Scala is functional

Functional programming treats functions like first-class citizens. In Scala, this is achieved with syntactic sugar and objects that extend traits (like Function2), but this is how functional programming is achieved in Scala. Also, Scala defines a simple and easy way to define anonymous functions (functions without names). It also supports higher-order functions and it allows nested functions. The syntax of these concepts will be explained in deeper details in the coming chapters.

Also, it helps you to code in an immutable way, and by this, you can easily apply it to parallelism with synchronization and concurrency.

Scala is statically typed

Unlike the other statically typed languages like Pascal, Rust, and so on, Scala does not expect you to provide redundant type information. You don't have to specify the type in most cases. Most importantly, you don't even need to repeat them again.

A programming language is called statically typed if the type of a variable is known at compile time: this also means that, as a programmer, you must specify what the type of each variable is. For example, Scala, Java, C, OCaml, Haskell, and C++, and so on. On the other hand, Perl, Ruby, Python, and so on are dynamically typed languages, where the type is not associated with the variables or fields, but with the runtime values.

The statically typed nature of Scala ensures that all kinds of checking are done by the compiler. This extremely powerful feature of Scala helps you find/catch most trivial bugs and errors at a very early stage, before being executed.

Scala runs on the JVM

Just like Java, Scala is also compiled into bytecode which can easily be executed by the JVM. This means that the runtime platforms of Scala and Java are the same because both generate bytecodes as the compilation output. So, you can easily switch from Java to Scala, you can and also easily integrate both, or even use Scala in your Android application to add a functional flavor.

Note that, while using Java code in a Scala program is quite easy, the opposite is very difficult, mostly because of Scala's syntactic sugar.

Also, just like the javac command, which compiles Java code into bytecode, Scala has the scalas command, which compiles the Scala code into bytecode.

Scala can execute Java code

As mentioned earlier, Scala can also be used to execute your Java code. Not just installing your Java code; it also enables you to use all the available classes from the Java SDK, and even your own predefined classes, projects, and packages right in the Scala environment.

Scala can do concurrent and synchronized processing

Some programs in other languages will take tens of lines to be coded, but in Scala, you will get the power to express the general patterns and concepts of programming in a concise and effective manner. Also, it helps you to code in an immutable way, and by this, you can easily apply it to parallelism with synchronization and concurrency.

You have been reading a chapter from
Scala and Spark for Big Data Analytics
Published in: Jul 2017
Publisher: Packt
ISBN-13: 9781785280849
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image