Introduction to Programming in Apache Scala Tutorial

Welcome to the second chapter of the Apache Spark and Scala tutorial (part of the Apache Spark and Scala course). This chapter will explain the basic concepts of programming in Scala.

Let us explore the objectives of Apache Scala in the next section.


After completing this lesson, you will be able to:

  • Explain the features of Scala.

  • List the basic data types and literals used in Scala.

  • List the operators and methods used in Scala.

  • Discuss a few concepts of Scala.

We will begin with an introduction to Scala in the next section.

Introduction to Scala

Scala is a modern and multi-paradigm programming language. It has been designed for expressing general programming patterns in an elegant, precise, and type-safe way. One of the prime features is that it integrates the features of both object-oriented and functional languages smoothly. 

It is a pure object-oriented language, as every value in it is an object. The objects’ behavior and types are explained through traits and classes. 

It is also a functional language, as every function in it is a value. By providing a lightweight syntax for defining anonymous functions, it provides support for higher-order functions.  

In addition, the language also allows functions to be nested and provides support for carrying. It also has features like case classes and pattern matching model algebraic types support. 

Scala is statically typed, being empowered with an expressive type system. The system enforces the use of abstractions in a coherent and safe way. To be particular, this system supports various features like annotations, classes, views, polymorphic methods, compound types, explicitly typed self-references and upper and lower type bounds. 

When it comes to developing domain-specific applications, it generally needs domain-specific language extensions. Scala, being extensible, provides an exceptional combination of language mechanisms. Due to this, it becomes easy to add new language constructs as libraries. 

In the next section of apache Scala tutorial, we will discuss features of Scala.

Interested in learning more about Apache Spark & Scala? Enroll in our Apache course today!

Features of Scala

The basic features of Scala are listed below. 

As discussed, it is a general-purpose programming language. Therefore, you can use it in nearly any type of use cases in which other languages such as Java or C# are used. Like in all other languages, in Scala too, you can create your application more precisely than others.

Scala is a multi-paradigm programming language. This means that it offers Object-Oriented and functional programming constructs that can be combined to cut out the domain model.

In addition, Scala has an expressive type system with type inferencing. Therefore, until some point, you can get benefited with both the features. Scala supports statically checked duck typing. Also, it has an expressive syntax and provides powerful constructs, using which you can create powerful abstractions and internal DSLs. 

Scala incorporates a very powerful parser combinator library, using which you can design external DSLs by constructing monadic parsers. You can combine these parsers using the combinators. 

Another important feature is its rich concurrency that primarily comes through actors. Scala supports the Erlang model of concurrency. With Scala, you get powerful frameworks such as Akka, in which the features of actors can be combined with Software Transactional Memory or STM.

You can access this framework using the URL given on the screen. Scala, therefore, proves to be a powerful tool if your use case includes a lot of stuff dealing with concurrent programming. 

Scala lets you create a data collection, processing, and analysis system that is based on Apache ActiveMQ and Camel. 

Also, Scala provides interoperability with Java and .NET. The language has been designed to work well with Java 2 Runtime Environment or JRE. It interacts smoothly with the mainstream object-oriented Java language. Scala works on the same compilation model of Java and lets you access multiple existing high-quality libraries. In addition, Scala also supports .NET Framework, also called CLR. 

In the next section of apache spark tutorial, we will get to know basic data types.

Basic Data Types

Scala supports the same data types as Java does, with the same precision and memory footprint. The table below lists and explains all the basic data types used in Scala.

basic data types of scala
We will discuss basic literals in the next section.

Basic Literals

The rules used by Scala f literals are easy and intuitive. We will first discuss the integer and floating type literals. Integer literals are of Int, Long, Short, and Byte types. They are available in two forms Decimal and Hexadecimal.
An example is given below.  

basic literals of scala 1
On the other hand, floating point literals contain decimal digits. They may optionally have a decimal point and may optionally be followed by an E and an exponent.

We will continue our discussion on basic literals in the next section.

Basic Literals (contd.)

Other types of literals are Character literals and String literals. Character literals contain any Unicode character between single quotes. They are special character literal escape sequences. An example is given below.

Scala > val hex = 0x6; Output - hex: Int=6

On the contrary, string literals contain characters surrounded by double quotes. An example to define these literals is given below.
basic literals of scala 2

Basic Literals (contd.)

Another type of literals is the Boolean type that has literals, true and false. A few examples for defining these literals are given below. One more type is symbol literals, which are written with idents. An ident can be any alphanumeric identifier.  
An example of it is given below. 

basic literals of scala 3
We will begin with an introduction to operators in the next section.

Introduction to Operators

An operator is a symbol that conveys to the compiler that it needs to perform specific logical or mathematical manipulations. Actually, these operators provide a nice syntax for general method calls.
For instance, consider the example given below.
introduction to operators
In this example, the class Int includes a method called + that takes an Int and provides an Int as a result. To invoke the + method, you need to add two Ints, as depicted below. 

In the next section of Scala tutorial, we will discuss the types of operators in Scala.

Types of Operators

Scala provides a rich set of built-in operators. Scala makes use of multiple operators. 

Arithmetic Operators

They allow you to invoke arithmetic methods using infix operator notation for addition, subtraction, multiplication, division, and the remainder on a numeric type. 

Relational and Logical Operators

Using these operators, you can compare numeric types using relational methods such as greater than, less than, greater than or equal to, and less than or equal to. All these methods provide a Boolean result. Additionally, you can use the unary operator for inverting a Boolean value.
Bitwise Operators

They allow you to perform operations on individual bits of integer types using bitwise methods such as bitwise and, bitwise or, and bitwise XOR. 

You can also invert each bit in its operand using any unary bitwise complement operator. An example to use this operator is given below.

Object equality operators

They allow you to compare two objects for equality using either the double equal operator or inverse. 

An example to use this operator is given below.

Introduction to Type Inference

Scala provides a built-in mechanism called type inference, using which you can omit certain type annotations. Therefore, for example, it is generally not required to specify the variable type, as the compiler can deduce it from the initialization expression of the variable.

In addition, you can also omit return types of methods, as they correspond to the body type and can be inferred by the compiler.
An example to define type inference is given below.
introduction to type interface in scala
In the next subsequent section, we will discuss type interferences for various methods.

Type Inference for Recursive Methods

For recursive methods, the compiler cannot infer a result type. The program example shown below will fail the compiler for the same reason.
type inference for recursive methods in scala

Type Inference for Polymorphic Methods and Generic Classes

When polymorphic methods are called or generic classes are instantiated, it is not required to specify type parameters. The reason is that the compiler of Scala will infer these missing type parameters from the actual method or constructor parameters and the context. 

type inference for polymorphic and generic classes in scala
The example given above illustrates the same concept. In this program, the last two lines are equivalent to the code given above, where all inferred types have been made explicit.

Unreliability on Type Inference Mechanism

In some scenarios, using type inference can become dangerous.
For example, consider the program given below.
unreliability on type inference mechanism in scala
This program does not compile, as the type inferred for variable objects is Null. Because the only value of that type is null, you cannot make this variable refer to another value.

In the next section, we will differentiate the Mutable collection and Immutable collection.

Mutable Collection vs. Immutable Collection

To understand the concepts of a mutable and immutable collection, let’s compare them through the table given below.
mutable collection vs immutable collection in scala

Mutable implies that it is possible to modify the collection of concern. Therefore, to change a collection “a” and every other reference to that collection, you can append elements using the given operator. On the other hand, immutable implies that the given collection object never changes.

You would need to build new collection objects using the given operators. This helps in concurrent algorithms because it doesn’t need locking to add anything to a collection. However, this feature can prove to be very useful, and it may come at the cost of some overhead.

As compared to mutable collections, immutable collections are fully persistent data structures.

The difference between these collections is very similar to what exists between variable and value.

A mutable collection that is bound to a value can be altered; however, you cannot reassign the value. On the other hand, an immutable collection cannot be altered; however, if it is assigned to a variable, that var can be assigned to a collection built from it using operations like +.

In the next section of Scala tutorial, we will discuss functions in Scala.


In Scala, a function is a first-class value. Therefore, like other values, these can be returned as a result or passed as a parameter. An example to define such functions is given below.
functions in scala

Note that higher-order functions are the ones that take other functions as parameters or return them as results. 

In the next section of Scala tutorial, we will discuss anonymous functions in Scala.

Anonymous Functions

An anonymous function is an alternative of named function definitions for small argument functions that tend to get created by parameterization by functions. It is an expression that evaluates to a function. These are defined without giving them any name.

In the next section of Scala tutorial, we will discuss objects in Scala.

Interested in learning more about Apache Spark & Scala? Enroll in our Apache course today!


An object is a named instance with members like methods and fields. In Scala, an object and its class have the same name. 

For instance, in this example, the first line has the keyword “object”, which is being used to declare a new object. It is being followed by the name of the object. In the second line, a value “x” is being assigned to the object instance. Note that the members of objects are similar to those of classes. 

Let’s now discuss some of the uses of objects. One of the primary uses is to contain methods and fields that are independent of any environment.
objects in scala 1
An example is “math.” This has the object name in the standard library containing multiple fields and methods depending only on arguments, if any, provided to them.

Objects are also used to create instances of classes.
objects in scala 2
An example is given above.

Note that in Scala, there are singleton objects instead of static members, which is a class with only one instance and can be created using the keyword object. In this way, Scala is more object-oriented than Java. 

In the next section of Scala tutorial, we will discuss Classes.


Scala does not include built-in rational numbers; however, you can define them using a class. A class acts as a blueprint for objects. Once a class is defined, objects can be created from this blueprint using the keyword “new.”

classes in scala
For instance, in this example, two variables, x and y, and a method are being defined. The method is not returning any value. The variables of a class are called fields of the class and methods are termed as class methods. The name of the class acts as a class constructor that can take multiple parameters.

In the next subsequent sections, we will discuss Traits as interfaces and its example.

Traits as Interfaces

Before you understand traits, let us first discuss the reason for its origin. In languages like Python and C++, you don’t require interface as they have multiple inheritances, which is subject to the diamond issue. What will happen if you define a class inheriting two methods with the same type signature from two different classes? An interface is basically a set of properties and methods that an implementing class needs to have.

For avoiding the issues of multiple inheritances, the Java designers instead decided to have single inheritance with interfaces to make the system a little flexible.

Scala exists half-way between full multiple inheritances and Java's single inheritance with interface model, as it has traits. Traits allow you to recreate interfaces as Java does and also lets you go further. Using traits, you can recreate the interfaces and implementation model of Java.


Consider the given example to create traits in Scala. The code below shows how you can implement the Student trait.

traits in scala
In the next subsequent sections, we will discuss Collections and it’s types.


Scala includes a rich set of collection library, which are containers of things. These can be sequenced as linear sets of items. They may be one element, bounded to zero, or have an arbitrary number. They can be lazy or strict too. Lazy collections contain elements that may not require memory until accessed, for example, Ranges.
In addition, collections can be mutable or immutable. Immutable collections can contain mutable items.
You should note that mutable and immutable collections work better in different problems. In doubt, you should start with an immutable collection and change it later if required.

Types of Collections

The most commonly used collections type is lists. List[X] is a linked list of type X.
An example is given below. 

collections in scala 1
Another type is sets, which is a collection of various pairwise elements of the same type.
An example is given below.

collections in scala 2
Scala maps represent a collection of key or value pairs.
Consider the given example.
collections in scala 3

Types of Collections (contd.)

Scala Tuples can hold objects with different types like an array or a list.

An example of the same is given below. 
collections in scala 4

In Scala Options, Option[X] gives a container for one or zero elements of a given type.
Consider the given example.
collections in scala 5
The most direct method to diagnose all the elements that are returned by an iterator is by using a while loop, as explained through the given example.
collections in scala 6

In the next section of Scala tutorial, we will discuss lists.


All operations on lists can be expressed using the given methods. Head is a method that returns the first element of a list. The tail method returns a list with all elements except the first. The third method, isEmpty returns true if the list is empty otherwise false.
The example given below shows the use of these methods. When this code is compiled and executed, it gives the output shown.

lists in scala
We will discuss maps and it’s operations in the next couple of sections of Scala tutorial.


As discussed, maps represent a collection of key or value pairs. You can retrieve any value based on the Scala map key. These keys are unique. However, values need not be unique. Also called Hash tables, Maps are of two types, the immutable and the mutable.

Scala uses the immutable Maps by default. If you need to use the mutable maps, you would need to import Scala.collection.mutable.Map class explicitly. To use both types of maps in the same map, you can continue referring to the immutable Map as Map, but you can refer the mutable set as mutable.Map.

maps in scala
The example given above shows how to declare immutable maps.


The basic operations on maps are similar to those on sets and fall into the given categories.

The lookup operations such as Contains, isDefinedAt, getOrElse, get, and apply, turn maps to limited functions from keys to values. The basic method is def get(key): Option[Value].

To test if the map includes an association for the given key, you can use the get key operation. It returns the associated value in a Some if the association is included, otherwise, it returns None. The apply method returns the associated value with a given key directly, without wrapping it in an Option. An exception is raised if the key is not defined in the map. 
Another maps operations are transformations. They produce a map through filtering and transforming bindings of a current map. These operations are filterKeys and mapValues. 

Subcollection procedures return keys and values of a map separately in different forms. These operations are keys, keysIterator, keySet, values, and valuesIterator.

Removals remove bindings from a map.

However, the last type, additions, and updates allow to add new or change the existing bindings.

In the next section of Scala tutorial, we will discuss pattern matching.

Pattern Matching

Pattern matching is supported by Scala for processing messages. This feature allows you to match on any sort of data using first-match policy. This built-in mechanism is the second most widely used feature in Scala, after closures and function values.

The example given below depicts how to match against an integer value.
pattern matching in scala
The case statements block declares a function mapping integers to strings. The keyword match gives an easy way to apply a function to an object.

We will discuss implicit in the next section of Scala tutorial.


A method containing implicit parameters are applicable to arguments like normal methods. This is because the implicit label has no impact. If the method misses arguments for its implicit parameters, those are provided automatically.
The actual arguments can be of two types.

First, these are all identifiers y that are accessible at the method call point without any prefix and denoting an implicit definition or parameter.

And second, these are all members of companion modules belonging to the implicit type of parameters, labeled implicit.

In the example given below, a method sum has been defined that is computing the sum of a list of elements through the unit and add operations.
implicits in scala

Note that the implicit value cannot exist at the top. They need to be members of a template.

We will discuss streams in the next section of Scala tutorial.


The Stream class executes lazy lists in which elements are evaluated only when required.
An example is given below.

streams in scala

Note that in Scala, a Stream is a list with its tail as a lazy value.

A value remains computed and is reused. In other words, the values are cached.


Let us summarize the topics covered in this lesson:

  • Scala is a modern and multi-paradigm programming language, supporting the same data types as Java does.

  • The basic literals used in Scala are Integer, Floating Type, Character, String, Boolean, and Symbol.

  • Scala provides various operators like Arithmetic, Relational and Logical, Bitwise, and Object Equality.

  • Type inference is a mechanism that allows to omit certain annotations and return types of methods.

  • A function is a “first-class” value.

  • A class is a blueprint of objects.

  • Scala has traits that allow recreating interfaces and implementation model of Java.

  • Collections are containers of things.

  • You can retrieve any value based on the Scala map key, which is unique but not its values.

  • Pattern matching allows processing messages.

  • A method containing implicit parameters are applicable to normal methods.

  • The Stream class executes lazy lists in which elements are evaluated only when required.


With this, we come to the end of the second chapter “Introduction to Programming in Scala” of the Apache Spark and Scala course. The next chapter is Using RDD for Creating Applications in Spark Tutorial.

  • Disclaimer
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, and OPM3 are registered marks of the Project Management Institute, Inc.

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