Data Structures in Java

Introduction

The data structure is a fundamental topic of every programming language. The selection of a suitable data structure is important as it affects both the performance and functionality of Java applications. While using a shopping app, sorting through the unending list of products is done by using the data structure technique. The data structure can be used in various fields, including computer graphics, operating systems, artificial intelligence, etc. It is a set of methods used for structuring data in computer memory.

Overview

The data structure is not written in any programming language rather it is a set of algorithms used for structuring data in computer memory to enhance the functionality of many applications. In this article, complete information regarding data structure in Java, data structures in Java with examples, data structures and algorithms in Java, etc, are discussed.

What is Data Structure?

The data structure is a specific way of storing and organizing data in computer memory to make it more useful. This is not only used for storing and organizing data but also used for arranging, processing, accessing, and retrieving data. The data structure can be defined as a collection of data with precise operations and qualities. Data structure helps users simply access the required data.

Need for Data Structures in Java

Applications get complicated due to the large amount of data. This leads to various problems in handling the data.

1. As the data grows rapidly high processing speed is required to handle a large amount of data.

2. Searching for the required data from a massive amount of data makes the searching process slow down.

3. Multiple requests by millions of users at a single time may lead to server breakdown.

To overcome these problems data structure is used. This technique helps the user to get the required data instantly.

Types of Data Structures

Mainly there are two types of data structure

1. primitive data structure

2. Non-primitive data structure

Some common types of data structures include

1. Array

2. Linked List

3. Stack

4. Queue

5. Graph

6. set

Primitive Data Structure

Primitive data structures are primitive data types that include int, char, float, double, and pointer. These data structures hold a single value.

Non-primitive Data Structure

Non-primitive data structures can be classified into two types:

1. Linear data structure: In linear data structure the data are arranged in a sequential manner in which one element is connected to another element in linear form. These are single-level data structures. Arrays, linked lists, stacks, and queues are known as linear data structures.

2. Nonlinear data structure: In nonlinear data structure, one element is connected to the ‘n’ number of elements. In this structure, elements are arranged in random ways. These are multi-level data structures. Trees and graphs are known as nonlinear data structures.

Major Operations

The following operations can be performed on a data structure.

1. Searching: An element in a data structure can be easily searched.

2. Sorting: Elements of a data structure can be sorted either in ascending or descending order.

3. Insertion: A new element can be inserted in a data structure.

4. Updation: An element in the data structure can be replaced by another element.

5. Deletion: An element can be deleted from the data structure by using this operation.

Which Data Structure?

A particular ADT (Abstract Data type) is executed by using some data structure. In this process, ADT gives an idea about what is to be done, and the data structure tells how it is to be implemented. In a particular ADT, various types of data structures can be performed depending on the time and space. So, which data structure is to be selected depends upon the user’s requirements.

Advantages of Data Structures

1. Efficient organization and storage of data: The data on data structure can be easily accessed, retrieved, and modified. Through efficient organization techniques, data structure makes it easy to handle complex data relationships.

2. Developed time and space complexity: This feature helps in performing major operations such as searching, insertion, deletion, and sorting in an efficient way. The user can select the appropriate data structure according to the priority based on space and time.

3. Improved data manipulation: Complex data manipulation, such as sorting, merging, and searching, is executed by using the data structure.

4. Flexibility and adaptability: With the help of object-oriented programming principles, custom data structures can be created.

Data Structures Index

DS Basics

DS Tutorial

DS Introduction

DS Algorithm

Ds Asymptotic Analysis

DS Pointer

DS Structure

DS Array

Array

2D Array

DS Linked List

Linked List

Insertion at beginning

Insertion at end

Insertion after specified node

Deletion at beginning

Deletion at end

Deletion after specified node

Traversing

Searching

Doubly Linked List

Insertion at beginning

Insertion at end

Insertion after specified node

Deletion at beginning

Deletion at end

Deletion of node having given data

Traversing

Searching

Circular Linked List

Insertion at beginning

Insertion at end

Deletion at beginning

Deletion at the end

Traversing

Searching

Circular Doubly List

Insertion at beginning

Insertion at end

Deletion at beginning

Deletion at the end

DS Stack

DS Stack

Array Implementation

Linked List Implementation

DS Queue

DS Queue

Array Implementation

Linked List Implementation

Circular Queue

DS Tree

Tree

Binary Tree

Pre-order Traversal

In-order Traversal

Post-order Traversal

Binary Search Tree

Searching in BST

Insertion in BST

Deletion in BST

AVL Tree

Insertion in AVL Tree

LL Rotation

LR Rotation

RL Rotation

RR Rotation

Deletion in AVL Tree

B Tree

B Tree

Red Black Tree

DS Graph

DS Graph

Graph Implementation

BFS Algorithm

DFS Algorithm

Spanning Tree

Prim's Algorithm

Kruskal's Algorithm

DS Searching

Linear Search

Binary Search

DS Sorting

Bubble Sort

Bucket Sort

Comb Sort

Counting Sort

Heap Sort

Insertion Sort

Merge Sort

Quick Sort

Radix Sort

Selection Sort

Shell Sort

Bitonic Sort

Cocktail Sort

Cycle Sort

Tim Sort

Classification of Data Structures

Singly Linked List

This linked list contains a node with a single pointer pointing to the next node. So this is also called a one-way list. This linked list stores data and references to the next node or a null value. The start pointer stores the linked list's first address and the last node's next pointer null value.

Circular Linked List

In a circular linked list, all the nodes are aligned to form a circle. Any node can be considered as a first node, and no null node at the end.

Doubly Linked List

In a doubly linked list traversing in both directions is possible. This linked list contains two pointers n which one is pointing to the next node and another is pointing to the previous node.

Example: A Java program to show the implementation of a linked list.

import java.util.*;  
public class LinkedList{  
     public static void main(String args[]){  
         
         LinkedList<String> ll=new LinkedList<String>();
         ll.add("Red");  
         ll.add("Blue");  
         ll.add("Yellow");  
         ll.add("Orange");  
         
         System.out.println(ll);
         
         }  
}  

Stack

Stack follows the last in first out (LIFO) data structure. It can be implemented as an array or linked list. Insertion in a stack is known as pushing denoted as push() and deletion is known as popping denoted as pop() and both operations can be done at the top of the stack only. Stacks can be used in parenthesis matching, solving the maze problem, nested function calls, etc. The syntax of the stack is represented below.

Stack var1 = new Stack(size);

Queue

Queue follows the first in first out (FIFO) data structure. In this insertion is done at the rear end denoted as enqueue() and deletion is done at the front end of the queue denoted as dequeue().

Binary Search Tree

Here the elements are arranged by following some order. In a binary search tree, the value of the left node must be lesser than the parent node, and the value of the right node must be larger than the parent node. Various operations such as searching, insertion, and deletion is easy in the binary search tree.

Heap

Applications related to priority, scheduling algorithms, caching, etc can be executed using a heap. Heap is a tree-based data structure in which the tree is considered as a complete binary tree. In this tree, the node can have utmost two children.

Hashing

Hashing is used to quickly rapidly a particular value within a given array. In this, each element has a unique hash code and the hash code is stored instead of the actual element.

Graph

This nonlinear data structure consists of vertices and edges. The vertices are referred to as nodes and edges are lines that again connect any two nodes in the graph. Connected data are stored by using a graph data structure. An example of graph data structure includes a network of people or a network of cities.

Array

The array is a collection of similar data items stored at connecting memory locations. In an array fixed size elements of the same data type are stored.

Example: A program to show the implementation of the array.

class Array
{
    public static void main (String[] args)
    {        
      int[] array;
               array = new int[5];
               array[0] = 1;
               array[1] = 4;     
      array[2] = 15;
      array[3] = 21;
      array[4] = 6;
      for (int i = 0; i < arr.length; i )
         System.out.println(array[i]);   
    }
}

Advantages of Arrays

1. Easily store elements of the same data type in.

2. Other data structures like stack and queue can also be implemented using an array.

3. There is no issue of overload or shortage of memory.

4. Data in arrays can be easily accessed.

Disadvantages of Arrays

1. Size of the array cannot be changed in the array.

2. In an array heterogeneous data cannot be stored.

Matrix

In a matrix, numbers are stored in rows and columns.

Conclusion

Complete information related to the data structure is presented here. The data structure is a set of methods used for structuring data in computer memory. Various types of data structures include arrays, stacks, linked lists, queues, sets, and graphs. The data structures are defined and listed to offer a clear idea to the user.

FAQs

1. What is data structure?

The data structure can be defined as a collection of data with precise operations and qualities. Data structure helps users simply access the required data.

2. What are the major operations of data structure?

The major operations of data structure include searching, sorting, deletion, and updation.

3. What are the main types of data structure?

The different types of data structures include arrays, stacks, linked lists, queues, sets, and graphs.

Take the Free Quiz on Java

Answer quick questions and assess your Java knowledge

Start Quiz