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Data structures are fundamental to any programming language. The choice of a particular data structure has a significant impact on the functionality and performance of Java applications, thus it is worthwhile to master data structures in Java.

This guide will help beginners to understand what is data structures, what is data structures in Java, the types of data structures in Java and many more.

What is Java?
What are Data Structures?
What are Data Structures in Java?
Types of Data Structures in Java
Advantages of Data Structures in java
Classification of Data Structures
Data Structures in Java FAQs

What is Java?

Java Programming is a high-level programming language created by sun microsystems. This programming language is reliable, object-oriented and secure. Java follows the WORA principle, which stands for “Write Once Run Anywhere”. You can run a java program as many times as you want on a java supported platform after it is compiled.

What are Data Structures?

A data structure is defined as a format for arranging, processing, accessing, and storing data. Data structures are the combination of both simple and complex forms, all of which are made to organise data for a certain use. Users find it simple to access the data they need and use it appropriately thanks to data structures.

To make you understand in simpler terms, look at the below example

If you want to store data in

One on the other - Stacks
Linear fashion - Array/ Linked List
Hierarchical Fashion - Trees
Connect Nodes - Graph

What are Data Structures in Java?

Data Structure in java is defined as the collection of data pieces that offers an effective means of storing and organising data in a computer. Linked List, Stack, Queue, and arrays are a few examples of java data structures.

Types of Data Structures in Java

Here is the list of some of the common types of data structures in Java:

Array
Linked List
Stack
Queue
Binary Tree
Binary Search Tree
Heap
Hashing
Graph

Here is the pictorial representation of types of java data structures

To learn more about Java Programming, you can take up a free online course offered by Great Learning Academy and upskill today. If you are already well-versed with the basics, go ahead and enrol yourself in the Data Structure & Algorithms in Java for Intermediate Level.

Further classification of types of Data Structures

There are two types of Data Structures:-

Primitive Data Structures
Non-primitive Data Structures

Primitive data Structures are also called Primitive Data Types. byte, short, int, float, char, boolean, long, and double are primitive Data types.

Non-primitive data Structures – Non-primitive Data Structures are of two types:-

Linear Data Structures
Non-linear Data Structures

Linear Data Structures – The elements arranged in a linear fashion are called Linear Data Structures. Here, each element is connected to one other element only. Linear Data Structures are as follows:

Arrays
- Single dimensional Array
- Multidimensional Array

Stack
Queue

Linked List
- Singly-linked list
- Doubly Linked list
- Circular Linked List

Non-Linear Data Structures – The elements arranged in a non-linear fashion are called Non-Linear Data Structures. Here, each element is connected to n-other elements. Non-Linear Data Structures are as follows:

Trees
- Binary Tree
- Binary Search Tree
- AVL Tree
- Red-Black Tree

Heap
- MaxHeap
- MinHeap

Hash
- HashSet
- HashMap

Advantages of Data Structures in java

Efficiency
Reusability
Processing Speed
Abstraction
Data Searching

Classification of Data Structures

Data Structures can be classified as:-

Static Data Structures are the Data structures whose size is declared and fixed at Compile Time and cannot be changed later are called Static Data structures.
Example – Arrays
Dynamic Data Structures are the Data Structures whose size is not fixed at compile time and can be decided at runtime depending upon requirements are called Dynamic Data structures.
Example – Binary search tree using Java

Syntax:

Array declaration
datatype varname []=new datatype[size];  
datatype[] varname=new datatype[size];

Array

What is an Array?

An array is the simplest data structure where a collection of similar data elements takes place and each data element can be accessed directly by only using its index number.

Array Advantages

Random access
Easy sorting and iteration
Replacement of multiple variables

Array Disadvantages

Size is fixed
Difficult to insert and delete
If capacity is more and occupancy less, most of the array gets wasted
Needs contiguous memory to get allocated

Array Applications

For storing information in a linear fashion
Suitable for applications that require frequent searching

Java Program using Array

import java.util.*;

class JavaDemo {
	public static void main (String[] args) {
	    int[] priceOfPen= new int[5];
	    Scanner in=new Scanner(System.in);
	    for(int i=0;i<priceOfPen.length;i++)
	        priceOfPen[i]=in.nextInt();

	    for(int i=0;i<priceOfPen.length;i++)
		    System.out.print(priceOfPen[i]+" ");
	}
}


Input:
23 13 56 78 10

Output:
23 13 56 78 10

Linked List

What is Linked List?

Linked list data structure helps the required objects to be arranged in a linear order.

Linked List Advantages

Dynamic in size
No wastage as capacity and size is always equal
Easy insertion and deletion as 1 link manipulation is required
Efficient memory allocation

Linked List Disadvantages

If head Node is lost, the linked list is lost
No random access is possible

Linked List Applications

Suitable where memory is limited
Suitable for applications that require frequent insertion and deletion

Java Program on Linked List


import java.util.*;

class LLNode{

	int data;
	LLNode next;
	
	LLNode(int data)
	{
		this.data=data;
		this.next=null;
		
	}
}


class Demo{
	
	LLNode head;
	
	
	LLNode insertInBeg(int key,LLNode head)
	{
		LLNode ttmp=new LLNode(key);
		
		if(head==null)
			head=ttmp;
		
		else
			{
				ttmp.next=head;
				head=ttmp;
			}
		return head;
	}
	
	
	LLNode insertInEnd(int key,LLNode head)
	{
		LLNode ttmp=new LLNode(key);
		LLNode ttmp1=head;
		
		if(ttmp1==null)
			head=ttmp;
		else
		{
			while(ttmp1.next!=null)
					ttmp1=ttmp1.next;
			ttmp1.next=ttmp;
			
		}
		
		return head;
			
	}


	LLNode insertAtPos(int key,int pos,LLNode head)
	{
		LLNode ttmp=new LLNode(key);
		
		if(pos==1)
		{
			ttmp.next=head;
			head=ttmp;
		}
		else
		{
			LLNode ttmp1=head;
			for(int i=1;ttmp1!=null && i<pos;i++)
				ttmp1=ttmp1.next;
			ttmp.next=ttmp1.next;
			ttmp1.next=ttmp;
		}
		
		return head;
	}
	
	
	LLNode delete(int pos,LLNode head)
	{
		LLNode ttmp=head;
		if(pos==1)
			head=ttmp.next;
		else
		{
			for(int i=1;ttmp!=null && i<pos-1;i++)
				ttmp=ttmp.next;
			ttmp.next=ttmp.next.next;
		}
		return head;
	}
	
	int length(LLNode head)
	{
		LLNode ttmp=head;
		int c=0;
		if(ttmp==null)
			return 0;
		else
		{
		 while(ttmp!=null)
			{	ttmp=ttmp.next;
				c++;
			}
		}
		return c;
	}
	
	
	LLNode reverse(LLNode head)
	{
		LLNode prevLNode=null,curLNode=head,nextLNode=null;
		while(curLNode!=null)
		{
			nextLNode=curLNode.next;
			curLNode.next=prevLNode;
			
			prevLNode=curLNode;
			curLNode=nextLNode;
		}
		
		head=prevLNode;
		return head;
	}
	
	
	void display(LLNode head)
	{
		LLNode ttmp=head;
		while(ttmp!=null)
			{System.out.print(ttmp.data+" ");
			 ttmp=ttmp.next;
			}
	}
	
	public static void main(String[] args)
	{
		LinkedListDemo l=new LinkedListDemo();
		l.head=null;
		Scanner in=new Scanner(System.in);
		 do
	{
 System.out.println("n********* MENU *********");
	 System.out.println("n1.Insert In End");
	 System.out.println("n2.Insert In Beg");
	 System.out.println("n3.Insert At A  Particular Pos");
	 System.out.println("n4.Delete At a Pos");
	 System.out.println("n5.Length");
	 System.out.println("n6.Reverse");
	 System.out.println("n7.Display");
	 System.out.println("n8.EXIT");
	 System.out.println("nenter ur choice : ");
	 int n=in.nextInt();
	 switch(n)
		{case 1: System.out.println("nenter the value ");
			  l.head=l.insertInEnd(in.nextInt(),l.head);
			 break;
		 case 2: System.out.println("nenter the value");
			 l.head=l.insertInBeg(in.nextInt(),l.head);
			 break;
		 case 3: System.out.println("nenter the value");
			 l.head=l.insertAtPos(in.nextInt(),in.nextInt(),l.head);
			 break;
		 case 4: 
			 l.head=l.delete(in.nextInt(),l.head);
			 break;
		 case 5: 
			System.out.println(l.length(l.head));
			 break;
		 case 6: 
			 l.head=l.reverse(l.head);
			 break;
		 case 7: 
			l.display(l.head);
		 		 break;
		 case 8: System.exit(0);
		 		 break;
		 default: System.out.println("n Wrong Choice!");
		 		  break;
		}
	 System.out.println("n do u want to cont... ");
	}while(in.nextInt()==1);

 }
}





Output:

********* MENU *********

1.Insert In End

2.Insert In Beg

3.Insert At A  Particular Pos

4.Delete At a Pos

5.Length

6.Reverse

7.Display

8.EXIT

enter ur choice :
1

enter the value
23

 do u want to cont...
1

********* MENU *********

1.Insert In End

2.Insert In Beg

3.Insert At A  Particular Pos

4.Delete At a Pos

5.Length

6.Reverse

7.Display

8.EXIT

enter ur choice :
1

enter the value
56

 do u want to cont...
1

********* MENU *********

1.Insert In End

2.Insert In Beg

3.Insert At A  Particular Pos

4.Delete At a Pos

5.Length

6.Reverse

7.Display

8.EXIT

enter ur choice :
2

enter the value
10

 do u want to cont...
1

********* MENU *********

1.Insert In End

2.Insert In Beg

3.Insert At A  Particular Pos

4.Delete At a Pos

5.Length

6.Reverse

7.Display

8.EXIT

enter ur choice :
7
10 23 56
 do u want to cont...
1

********* MENU *********

1.Insert In End

2.Insert In Beg

3.Insert At A  Particular Pos

4.Delete At a Pos

5.Length

6.Reverse

7.Display

8.EXIT

enter ur choice :
3

enter the value
67
2

 do u want to cont...
1

********* MENU *********

1.Insert In End

2.Insert In Beg

3.Insert At A  Particular Pos

4.Delete At a Pos

5.Length

6.Reverse

7.Display

8.EXIT

enter ur choice :
7
10 23 67 56
 do u want to cont...
1

********* MENU *********

1.Insert In End

2.Insert In Beg

3.Insert At A  Particular Pos

4.Delete At a Pos

5.Length

6.Reverse

7.Display

8.EXIT

enter ur choice :
4
2

 do u want to cont...
1

********* MENU *********

1.Insert In End

2.Insert In Beg

3.Insert At A  Particular Pos

4.Delete At a Pos

5.Length

6.Reverse

7.Display

8.EXIT

enter ur choice :
7
10 67 56
 do u want to cont...
1

********* MENU *********

1.Insert In End

2.Insert In Beg

3.Insert At A  Particular Pos

4.Delete At a Pos

5.Length

6.Reverse

7.Display

8.EXIT

enter ur choice :
6

 do u want to cont...
1

********* MENU *********

1.Insert In End

2.Insert In Beg

3.Insert At A  Particular Pos

4.Delete At a Pos

5.Length

6.Reverse

7.Display

8.EXIT

enter ur choice :
7
56 67 10
 do u want to cont...

Stack

What is a stack?

A stack is a representation of nodes. There are two components to each node: data and next (storing address of next node). Each node’s data portion contains the assigned value, and its next pointer directs the user to the node that has the stack’s subsequent item. The highest node in the stack is referred to as the top.

Features of Stack

Linear Data Structures using Java
Follows LIFO: Last In First Out
Only the top elements are available to be accessed
Insertion and deletion takes place from the top
Eg: a stack of plates, chairs, etc
4 major operations:
- push(ele) – used to insert element at top
- pop() – removes the top element from stack
- isEmpty() – returns true is stack is empty
- peek() – to get the top element of the stack
All operation works in constant time i.e, O(1)

Stack Advantages

Maintains data in a LIFO manner
The last element is readily available for use
All operations are of O(1) complexity

Stack Disadvantages

Manipulation is restricted to the top of the stack
Not much flexible

Stack Applications

Recursion
Parsing
Browser
Editors

Java Program using Stack

import java.util.*;

class Stack
{
   int[] a;
   int top;
   Stack()
   {	
	a=new int[100];
	top=-1;
   }
  
  void push(int x)
  {	
	if(top==a.length-1)
	  System.out.println("overflow");
	else
	 a[++top]=x;
   }
   
   int pop()
   {
     if(top==-1)
		{System.out.println("underflow");
	     return -1;
		}
	 else
	   return(a[top--]);
	}
	
	void display()
	{
		for(int i=0;i<=top;i++)
			System.out.print(a[i]+" ");
		System.out.println();	
	}
	
	boolean isEmpty()
	{
		if(top==-1)
			return true;
		else 
			return false;
	}
	
	int peek()
	{
		if(top==-1)
			return -1;
		return (a[top]);
	}
	
	
}

public class Demo
{
	public static void main(String args[])
	{
		
		Stack s=new Stack();
		Scanner in= new Scanner(System.in);
		
		 do
			{System.out.println("n******** MENU *******");
			 System.out.println("n1.PUSH");
			 System.out.println("n2.POP");
			 System.out.println("n3.PEEK");
			 System.out.println("n4 IS EMPTY");
			 System.out.println("n5.EXIT");
			 System.out.println("n enter ur choice : ");
			 switch(in.nextInt())
				{
				 case 1: 
					 System.out.println("nenter the value ");
					 s.push(in.nextInt());
					 break;
				 case 2: 
					System.out.println("n popped element : "+ s.pop());
					 break;
				 
				case 3: 
					System.out.println("n top element : "+ s.peek());
					 break;
				 case 4: System.out.println("n is empty : "+ s.isEmpty());
						 break;
				 case 5: System.exit(0);
						 break;
				 default: System.out.println("n Wrong Choice!");
						  break;
				}
			 System.out.println("n do u want to cont... ");
			}while(in.nextInt()==1);

	}
}






Output:

******** MENU *******

1.PUSH

2.POP

3.PEEK

4 IS EMPTY

5.EXIT

 enter ur choice :
1

enter the value
12

 do u want to cont...
1

******** MENU *******

1.PUSH

2.POP

3.PEEK

4 IS EMPTY

5.EXIT

 enter ur choice :
1

enter the value
56

 do u want to cont...
1

******** MENU *******

1.PUSH

2.POP

3.PEEK

4 IS EMPTY

5.EXIT

 enter ur choice :
2

 popped element : 56

 do u want to cont...
1

******** MENU *******

1.PUSH

2.POP

3.PEEK

4 IS EMPTY

5.EXIT

 enter ur choice :
4

 is empty : false

 do u want to cont...
1

******** MENU *******

1.PUSH

2.POP

3.PEEK

4 IS EMPTY

5.EXIT

 enter ur choice :
2

 popped element : 12

 do u want to cont...

Java Data structure program of Stack – using LinkedList

import java.util.*;

class LNode
{
	 int data;
	 LNode next;
	 LNode(int d)
	 {
		data=d;
	 }
	 
}

 class Stack
{
	 LNode push(int d,LNode head){  
		
				LNode tmp1 = new LNode(d);
				
				if(head==null)
				   
					head=tmp1;
				
				else
				{
					tmp1.next=head;
					
					head=tmp1;
				}
				return head;
			 }
			 
			 
	 LNode pop(LNode head){
		   
		    if(head==null)
		        System.out.println("underflow");
		   else
				head=head.next;
			return head;
		 }
	

	void display(LNode head){
		
				System.out.println("n list is : ");
				if(head==null){
					
					System.out.println("no LNodes");
			
					return;
					}
				 
				LNode tmp=head;

				while(tmp!=null){
						
				System.out.print(tmp.data+" ");
					 
				tmp=tmp.next;
					 
					
				}
	       }

    boolean isEmpty(LNode head)
	{
		if(head==null)
			return true;
		else
			return false;
	}
	
	int peek(LNode head)
	{
		if(head==null)
			return -1;
		return head.data;
	}
	
}


public class Demo{
		
		public static void main(String[] args)
		{
		Stack s=new Stack();
		LNode head=null;
		Scanner in=new Scanner(System.in);
		
		 do
			{System.out.println("n******** MENU *******");
			 System.out.println("n1.PUSH");
			 System.out.println("n2.POP");
			 System.out.println("n3.PEEK");
			 System.out.println("n4 IS EMPTY"); 
			 System.out.println("n5 DISPLAY");
			 System.out.println("n6.EXIT");
			 System.out.println("n enter ur choice : ");
			 switch(in.nextInt())
				{
				 case 1: 
					 System.out.println("nenter the value ");
					 head=s.push(in.nextInt(),head);
					 break;
				 case 2: 
					 head=s.pop(head);
					 break;
				 
				case 3: 
				System.out.println("n top element : "+ s.peek(head));
					 break;
				 case 4: 
System.out.println("n is empty : "+ s.isEmpty(head));
						 break;
				 case 5: s.display(head); 
						 break;
				 case 6: System.exit(0);
						 break;
				 default: System.out.println("n Wrong Choice!");
						  break;
				}
			 System.out.println("n do u want to cont... ");
			}while(in.nextInt()==1);

	}
}





Output
******** MENU *******

1.PUSH

2.POP

3.PEEK

4 IS EMPTY

5 DISPLAY

6.EXIT

 enter ur choice :
1

enter the value
12

 do u want to cont...
1

******** MENU *******

1.PUSH

2.POP

3.PEEK

4 IS EMPTY

5 DISPLAY

6.EXIT

 enter ur choice :
1

enter the value
56

 do u want to cont...
1

******** MENU *******

1.PUSH

2.POP

3.PEEK

4 IS EMPTY

5 DISPLAY

6.EXIT

 enter ur choice :
5

 list is :
56 12
 do u want to cont...
1

******** MENU *******

1.PUSH

2.POP

3.PEEK

4 IS EMPTY

5 DISPLAY

6.EXIT

 enter ur choice :
3

 top element : 56

 do u want to cont...
1

******** MENU *******

1.PUSH

2.POP

3.PEEK

4 IS EMPTY

5 DISPLAY

6.EXIT

 enter ur choice :
4

 is empty : false

 do u want to cont...
1

Queue

What is Queue?

The queue is called an abstract data structure. Data is always added to one end (enqueued), and removed from the other (dequeue). Queue uses the First-In-First-Out approach and data item that was stored initially will be accessed first in a queue.

Features of Queue

Linear Data Structure
Follows FIFO: First In First Out
Insertion can take place from the rear end.
Deletion can take place from the front end.
Eg: queue at ticket counters, bus station
4 major operations:
- enqueue(ele) – used to insert element at top
- dequeue() – removes the top element from queue
- peekfirst() – to get the first element of the queue
- peeklast() – to get the last element of the queue
All operation works in constant time i.e, O(1)

Queue Advantages

Maintains data in FIFO manner
Insertion from beginning and deletion from end takes O(1) time

Queue Applications

Scheduling
Maintaining playlist
Interrupt handling

Variations in Queue: Two popular variations of queues are Circular queues and Dequeues.

Java program of Queue- using Array


import java.util.*;

class Queue{

 int front;
 int rear;
 int[] arr;
 
 Queue()
 {
   front=rear=-1;
   arr=new int[10];
  }
  
  void enqueue(int a)
  {
    if(rear==arr.length-1)
		System.out.println("overflow");
	else
		arr[++rear]=a;
	
	if(front==-1)
		front++;
   }
   
   int dequeue()
   {
     int x=-1;
	 if(front==-1)
		System.out.println("underflow");
	 else
		x=arr[front++];
	 if(rear==0)
	     rear--;
	 return x;
    }
	
	void display()
	{
	  for(int i=front;i<=rear;i++)
		System.out.print(arr[i]+" ");

	 System.out.println();


	}
}

public class QueueDemo{

	public static void main(String[] args)
	{
	  Queue ob=new Queue();
	  ob.enqueue(1);
	  ob.enqueue(2);
	  ob.enqueue(3);
	  ob.enqueue(4);
	  ob.enqueue(5);
	  ob.display();
	  ob.dequeue();
	  ob.display();
	 }
}
	  




Output:


1 2 3 4 5 
2 3 4 5

Demonstration of Queue- using LinkedList

class LNode{
	
	int data;
	LNode next;

	LNode(int d)
	{
		data=d;
	}
}


class Queue{

	LNode enqueue(LNode head,int a)
	{
		LNode tmp=new LNode(a);
		if(head==null)
			head=tmp;
		else
		 { 
			LNode tmp1=head;
			while(tmp1.next!=null)
				tmp1=tmp1.next;
			
			tmp1.next=tmp;
		}
		return head;
	}
	
	
	LNode dequeue(LNode head)
	{
		if(head==null)
		        System.out.println("underflow");
		   else
				head=head.next;
			return head;
	}
	
	void display(LNode head)
	{
		
				System.out.println("n list is : ");
				if(head==null){
					
					System.out.println("no LNodes");
			
					return;
					}
				 
				LNode tmp=head;

				while(tmp!=null){
						
				System.out.print(tmp.data+" ");
					 
				tmp=tmp.next;
					 
					
				}
	}
	
	}
	
	public class QueueDemoLL{
		
		public static void main(String[] args)
		{
			Queue ob=new Queue();
			LNode head=null;
			
			head=ob.enqueue(head,1);
			head=ob.enqueue(head,2);
			head=ob.enqueue(head,3);
			head=ob.enqueue(head,4);
			head=ob.enqueue(head,5);
			ob.display(head);
			head=ob.dequeue(head);
			ob.display(head);
		}
	}




Output

list is : 
1 2 3 4 5 
list is : 
2 3 4 5

Binary Tree

What is a Binary Tree?

In a binary tree, the branches of the tree are made up of up to two child nodes for each node. The left and right nodes are the common names for the two youngsters. Child nodes make references to their parents, whereas parent nodes are nodes with children.

Features of Binary Tree

Hierarchical Data Structure
The topmost element is known as the root of the tree
Every Node can have at most 2 children in the binary tree
Can access elements randomly using index
Eg: File system hierarchy
Common traversal methods:
- preorder(root) : print-left-right
- postorder(root) : left-right-print
- inorder(root) : left-print-right

Binary Tree Advantages

Can represent data with some relationship
Insertion and search are much more efficient

Binary Tree Disadvantages

Sorting is difficult
Not much flexible

Binary Tree Applications

File system hierarchy
Multiple variations of the binary tree have a wide variety of applications

Demonstration of Binary Tree

class TLNode
{
 int data;
 TLNode left,right;
 
 TLNode(int d)
 {
   data=d;
  }
 }
 
 
public class BinaryTree
{
   static void preorder(TLNode r)
   {
		if(r==null)
		    return;
		
		System.out.print(r.data+" ");
		
		preorder(r.left);
		preorder(r.right);
		
   }
   static void inorder(TLNode r)
   {
		if(r==null)
		    return;
		
		
		inorder(r.left);
		System.out.print(r.data+" ");
		inorder(r.right);
		
   }
   static void postorder(TLNode r)
   {
		if(r==null)
		    return;
		
		
		postorder(r.left);
		postorder(r.right);
		System.out.print(r.data+" ");

   }
     
    public static void main(String[] args)
	{
		TLNode root=new TLNode(1);
		
		root.left=new TLNode(2);
		root.right=new TLNode(3);
		
		root.left.left=new TLNode(4);
		root.left.right=new TLNode(5);
		
		root.right.left=new TLNode(6);
		root.right.right=new TLNode(7);
		preorder(root);
		System.out.println();
		
		inorder(root);
		System.out.println();
		
		postorder(root);
		System.out.println();
		
		
	}
}



	 
Output
	
1 2 4 5 3 6 7 
4 2 5 1 6 3 7 
4 5 2 6 7 3 1

Binary Search Tree

What is a Binary Search Tree?

The binary search tree is an advanced algorithm which is used to analyse the nodes, branches and many more. The BST was developed using the architecture of a fundamental binary search algorithm, allowing for quicker node lookups, insertions, and removals.

Features of Binary Search Tree

A binary tree with the additional restriction
Restriction:
- The left child must always be less than the root node
- The right child must always be greater than the root node
Insertion, Deletion, Search is much more efficient than a binary tree

Binary Search Tree Advantages

Maintains order in elements
Can easily find the min and max Nodes in the tree
In order, traversal gives sorted elements

Binary Search Tree Disadvantages

Random access is not possible
Ordering adds complexity

Binary Search Tree Applications

Suitable for sorted hierarchical data

Demonstration of Binary Search Tree

class TLNode{

	int data;
	TLNode left,right;
	
	TLNode(int d)
	{
		data=d;
	}
 }
 
 public class BST{
 
	TLNode root;
	
	TLNode insert(int d,TLNode root)
	{
	  if(root==null)
	    root=new TLNode(d);
	  
      else if(d<=root.data)
		root.left=insert(d,root.left);
	
	  else
		root.right=insert(d,root.right);
	
	  return root;
	}
	
	TLNode search(int d,TLNode root)
	{
		if(root.data==d)
			return root;
		else if(d<root.data)
			return search(d,root.left);
	    else
			return search(d,root.right);
	}
	
	
	
	void inorder(TLNode r)
   {
		if(r==null)
		    return;
		
		
		inorder(r.left);
		System.out.println(r.data);
		inorder(r.right);
		
   }
   

TLNode delete(TLNode root, int data) 
    { 
        
        if (root == null)  return root; 
 
        if (data < root.data) 
            root.left = delete(root.left, data); 
        else if (data > root.data) 
            root.right = delete(root.right, data); 
  
        else
        { 
            
            if (root.left == null) 
                return root.right; 
            else if (root.right == null) 
                return root.left; 
  
            
            root.data = minValue(root.right); 
  
            root.right = delete(root.right, root.data); 
        } 
  
        return root; 
    } 	
   int minValue(TLNode root) 
    { 
        int minv = root.data; 
        while (root.left != null) 
        { 
            minv = root.left.data; 
            root = root.left; 
        } 
        return minv; 
    } 

   
   public static void main(String[] args)
   {
		BST ob=new BST();
		ob.root=ob.insert(50,ob.root); 
                ob.root=ob.insert(30,ob.root); 
                ob.root=ob.insert(20,ob.root); 
                ob.root=ob.insert(20,ob.root); 
                ob.root=ob.insert(70,ob.root); 
                ob.root=ob.insert(60,ob.root); 
                ob.root=ob.insert(80,ob.root);    
		ob.root=ob.delete(ob.root,50);
		System.out.println("******" +ob.root.data);
		ob.inorder(ob.root);
		
		TLNode find=ob.search(30,ob.root);
		if(find==null)
			System.out.println("not found");
		else
			System.out.println("found : "+find.data);
		
		
	}
}

  Output:
  
******60
20
20
30
60
70
80
found : 30

Heap

Binary Heap can be visualized array as a complete binary tree
Arr[0] element will be treated as root
length(A) – size of array
heapSize(A) – size of heap
Generally used when we are dealing with minimum and maximum elements
For ith node

(i-1)/2	Parent
(2*i)+1	Left child
(2*i)+2	Right Child

Heap Advantages

Can be of 2 types: min heap and max heap
Min heap keeps the smallest element and top and max keep the largest
O(1) for dealing with min or max elements

Heap Disadvantages

Random access is not possible
Only min or max element is available for accessibility

Heap Applications

Suitable for applications dealing with priority
Scheduling algorithm
caching

Program of Max Heap

import java.util.*;


class Heap{

	int heapSize;
	
	void build_max_heap(int[] a)
	{
		heapSize=a.length;
		for(int i=(heapSize/2);i>=0;i--)
			max_heapify(a,i);
		
	}
	
	void max_heapify(int[] a,int i)
	{
		int l=2*i+1;
		int r=2*i+2;
		int largest=i;
		if(l<heapSize &&a[l]>a[largest])
			largest=l;
		if(r<heapSize &&a[r]>a[largest])
			largest=r;
		if(largest!=i)
		{
			int t=a[i];
			a[i]=a[largest];
			a[largest]=t;
		    max_heapify(a,largest);
		}
		
	}
	
	//to delete the max element
	
	int extract_max(int[] a)
	{
		if(heapSize<0)
			System.out.println("underflow");
		int max=a[0];
		a[0]=a[heapSize-1];
		heapSize--;
		max_heapify(a,0);
		return max;
	}
	
	void increase_key(int[] a,int i,int key)
	{
		if(key<a[i])
			System.out.println("error");
		a[i]=key;
		while(i>=0 && a[(i-1)/2]<a[i])
		{
			int t=a[(i-1)/2];
			a[(i-1)/2]=a[i];
			a[i]=t;
			
			i=(i-1)/2;
		}
	}
	
	void print_heap(int a[])
	{
		for(int i=0;i<heapSize;i++)
		    System.out.println(a[i]+" ");
	}
}
	
public class HeapDemo{
	
	public static void main(String[] args)
	{
		Scanner in=new Scanner(System.in);
		int n=in.nextInt();
		int a[]=new int[n];
		
		System.out.println("enter the elements of array");
		
		for(int i=0;i<n;i++)
		  a[i]=in.nextInt();
	         Heap ob=new Heap();
		
		ob.build_max_heap(a);
		ob.print_heap(a);
		
		
		System.out.println("maximum element is : "+ob.extract_max(a));
		ob.print_heap(a);
		System.out.println("maximum element is : "+ob.extract_max(a));
		ob.increase_key(a,6,800);
		ob.print_heap(a);
		   
	}

}

Output
7
enter the elements of array
50 100 10 1 3 20 5
100
50
20
1
3
10
5
maximum element is : 100
50
5
20
1
3
10
maximum element is : 50
800
5
20
1
3

Hashing

Uses special Hash function
A hash function maps an element to an address for storage
This provides constant-time access
Collision resolution techniques handle collision
Collision resolution technique
- Chaining
- Open Addressing

Hashing Advantages

The hash function helps in fetching elements in constant time
An efficient way to store elements

Hashing Disadvantages

Collision resolution increases complexity

Hashing Applications

Suitable for the application needs constant time fetching

Demonstration of HashSet – to find string has unique characters

import java.util.*;

class HashSetDemo1{

	static boolean isUnique(String s)
	{
		HashSet<Character> set =new HashSet<Character>();
		
		for(int i=0;i<s.length();i++)
		    {
				char c=s.charAt(i);
				if(c==' ')
					continue;
				if(set.add(c)==false)
					return false;
					
			}
			
		return true;
	}
	
	
	public static void main(String[] args)
	{
		String s="helo wqty ";
		boolean ans=isUnique(s);
		if(ans)
			System.out.println("string has unique characters");
		else
			System.out.println("string does not have unique characters");

		
		
	}
}

Output:
string has unique characters

Demonstration of HashMap – count the characters in a string

import java.util.*;

class HashMapDemo
{

	static void check(String s)
	{
		HashMap<Character,Integer> map=new HashMap<Character,Integer>();
		for(int i=0;i<s.length();i++)
			{char c=s.charAt(i);
			 if(!map.containsKey(c))
				map.put(c,1);
			 else
				map.put(c,map.get(c)+1);
			}
			
		
		
		Iterator<Character> itr = map.keySet().iterator();
		while (itr.hasNext()) {
			Object x=itr.next();
			System.out.println("count of "+x+" : "+map.get(x));
		}
	}
	
	public static void main(String[] args)
	{
		String s="hello";
		check(s);
	}
}

Output
count of e : 1
count of h : 1
count of l : 2
count of o : 1

Demonstration of HashTable – to find strings has unique characters

import java.util.*; 
class hashTabledemo { 
	public static void main(String[] arg) 
	{ 
		// creating a hash table 
		Hashtable<Integer, String> h = 
					new Hashtable<Integer, String>(); 

		Hashtable<Integer, String> h1 = 
					new Hashtable<Integer, String>(); 

		h.put(3, "Geeks"); 
		h.put(2, "forGeeks"); 
		h.put(1, "isBest"); 

		// create a clone or shallow copy of hash table h 
		h1 = (Hashtable<Integer, String>)h.clone(); 

		// checking clone h1 
		System.out.println("values in clone: " + h1); 

		// clear hash table h 
		h.clear(); 

		// checking hash table h 
		System.out.println("after clearing: " + h); 
				System.out.println("values in clone: " + h1); 


	} 
} 

Output
values in clone: {3=Geeks, 2=forGeeks, 1=isBest}
after clearing: {}
values in clone: {3=Geeks, 2=forGeeks, 1=isBest}

Graph

Basically it is a group of edges and vertices
Graph representation
- G(V, E); where V(G) represents a set of vertices and E(G) represents a set of edges
The graph can be directed or undirected
The graph can be connected or disjoint

Graph Advantages

finding connectivity
Shortest path
min cost to reach from 1 pt to other
Min spanning tree

Graph Disadvantages

Storing graph(Adjacency list and Adjacency matrix) can lead to complexities

Graph Applications

Suitable for a circuit network
Suitable for applications like Facebook, LinkedIn, etc
Medical science

Demonstration of Graph

import java.util.*;

class Graph
{
	int v;
	LinkedList<Integer> adj[];

	Graph(int v)
	{
		this.v=v;
		adj=new LinkedList[v];
		for(int i=0;i<v;i++)
			adj[i]=new LinkedList<Integer>();
	}


	void addEdge(int u,int v)
	{
		adj[u].add(v);
	}
	
	void BFS(int s)
	{
		boolean[] visited=new boolean[v];
		LinkedList<Integer> q=new LinkedList<Integer>();
		q.add(s);
		visited[s]=true;

		while(!q.isEmpty())
		{
			int x=q.poll();
			System.out.print(x+" ");

			Iterator<Integer> itr=adj[x].listIterator();
			while(itr.hasNext())
			{
			  int p=itr.next();
			  if(visited[p]==false)
				{
					visited[p]=true;
					q.add(p);
				}
			}
		}
	}
	
	
	void DFSUtil(int s,boolean[] visited)
	{
		visited[s]=true;
		System.out.println(s);

		Iterator<Integer> itr=adj[s].listIterator();
		while(itr.hasNext())
		{
			int x=itr.next();
			if(visited[x]==false)
			{                                                        
				//visited[x]=true;

				DFSUtil(x,visited);
			} 
		}
	}
	
	
	void DFS(int s){
		boolean visited[]=new boolean[v];
		DFSUtil(s,visited);
	}

	public static void main(String[] args)
		{
			Graph g=new Graph(4);
			g.addEdge(0,1);
			g.addEdge(0,2);
			g.addEdge(1,2);
			g.addEdge(2,0);
			g.addEdge(2,3);
			g.addEdge(3,3);
			
			g.BFS(2);
			g.DFS(2);

		}
}

Output:
2 0 3 1 2
0
1
3

Data Structures in Java FAQs

Can I use Java for data structures?

Yes, you can use Java for data structures. Here, Java is just a programming language, and data structures help in storing and organizing the data in the required format.

What are the data structures of Java?

Some of the data structures of Java are:Linked Lists
Arrays
Stack
Queue
Graph
Set

Which data structure is best for Java?

There is no such best data structure for Java. But programmers will use arrays as it is one of the simplest and most widely used data structures.

What is the fastest data structure in Java?

For different problems, different data structures are the fastest. But in general, arrays are the fastest data structures in Java as it is a simple data structure.

Should I learn data structures in Java?

Yes, learning data structures in Java helps you in enhancing your programming knowledge. It is said that Data structures + Algorithms = Programs, so learning data structures is important.

Which language is best for DSA?

Language is just a medium, but in the current trend, Java or Python is the best language for DSA.

How many data structures are there in Java?

There are 2 data structures in Java. They are linear and non-linear (hierarchical) data structures.

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