DEV Community: Mohith

Atomicity

Mohith — Mon, 30 Mar 2026 01:10:21 +0000

Atomicity means a transaction is treated as one complete action, not as separate steps. All operations inside the transaction must succeed together. If any step fails, the entire transaction is cancelled, and the database returns to its original state. This prevents partial updates and keeps the data consistent.

A simple real-world example is a wallet transfer. When I transfer money, I expect it to behave as one single action. Either the full amount is deducted from the sender and added to the receiver, or nothing happens at all. If something fails in the middle, the system rolls everything back so no money is lost and no partial update occurs.

BEGIN;

-- Deduct money from Alice
UPDATE accounts
SET balance = balance - 200
WHERE name = 'Alice';

-- Intentional error (Charlie does not exist)
UPDATE accounts
SET balance = balance + 200
WHERE name = 'Charlie';

COMMIT;

In this case, the second update fails because the user Charlie does not exist. Since one step in the transaction fails, the entire transaction is cancelled. The database performs a rollback, and the commit does not take effect.

ROLLBACK;

After the rollback, Alice’s balance remains unchanged, and no partial deduction occurs. This behavior demonstrates Atomicity — either all operations succeed, or none of them are applied.

sql practice — filtering movies

Mohith — Sun, 29 Mar 2026 08:38:57 +0000

1. find all movies where special features is null

select * from film where special_features is null;

2. find movies with rental duration more than 7 days

select * from film where rental_duration > 7;

3. movies with rental rate 4.99 and replacement cost > 20

select * from film where rental_rate = 4.99 and replacement_cost > 20;

4. movies with rental rate 0.99 or rating pg-13

select * from film where rental_rate = 0.99 or rating = 'pg-13';

5. first 5 rows sorted alphabetically by title

select * from film order by title asc limit 5;

6. skip first 10 rows and fetch next 3 highest replacement cost

select * from film order by replacement_cost desc offset 10 limit 3;

7. movies with rating g, pg, pg-13

select * from film where rating in ('g','pg','pg-13');

8. movies with rental rate between 2 and 4

select * from film where rental_rate between 2 and 4;

9. movies with titles starting with "the"

select * from film where title like 'the%';

10. first 10 movies rate 2.99 or 4.99, rating r, title contains love

select * from film where (rental_rate in (2.99,4.99)) and rating='r' and title ilike '%love%' limit 10;

11. movies where title contains % symbol

select * from film where title like '%\%%' escape '\';

12. movies where title contains underscore

select * from film where title like '%\_%' escape '\';

13. titles start with a or b and end with s

select * from film where (title like 'a%s' or title like 'b%s');

14. title contains man, men, or woman

select * from film where title ilike '%man%' or title ilike '%men%' or title ilike '%woman%';

15. titles containing digits

select * from film where title ~ '[0-9]';

16. titles containing backslash

select * from film where title like '%\\%';

17. titles contain love or hate

select * from film where title ilike '%love%' or title ilike '%hate%';

18. first 5 titles ending with er, or, ar

select * from film where title ilike '%er' or title ilike '%or' or title ilike '%ar' limit 5;

Launch a Simple EC2 Instance, Run a Web Server & Access It from the Internet - CA28

Mohith — Sun, 29 Mar 2026 07:34:43 +0000

one of the first things you should try is launching an EC2 instance and hosting a simple website. In this guide, we'll create an EC2 instance, install a web server, and access it from the public internet.

Step 1 — Launch EC2 Instance

Go to AWS Console
Open EC2 Dashboard
Click Launch Instance

Configure:

Name

My-Web-Server

AMI

Amazon Linux 2023

Instance type

t2.micro (Free tier)

Step 2 — Configure Security Group

Allow SSH and HTTP traffic:
type - ssh & http is in port 22 & 88 sorce is my ip and anywhere

This allows:

SSH login
Public web access

Step 3 — Connect to EC2

Use EC2 Instance Connect web browser on console :

throught the above connect option present in it

Step 4 — Install Apache Web Server

Update packages

sudo yum update -y

Install Apache

sudo yum install httpd -y

Start server

sudo systemctl start httpd

Enable auto start

sudo systemctl enable httpd

Step 5 — Create Simple Website

Create index file:

sudo nano /var/www/html/index.html

Enter the html code

<!DOCTYPE html>
<html>
<head>
    <title>My EC2 Website</title>
</head>
<body>
    <h1>Hello from EC2 </h1>
    <p>My HTML is working!</p>
</body>
</html>

Save and exit.

Step 6 — Access Website from Internet

Copy Public IPv4 address
Open in browser:

http://your-public-ip

Example:

http://13.60.156.82

You should see:

Hello from EC2 
My first AWS hosted website

Architecture

Browser → Internet → EC2 Public IP → Apache → HTML Page

Common Issue (IMPORTANT)

If website not loading:
Check Security Group:
Wrong:

HTTP 80 → 0.0.0.0/32

Correct:

HTTP 80 → 0.0.0.0/0

This allows internet access.

Useful Commands

Check server status

sudo systemctl status httpd

Restart server

sudo systemctl restart httpd

Stop server

sudo systemctl stop httpd

What i Learned from this is

✅ Launch EC2 instance
✅ Configure security group
✅ Install Apache web server
✅ Deploy HTML page
✅ Access from internet

CA 31 - Select Queries from DVD Rental database

Mohith — Sat, 28 Mar 2026 19:05:21 +0000

SQL SELECT Practice Queries

1. Retrieve film titles and rental rates with aliases

select title as "movie title",rental_rates as "rate"from film;

2. List customer names and email with aliases

select first_name as "first name",last_name as "last name",email from customer;

3. Films sorted by rental rate desc, then title asc

select title, rental_rate from film order by title asc, rental_rate dsc;

4. Actor names sorted by last name then first name

select last_name, first_name from actor order by last_name asc, first_name asc;

5. Unique replacement costs

select distinct replacement_cost from film;

6. Film title and duration

select title,length as "duration(min)"from film;

7. Customer active status with alias

select first_name,last_name,active is "is active" from customer;

8. Film categories alphabetically

select name from category order by name;

9. Films sorted by length descending

select title, length from film order by length desc;

10. Actors sorted by first name descending

select first_name, last_name from actor order by first_name desc;

11. Unique ratings

select distinct rating from film;

12. Unique rental duration

select distinct rental_duration from film;

13. Unique customer id based on active status

select distinct customer_id, active from customer order by customer_id;

14. Earliest rental date for each customer

select customer_id, min(rental_date) as rental_date from rental group by customer_id order by customer_id;

15. list 10 shortest films

select title, length from film order by length asc limit 10;

16. Top 5 customers with highest id

select first_name, last_name from customer order by customer_id desc limit 5;

17. Unique store ids

select distinct store_id from inventory;

18. Unique replacement cost sorted

select distinct replacement_cost from film order by replacement_cost;

19. First rental date for each store

select i.store_id,min(r.rental_date) as rental_date from rental r join inventory i on r.inventory_id = i.inventory_id group by i.store_id order by i.store_id;

20. Unique ratings sorted

select distinct rating from filmorder by rating;

21. Films sorted by rating asc and length desc

select title, rating, length from film order by rating asc, length desc;

22. Actors sorted by last name asc, first name desc

select first_name, last_name from actor order by last_name asc, first_name desc;

23. Films by replacement cost asc and rental rate desc

select title, replacement_cost, rental_rate from film order by replacement_cost asc, rental_rate desc;

24. Customers sorted by last name asc and first name desc

select first_name, last_name from customer order by last_name asc, first_name desc;

25. Rentals sorted by customer and date

select * from rental order by customer_id asc, rental_date desc;

26. Films by rental duration and title

select title, rental_duration from film order by rental_duration asc, title desc;

CA 30 - Basic Select SQL Querie

Mohith — Sat, 28 Mar 2026 18:46:58 +0000

basic hackerank problems sql queries

When you're starting with SQL, the SELECT statement is the most important command. It allows you to retrieve data from database tables using different conditions.

FROM
WHERE
COUNT(column)
COUNT(DISTINCT column)
LEFT(column, n)

1. Query all columns for a city in CITY with the ID 1661

SELECT * FROM CITY WHERE ID = 1661;

2. Query all American cities with population larger than 100000

SELECT * FROM CITY WHERE COUNTRYCODE = 'USA' AND POPULATION > 100000;

3. Query all attributes of every Japanese city

SELECT * FROM CITY WHERE COUNTRYCODE = 'JPN';

4. Difference between total CITY entries and distinct CITY entries

SELECT COUNT(CITY) - COUNT(DISTINCT CITY) FROM STATION;

5. Query NAME of American cities with population larger than 120000

SELECT NAME FROM CITY WHERE COUNTRYCODE = 'USA' AND POPULATION > 120000;

6. Query names of all Japanese cities

SELECT NAME FROM CITY WHERE COUNTRYCODE = 'JPN';

7. List CITY names that do not start with vowels (no duplicates)

SELECT DISTINCT CITYFROM STATION WHERE LEFT(CITY,1) NOT IN
('A','E','I','O','U');

8. Query all columns from CITY table

SELECT * FROM CITY;

9. Query CITY and STATE from STATION table

SELECT CITY, STATE FROM STATION;

How a Request Travels from Client to Server

Mohith — Sat, 28 Mar 2026 18:35:02 +0000

my thought process for request travels from the client to server is

We use the internet every day — scrolling, clicking, searching — but we rarely think about what actually happens behind that one simple action. Let’s say you type google.com or click a button on a website. That small action silently starts a full journey across the internet.

It all begins with your device, also called the client. The moment you enter a URL, your system doesn’t immediately know where to go. Computers don’t understand domain names — they understand IP addresses. So your device reaches out to DNS (Domain Name System) to translate that human-readable name into an IP address. You can think of DNS like a contact list — it converts names into numbers.

Once the IP address is found, your browser prepares an HTTP request. This request includes things like the method (GET, POST), headers, and some metadata describing what you're asking for. Before sending it, the request goes through the TCP/IP protocol stack, where a connection is established using the TCP three-way handshake to make sure communication is reliable.

Now the interesting part — the request is broken into smaller pieces called packets. These packets travel across multiple networks, routers, and systems using IP routing. Each router along the way decides the best path for the packets, similar to how maps choose the fastest route.

these packets reach the server. The server reassembles them, understands the request, and processes it. This may involve fetching data from a database, running backend logic, or simply returning a static webpage.Once the processing is done, the server sends back an HTTP response — again in packets. These packets travel all the way back to your device, where they are reassembled, and your browser finally renders the content on your screen.

how DNS resolver is happening - CA27

Mohith — Sat, 28 Mar 2026 18:25:30 +0000

actual my thoght process for the how DNS resolver is happening Every time you type something like google.com in your browser, your device has one simple goal — find the IP address of that website so it can connect to the server. This whole process is called DNS resolution, and even though it sounds complicated, it actually happens in milliseconds behind the scenes.

It starts from your device (the client). Before asking anyone else, your system first checks locally. That means it looks into the browser cache, operating system cache, and sometimes even the hosts file to see if the IP address is already known. If it finds it, then it can directly use it and skip the rest. If not, it sends a request to a DNS resolver, which is usually provided by your ISP or a public DNS service.

Now the resolver does the main work. It doesn’t directly know the IP address, so it starts asking step by step. First, it contacts a root name server. The root server doesn’t give the IP, but it tells where to find the TLD server (like .com, .org, .net). Then the resolver asks the TLD server. The TLD server responds with the address of the authoritative DNS server for that domain. Finally, the resolver queries the authoritative server, and this server returns the actual IP address of the website.

Once the resolver gets the IP address, it sends it back to your device and also stores it in cache so next time it’s faster. Now your browser finally has the IP address. Using that, it creates a connection (TCP/IP) and sends an HTTP request to the server to get the website content.

IP address and Subnet - CA25

Mohith — Sat, 28 Mar 2026 18:14:43 +0000

what i have been understand throught this session
When you open a website, your computer communicates with another computer on the internet.
This communication happens using IP addresses and subnets.
what i have been learned:

What is an IP Address
Types of IP Address
What is Subnet
Why Subnet is used *Real-world example

as per mythought process What is an IP Address?

An IP address is a unique identifier assigned to each device on a network.the ip address will be divide into parts 8bits-8bits-8bits-8bits which is totally 32bits.actually every ip is will be in two different types of port which is network port and host port the first 24bits will be network port and last remaining is the host port the cidr will works thought the process of workflow
you can ask what is cidr calculator ??
which is used to set the count,first usable ip,netmask,cidr base ip,broadcast ip by using this which is used to be calculated

Example IP addresses

Just like our home address helps people find your house,
an IP address helps computers find each other on the internet.

192.168.1.1
8.8.8.8
172.16.0.1

There are some Types of IP Address

1. Public IP Address

Used on the internet and assigned by ISP(internet acces protocol)
Example:
8.8.8.8

2. Private IP Address

Used inside local networks (WiFi, office, home).
Example ranges:

192.168.x.x
10.x.x.x
172.16.x.x

What is Subnet?

A Subnet means dividing a large network into smaller networks.
Subnet = Sub Network
Subnet helps:

Reduce network traffic
Improve performance
Increase security
Better network

Example Without Subnet

All devices in one network:
192.168.1.1
192.168.1.2
192.168.1.3
192.168.1.254

This creates heavy traffic.

some Example With Subnet

Subnet 1
192.168.1.1 – 192.168.1.50
Subnet 2
192.168.1.51 – 192.168.1.100
Subnet 3
192.168.1.101 – 192.168.1.150
Now network is faster and organized.

What is Subnet Mask?

Subnet mask defines network and host portion.
Example:
IP Address: 192.168.1.10
Subnet Mask: 255.255.255.0
Network part → 192.168.1
Host part → 10

how in Real World works

Network → Building
Subnet → Floor
IP Address → Room number
Example:
Building A
Floor 1 → Subnet
Room 101 → IP Address

Conclusion

IP Address identifies devices
Subnet divides networks
Subnet improves performance and security
Subnet mask defines network range

CA 03 - Number Guessing Game

Mohith — Sun, 22 Mar 2026 18:58:55 +0000

From Number Guessing Game to System Design Concepts

this session, we started by building a simple Number Guessing Game, but the discussion slowly moved into system design concepts like locking, database design, randomness, and security. The idea was to not just build a game, but to understand how similar concepts apply in real-world systems.

Before this, we already discussed a ticket booking system, where multiple users try to book the same seat at the same time.

Ticket Booking System Problem

Consider two users trying to book the same seat.

User A selects seat 1
User B selects seat 1 at the same time

Both users see the seat as available and both attempt to book it.
This creates a race condition and leads to duplicate booking.

This happens because there is no locking mechanism.

Why Locking is Needed

To prevent this issue, we introduce locking.

When User A selects a seat:

The seat gets locked
User B cannot access it
User A proceeds to payment
If payment completes, seat becomes booked
If payment times out, lock is released

This ensures only one user can access the seat at a time and maintains data consistency.

Types of Locking

Two types of locking were discussed.

Optimistic Locking
Assumes conflicts are rare. Multiple users can read data, and conflict is checked only when updating.

Pessimistic Locking
Locks the resource immediately. Other users cannot access it. This is safer and commonly used in booking systems.

Database Tables for Ticket Booking

Two tables are required.

Movies table stores:

movie name
show time
release date

Seats table stores:

movie id
seat number
status

Seat status is "available" by default.

Before booking begins, movie and seat details are inserted into these tables.

Booking Flow with Concurrency

User selects seat
Seat gets temporarily locked
User proceeds to payment
Lock held for limited time (example: 7 minutes)
If payment success → seat booked
If timeout → lock released

Without locking, multiple users can book the same seat.

Isolation levels help but do not fully solve concurrency issues.

Row Level Locking Example

Seat 1 is available

User A selects seat 1
Seat 1 becomes locked

User B tries to select seat 1
User B is blocked

Only when lock is released, seat becomes available again.

This demonstrates row level locking.

Number Guessing Game Design

After discussing concurrency, we moved to building a Number Guessing Game.

Two players try to guess a secret number within a range.
The goal is to guess the number with minimum attempts.

Difficulty levels define:

range of numbers
number of attempts
score

Example:

Easy → 1 to 20
Medium → 1 to 50
Hard → 1 to 100

Leaderboard stores attempts and scores.

Game Flow

Start with greeting message
Show difficulty selection menu
User selects difficulty
Generate random number
User guesses number
System gives hint (higher / lower)
Track attempts
Store score in leaderboard

Random Number Generation

Computers do not generate truly random numbers.
They generate pseudo-random numbers using algorithms.

Random numbers depend on a seed value.
If the seed is same, the sequence will also be same.
Usually, system time is used as seed.

Different systems may produce different sequences.

So randomness is algorithm-based, not truly random.

Handling User Input

User input must be validated properly.

Difficulty input may come as string
Convert string to integer
Validate range
Handle invalid input

Functions return:

int
string
boolean

Proper type conversion avoids runtime errors.

Leaderboard Design

Leaderboard data stored in database.

It contains:

username
difficulty
attempts
score

Operations include:

inserting score
fetching leaderboard
sorting by attempts
filtering by difficulty

Efficient queries and indexing improve performance.

System Design Takeaways

Concurrency handling is important
Locking prevents race conditions
Row level locking improves safety
Timeout based locking avoids deadlocks
Leaderboard stored in database
Efficient queries reduce load
Indexing improves performance

These concepts apply to real systems like:

ticket booking
ride booking
hotel booking
food delivery

Security and Network

Communication happens over HTTPS.

Security includes:

TLS encryption
public/private key pairs
encrypted data transfer

This prevents middleman attacks and ensures secure communication.

This is important for:

payments
authentication
booking systems

Summary

In this session, we learned:

Concurrency issues in booking systems
Optimistic vs pessimistic locking
Database table design
Row level locking
Number guessing game design
Random number generation
Input validation and type casting
Leaderboard system design
Security basics using HTTPS

This session showed how even a simple Number Guessing Game can help understand real-world system design concepts.

Remove Duplicates from a Sorted Linked List –CA23

Mohith — Fri, 20 Mar 2026 18:12:14 +0000

My Thinking and Approach

Introduction

In this problem, I was given a sorted linked list and asked to remove duplicate elements.

Since the list is already sorted, duplicates will always appear next to each other. This made the problem easier to approach.

Problem Statement

Given a sorted linked list
Remove duplicate nodes
Return the updated list

My Initial Thought

Initially, I thought:

Store elements in a set
Rebuild the linked list

But this uses extra space, which is not required here.

Key Observation

Because the list is sorted:

Duplicate values are always adjacent
So I only need to compare current node with the next node

Optimized Approach

I decided to:

Traverse the list once
If current node value equals next node value:
- Skip the next node
Otherwise:
- Move forward

My Approach

Start with curr = head
Traverse while curr and curr.next are not null

Steps:

If curr.data == curr.next.data:

Remove duplicate by skipping node
curr.next = curr.next.next

Else:

Move to next node

Code (Java)

class Solution {
    Node removeDuplicates(Node head) {
        Node curr = head;

        while (curr != null && curr.next != null) {
            if (curr.data == curr.next.data) {
                curr.next = curr.next.next;
            } else {
                curr = curr.next;
            }
        }

        return head;
    }
}

Example Walkthrough

Example

Input:
2 → 2 → 4 → 5

Steps:

Compare 2 and 2 → remove duplicate
List becomes → 2 → 4 → 5

Output:
2 → 4 → 5

Complexity Analysis

Time Complexity: O(n)
Space Complexity: O(1)

Key Takeaways

Sorted property simplifies the problem
No need for extra space
Pointer manipulation is important in linked lists

Conclusion

This problem helped me understand how to efficiently handle duplicates in linked lists. It also reinforced the importance of using problem constraints (like sorted order) to simplify the solution.

Reverse a Linked List – CA22

Mohith — Fri, 20 Mar 2026 18:09:49 +0000

My Thinking and Approach

Introduction

In this problem, I was given the head of a singly linked list and asked to reverse it.

At first, I thought it might be tricky because linked lists don’t allow direct indexing like arrays. But once I understood how pointers work, the solution became clear.

Problem Statement

Given the head of a singly linked list
Reverse the list
Return the new head

My Initial Thought

Initially, I thought:

Store elements in an array
Reverse the array
Rebuild the linked list

But this uses extra space and is not efficient.

So I tried to solve it directly using pointers.

Optimized Approach (Iterative)

I realized that:

Each node points to the next node
To reverse, I need to change the direction of these pointers

My Approach

Use three pointers:
- prev → previous node
- curr → current node
- next → next node

Steps

Initialize:

prev = null
curr = head

Traverse the list:

Store next node → next = curr.next
Reverse pointer → curr.next = prev
Move prev forward
Move curr forward

At the end:

prev becomes the new head

Code (Java)

class Solution {
    Node reverseList(Node head) {
        Node prev = null;
        Node curr = head;

        while (curr != null) {
            Node next = curr.next;
            curr.next = prev;
            prev = curr;
            curr = next;
        }

        return prev;
    }
}

Example Walkthrough

Example 1

Input:
1 → 2 → 3 → 4

Steps:

Reverse 1 → null
Reverse 2 → 1
Reverse 3 → 2
Reverse 4 → 3

Output:
4 → 3 → 2 → 1

Example 2

Input:
2 → 7 → 10 → 9 → 8

Output:
8 → 9 → 10 → 7 → 2

Complexity Analysis

Time Complexity: O(n)
Space Complexity: O(1)

Key Takeaways

Linked lists require pointer manipulation
Always store next node before changing links
Iterative approach is simple and efficient

Conclusion

This problem helped me understand how linked lists work internally. It improved my confidence in handling pointer-based problems and showed how simple logic can reverse an entire data structure efficiently.

Majority Element – CA21

Mohith — Fri, 20 Mar 2026 18:04:51 +0000

My Thinking and Approach

Introduction

In this problem, I was given an array and asked to find the majority element.

A majority element is the one that appears more than n/2 times in the array. If no such element exists, we need to return -1.

At first, it looked like a simple counting problem, but I learned that there is a more optimized way to solve it.

Problem Statement

Given an array arr[]
Find the element that appears more than n/2 times
If no such element exists, return -1

My Initial Approach

Initially, I thought of using a frequency count:

Use a HashMap
Count occurrences of each element
Return the element with count > n/2

Drawback

Time Complexity: O(n)
Space Complexity: O(n)

Although this works, it is not the most optimal solution.

Optimized Approach (Boyer-Moore Voting Algorithm)

To improve efficiency, I used the Boyer-Moore Voting Algorithm, which works in:

Time: O(n)
Space: O(1)

My Approach

Step 1: Find Candidate

Maintain two variables:
- candidate
- count
Traverse the array:
- If count == 0, assign current element as candidate
- If current element equals candidate → increment count
- Else → decrement count

Step 2: Verify Candidate

Count how many times the candidate appears
If count > n/2 → return candidate
Else → return -1

Code (Java)

class Solution {
    int majorityElement(int arr[]) {
        int candidate = 0, count = 0;

        for (int num : arr) {
            if (count == 0) {
                candidate = num;
            }

            if (num == candidate) {
                count++;
            } else {
                count--;
            }
        }

        count = 0;
        for (int num : arr) {
            if (num == candidate) {
                count++;
            }
        }

        return (count > arr.length / 2) ? candidate : -1;
    }
}

Example Walkthrough

Example 1

Input:
[1, 1, 2, 1, 3, 5, 1]

Candidate becomes 1
It appears more than n/2 times

Output:
1

Example 2

Input:
[2, 13]

No majority element exists

Output:
-1

Complexity Analysis

Time Complexity: O(n)
Space Complexity: O(1)

Key Takeaways

Boyer-Moore algorithm is very efficient
Always verify the candidate
Helps reduce space complexity

Conclusion

This problem helped me understand how to optimize a simple counting problem into a more efficient solution using the Boyer-Moore Voting Algorithm. It is a very useful concept for coding interviews and competitive programming.