DEV Community: Yogaraj

Linux Learning Journey – Week 2 Progress

Yogaraj — Thu, 18 Sep 2025 17:12:05 +0000

After covering the basics in Week 1, this week I moved on to some very practical Linux commands. These helped me understand how processes run, how memory is used, and how to manage files more effectively. Here’s what I learned:

Switching Users

su - : Allows switching between different users in the system. Very useful when you need root access or want to work under a specific account.

Process Management

top : Shows currently running processes, just like Task Manager in Windows. Great for checking which tasks are consuming resources.

kill [PID] : Ends a process using its process ID. By default, it asks permission from the parent process.

kill -9 [PID] : Force kills a process immediately (like force quit).

pkill [process_name] : Kills a process using its name instead of the PID.

Memory and Disk Usage

df : Displays details of hard disk partitions (similar to drives in Windows).

df -h : Same as above, but in human‑readable format.

free : Shows memory usage.

free -G : Memory details in GB.

free -M : Memory details in MB.

Swap : Acts as temporary memory when RAM is full. Part of the hard disk is used as memory, and we can even add extra swap space if needed.

File Searching and Content

grep : Works like Ctrl + F in Windows. Used to search for text inside files.

tac [filename] : Displays file content in reverse order (opposite of cat).

File and Directory Operations

pwd : Prints the present working directory.

cd / : Takes you to the root directory of the Linux system.

ls : Lists all files and folders in the current directory.

ls -ltr : Lists in long format, shows file sizes, timestamps, and arranges in reverse order.

rm -f [file] : Force delete a file.

rm -vf [file] : Deletes with detailed output.

echo "text" : Prints whatever you type (useful for testing or adding text to files).

Extra Tip

To check when the server was installed, you can explore system logs or use commands in / to trace system details.

My Reflection

Week 2 was all about getting comfortable with managing processes, checking system resources, and learning how to navigate efficiently. The commands top, kill, and grep especially stood out because they are powerful for troubleshooting and searching.

I can already feel myself moving from just “using Linux” to actually controlling it. Excited to keep building on this in Week 3

I’m here to learn out loud.

You’ll find:

Raw, honest notes from my daily learning
Simple examples I’ve tried on my own
Weekly summaries of what clicked (and what didn’t)
Thanks for stopping by — and if you're also on a similar path, let’s connect and grow together! 🌱

Follow me for weekly updates and reflections from my cloud learning journey.

aws #cloudcomputing #sql #linux
💭 Got suggestions, feedback, or just want to say hi?

📩 Reach me at: yogarajprof@gmail.com

Learning Linux Step by Step – Week 1 Progress

Yogaraj — Fri, 05 Sep 2025 17:14:21 +0000

🖥️ Linux Learning Journey – Week 1

I’ve officially started my Linux learning journey! To get hands-on practice, I installed Red Hat Enterprise Linux (RHEL) on VMware Workstation. Running it inside a virtual machine makes it safe to explore, since even if I mess something up, my main system stays unaffected.

Here’s everything I covered in my first week:

🔹 Installation & Setup
I learned the basics of Linux distributions (distros) and why they exist. Some are community-based (like Ubuntu, Debian), while others like RHEL are enterprise-focused. Setting up RHEL inside VMware gave me a real server-like environment to practice on.

🔹 Linux File System
Unlike Windows, where drives are labeled (C:, D:, etc.), Linux has a single root directory (/), and everything starts from there. I explored some important folders:

/home → stores user files

/etc → contains system configuration files

/var → keeps logs and variable data

/bin → essential system commands and binaries
It felt structured and logical once I understood the hierarchy.

🔹 Basic Navigation Commands
I practiced commands to move around and explore the system:

pwd → shows current directory

ls → lists files and directories

cd → change directory

clear → clears the terminal
At first, it felt strange not having a GUI to click around, but slowly I got comfortable navigating purely with commands.

🔹 File & Directory Management
Creating and managing files/directories was my next step:

mkdir newfolder → creates a directory

rmdir oldfolder → removes an empty directory

touch notes.txt → creates an empty file

cp file1 file2 → copies files

mv file1 file2 → moves or renames files

rm file.txt → deletes a file

It’s simple but powerful. With just these few commands, I could organize files completely from the terminal.

🔹 Viewing Files
Linux provides different ways to check file contents:

cat for quick display

less and more for scrolling through long files

head and tail for previewing the beginning or end of a file
This was really useful when I explored system files in /etc and /proc.

🔹 User Management Basics
Linux is a multi-user system, so learning user management was important:

Checked the current user with whoami and id

Switched between users with su and ran admin tasks with sudo

Created new users using useradd newuser and set passwords with passwd

Removed accounts with userdel

This gave me an idea of how Linux handles different users and permissions, something very important in servers.

✨ Takeaway:
Week 1 has been about building a foundation. From installing RHEL inside VMware to creating files, directories, and even new users, I now feel more comfortable with the Linux command line. It was a bit challenging in the beginning, but the more I practice, the more natural it feels.

Next, I’ll move on to permissions, wildcards, and process management in Week 2. Looking forward to diving deeper 🔥

Linux #RHEL #VMware #LearningJourney #Tech

🚀 Building My First SQL Project: Employee Attendance & Leave Management System

Yogaraj — Mon, 18 Aug 2025 16:08:40 +0000

Over the past few weeks, I’ve been learning SQL and wanted to put that knowledge into practice by building a small project. To keep it simple but realistic, I decided to create an Employee Attendance & Leave Management System.

This project helped me understand how to design tables, insert real-looking values, and run queries that actually make sense in a workplace scenario

📌 Why This Project?

Almost every organization needs a way to track employees, their departments, attendance, and leaves. Instead of building a complex system, I focused on a simple yet practical database that covers:

📂 Project Setup

Database Name: EMP_DB

Number of Tables: 6 (Employees, Departments, Attendance, Leave, Projects, Salaries)

Tools Used: MySQL Workbench (you can use any SQL environment)
🛠 Tables I Created

Here’s a quick overview of the tables:

Employees → stores employee details like ID, name, department.

Departments → keeps track of all departments.

Attendance → logs employee check-ins/check-outs.

Leave → records leave applications and approvals.

Projects → assigns employees to projects.

Salaries → salary details per employee.

💾 Example Queries

Some queries I tried running:

Get employees with pending leaves.

Find the department with the most employees.

Check attendance percentage for each employee.

Show employees assigned to multiple projects.

These queries gave me confidence that my tables were connected properly with Primary Keys and Foreign Keys.

🚀 What I Learned

How to design a database from scratch.

The importance of relationships between tables.

Writing queries that solve real use cases.

Using GitHub to host my project files.

📌 Project Repo

I’ve uploaded the SQL script and README file here:
👉 https://github.com/yogaraj638/EMP_DB_Project

🔮 Next Steps

This was just a beginner project, but I plan to:

Add triggers/stored procedures.

Work with larger sample data.

Connect this database with a simple frontend (maybe in the future).

aws #cloudcomputing #sql #linux
💭 Got suggestions, feedback, or just want to say hi?

📩 Reach me at: yogarajprof@gmail.com

📊 SQL Learning Journey — Week 4 Recap

Yogaraj — Wed, 06 Aug 2025 18:01:55 +0000

🧠 Key Concepts Explored

🧪 Subqueries Simplified

Subqueries are powerful tools in SQL. This week, I learned that:

Subquery is independent — it returns a value.
Outer query uses that value, applying it across the main table.

💡 Golden Rule for Subqueries:

Don't try to understand the whole table first. Instead, zoom in:

Who should be in the result?
What is the condition to qualify?
What’s the minimal data I need?

🎯 3-Step SQL Problem Solving Template:

Step	Question	Example Thought
1	Who is the output about?	Authors
2	What must they have done?	Viewed their own article
3	What’s the SQL logic?	`author_id = viewer_id` → `SELECT DISTINCT author_id`

🧰 Handy Functions

Function	Purpose	Syntax Example	Result
`DATE_ADD()`	Adds interval to date	`DATE_ADD('2025-08-06', INTERVAL 1 DAY)`	`2025-08-07`
`DATE_SUB()`	Subtracts interval from date	`DATE_SUB('2025-08-06', INTERVAL 1 DAY)`	`2025-08-05`

🧾 ENUM Usage

ENUM is a data type used to restrict column values to a predefined set.

Example:

status ENUM('Pending', 'Shipped', 'Delivered', 'Cancelled')

Only those 4 values are allowed.
You can include numbers, but they’re stored as strings, not integers.

✅ LeetCode Practice — 10 Problems Solved 🎉

This week, I tackled and completed 10 beginner-friendly SQL problems:

Problem No.	Title	Difficulty
1757	Recyclable and Low Fat Products	Easy
584	Find Customer Referee	Easy
595	Big Countries	Easy
1148	Article Views I	Easy
1683	Invalid Tweets	Easy
1378	Replace Employee ID With The Unique Identifier	Easy
1068	Product Sales Analysis I	Easy
1581	Customer Who Visited but Did Not Make Any Transactions	Easy
197	Rising Temperature	Easy
1661	Average Time of Process per Machine	Easy
577	Employee Bonus	Easy

🌱 What’s Next?

Dive deeper into Window Functions
Explore Advanced Subqueries and Nested Joins
Build a mini-project using real-world datasets

Thanks for reading! Feel free to connect and share your learning journey too. 💬

#SQL #100DaysOfSQL #LearningJourney #Subqueries #LeetCode

5 SQL Join Mistakes I Made as a Learner (and How I Fixed Them)"

Yogaraj — Sun, 27 Jul 2025 11:47:57 +0000

When I first started learning SQL, joins felt like magic—until they didn’t. Joins are incredibly powerful, but they can also be tricky when you're new. I made a lot of mistakes along the way, and in this post, I’ll share the top 5 that tripped me up (with real examples) and how I fixed them. Hopefully, they’ll save you some time and confusion!

1. Trying FULL OUTER JOIN Directly in MySQL

Mistake:

SELECT * FROM food_sales
FULL OUTER JOIN data_sales ON food_sales.ID = data_sales.ID;

I expected this to return all matches plus unmatched rows from both tables. But MySQL threw an error.

Fix: MySQL doesn't support FULL OUTER JOIN directly. You need to simulate it using UNION of a LEFT JOIN and RIGHT JOIN.

Corrected Code:

SELECT fs.ID, fs.City, ds.Product
FROM food_sales fs
LEFT JOIN data_sales ds ON fs.ID = ds.ID

UNION

SELECT ds.ID, fs.City, ds.Product
FROM food_sales fs
RIGHT JOIN data_sales ds ON fs.ID = ds.ID;

2. Using WHERE with Aliases Before Declaring Them

Mistake:

SELECT FS.City, FS.Category, (FS.Qty * FS.UnitPrice) AS TotalSales
FROM food_sales FS
WHERE TotalSales > 50;

I thought I could use the alias TotalSales in the WHERE clause.

Fix: SQL doesn't recognize aliases in WHERE—they're created during the SELECT phase, which runs after WHERE.

Corrected Code:

SELECT FS.City, FS.Category, (FS.Qty * FS.UnitPrice) AS TotalSales
FROM food_sales FS
WHERE (FS.Qty * FS.UnitPrice) > 50;

Or, use a subquery if you want cleaner filtering:

SELECT * FROM (
  SELECT FS.City, FS.Category, (FS.Qty * FS.UnitPrice) AS TotalSales
  FROM food_sales FS
) AS Sub
WHERE TotalSales > 50;

3. Confusion Between ON and WHERE Clauses

Mistake:

SELECT *
FROM food_sales FS, data_sales DS
WHERE FS.ID = DS.ID;

This technically works (old-style join), but it’s messy and confusing.

Fix: Always use JOIN ... ON for better readability and modern SQL syntax.

Corrected Code:

SELECT *
FROM food_sales FS
INNER JOIN data_sales DS ON FS.ID = DS.ID;

4. Overwriting Columns with the Same Alias

Mistake:

SELECT ds.product AS Product, IFNULL(ds.product, 'No Product') AS Product
FROM data_sales ds;

I thought both lines would be fine—but I reused the alias Product, which caused confusion.

Fix: Always use unique aliases in your SELECT clause.

Corrected Code:

SELECT ds.product AS ActualProduct, IFNULL(ds.product, 'No Product') AS CleanedProduct
FROM data_sales ds;

5. Assuming JOINs Automatically Drop NULLs

Mistake: I thought an INNER JOIN would always remove NULL values from all columns.

But when joining on unrelated or mismatched columns, NULLs may still show up in non-joined fields.

Fix: Always check your join condition and consider using COALESCE() or IS NULL to manage missing data explicitly.

Example:

SELECT fs.City, COALESCE(ds.Product, 'Unknown') AS Product
FROM food_sales fs
LEFT JOIN data_sales ds ON fs.ID = ds.ID;

Final Thoughts:

SQL joins are powerful tools, but they require precision and understanding. Each mistake I made taught me something valuable, and I hope by sharing these, your SQL journey becomes a little smoother. Let me know in the comments which one tripped you up—or if you have another SQL lesson to share!

Happy Querying! 😊

💭 Got suggestions, feedback, or just want to say hi?

📩 Reach me at: yogarajprof@gmail.com

"Week 2 Update: Starting SQL Basics Alongside My AWS Learning"

Yogaraj — Sun, 13 Jul 2025 10:36:18 +0000

Hey everyone! 👋

Checking in with my Week 2 learning update — shifting gears a bit alongside AWS to start exploring SQL fundamentals. Here’s what I covered this week using MySQL for hands-on practice:

🚀 What I Learned This Week:
🔹 Core Concepts:

Data Types: Qualitative vs. Quantitative

DBMS vs. RDBMS: Understanding how SQL talks to databases

Local Server Setup & MySQL Installation

🔹 Table Basics:

Creating Tables

SQL Data Types: NUMBER, TEXT, DATE

CHAR vs. VARCHAR

🔹 Table Constraints:

PRIMARY KEY, FOREIGN KEY, UNIQUE, NOT NULL, CHECK

DEFAULT, AUTO_INCREMENT

🔹 Operators & Commands:

Comparison + Logical Operators (AND, OR, NOT)

SQL Command Types: DDL, DML, DQL, TCL, DCL

GROUP BY + HAVING — filtering grouped data

✍️ Why SQL?
Since many cloud roles involve working with databases, I wanted to build up SQL fundamentals alongside AWS.

✅ Next Up:
SQL JOINS

Subqueries

Real-world practice scenarios

That’s my SQL progress so far as part of my AWS learning journey. Next, I’ll dive deeper into JOINS, subqueries, and real-time SQL scenarios.

Thanks for stopping by — and if you're also on a similar path, let’s connect and grow together! 🌱

Follow me for weekly updates and reflections from my cloud learning journey.

aws #cloudcomputing #sql #linux
💭 Got suggestions, feedback, or just want to say hi?

📩 Reach me at: yogarajprof@gmail.com

"Kicking Off My Cloud Journey: Learning AWS and Beyond 🚀"

Yogaraj — Tue, 24 Jun 2025 17:50:44 +0000

Hi everyone! 👋

I'm excited to share that I'm starting my cloud journey — diving into AWS and a range of related technologies. This marks the beginning of a consistent effort to build a solid foundation for a career in cloud computing.

Rather than listing everything I’ll be learning, I’ll use this blog to log my learnings, experiences, struggles, and small wins along the way.

🧠 Why This Blog?

I’m writing to:

Keep myself accountable and consistent
Share beginner-friendly insights and resources
Connect with others learning cloud tech
Build a learning portfolio that reflects real progress

✨ What You Can Expect

I’m here to learn out loud.

You’ll find:

Raw, honest notes from my daily learning
Simple examples I’ve tried on my own
Weekly summaries of what clicked (and what didn’t)

Thanks for stopping by — and if you're also on a similar path, let’s connect and grow together! 🌱

Follow me for weekly updates and reflections from my cloud learning journey.

aws #cloudcomputing #sql #linux

💭 Got suggestions, feedback, or just want to say hi?

📩 Reach me at: yogarajprof@gmail.com