Day 80 of Learning MERN Stack

Hello Dev Community! 👋

It is officially Day 80 of my 100-day full-stack and database engineering streak! 🎯 I have officially crossed 80% of this intense learning run. Yesterday, I focused on structural table checks and aggregation functions. Today, I dove deep into the logical core of database filtering by mastering: SQL Logical Operators (AND, OR, NOT, IN, BETWEEN, LIKE)!

When users search or apply multiple filters on a frontend application—like sorting clothes on an e-commerce platform or picking movie genres on a media streaming service—the backend relies entirely on these operators to scan massive tabular datasets efficiently.

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🧠 Deep Dive: The Logic Gates of SQL

Today, I built and verified complex query matrices to understand exactly how the SQL engine processes multi-conditional statements:

1. Intersecting & Alternating Conditions (AND, OR, NOT)

• AND: Strict matching. Evaluates to true only if all wrapped conditions pass.
• OR: Flexible matching. Returns records if any single independent condition is met.
• NOT: Negation guard. Reverses the logic state, pulling rows that explicitly do not match the given parameter.

2. Set Matching & Range Boundaries (IN, BETWEEN)

• IN: Replaces bulky, repetitive OR chains. It lets me pass an array group (e.g., WHERE city IN ('Lahore', 'Karachi')) to scan categorical subsets instantly.
• BETWEEN: Streamlines numerical and date range boundaries. Instead of writing >= 30 AND <= 50, using BETWEEN 30 AND 50 makes the query incredibly clean and readable.

3. Advanced Pattern Matching (LIKE & Wildcards)

The absolute game-changer for search functionalities! By pairing LIKE with wildcards (% and _), I can run fuzzy text pattern matching:

• LIKE 'A%' — Grabs any string records starting with the letter "A".
• LIKE '%m' — Targets strings ending with the letter "m".
• LIKE '%ali%' — Scans for any strings containing the substring "ali" anywhere inside the column value.

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🛠️ Operational Look at the Day 80 Script Architecture

Here is how I synthesized these logical blocks into real-world relational operations:

sql
-- Combining Range parameters with Category sets
SELECT name, age, city 
FROM student 
WHERE (age BETWEEN 20 AND 35) AND city IN ('Karachi', 'Lahore', 'Islamabad');

-- Running negation and search wildcards simultaneously
SELECT * 
FROM student 
WHERE city NOT IN ('Faisalabad') AND name LIKE 'A%';