7-Modern-Languages-in-7-Weeks---Systems--Security---Algorithms-Track/week 1/day 3

📘 Week 1 · Day 3 — SQL Exercises

This document describes all exercises for Week 1 Day 3, focused on SQL conditionals, filtering, and algorithmic thinking using PostgreSQL.

The goal of today’s exercises is to translate the control-flow logic you used in C (Day 1) and Python (Day 2) into declarative SQL queries, while keeping the same performance and security mindset.

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🎯 Learning Objectives

By completing today’s exercises, you practice:

• Replacing loops with SQL filtering (WHERE)
• Using conditions to select and classify data
• Understanding how databases execute algorithms internally
• Reasoning about runtime complexity in a data-driven context
• Applying validation logic at the database layer (security best practice)

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🛠 Database Setup (Reference)

All exercises assume the following PostgreSQL table:

inti_db.sql

CREATE TABLE users (
    id SERIAL PRIMARY KEY,
    username TEXT
);

Sample data:

INSERT INTO users (username) VALUES
('admin'),
('root1'),
('John_Doe'),
('Alice'),
('Bob42'),
('charlie'),
('eve99'),
('Mallory');

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🧪 Exercises

Exercise 1 — Length Filtering

Task: Select all usernames that are longer than 5 characters.

Concepts practiced:

• WHERE clause
• String length evaluation

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Exercise 2 — Letters-Only Usernames

Task: Select usernames that:

• Contain only letters (A–Z, a–z)
• Contain no digits
• Contain no underscores or symbols

Concepts practiced:

• Regular expressions in PostgreSQL
• Character validation at the database level
• Replacing character-by-character loops with pattern matching

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Exercise 3 — Accepted vs Refused Classification

Task: Return a result set containing:

• username

• status column with values:

  • Accepted
  • Refused

Rules:

• Username length ≤ 20
• Username contains letters only

Concepts practiced:

• CASE WHEN expressions
• Conditional logic inside SQL queries
• Translating if / else into declarative form

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Exercise 4 — Count Valid Usernames

Task: Return only the number of usernames that are valid according to the same rules:

• Length ≤ 20
• Letters only

Concepts practiced:

• Aggregate functions (COUNT)
• Combining filtering and aggregation
• Thinking about algorithm cost without explicit loops

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Exercise 5 — Algorithm Analysis (Written)

Task: Answer the following questions:

1. If the users table doubles in size, what happens to the execution time?

2. Write the runtime formula using:

   • n = number of rows
   • m = average username length

Expected reasoning:

• SQL engines still scan rows internally
• Regex checks still evaluate characters

Expected formula:

T(n, m) = n × m

Explain this in plain language, from a sysadmin or security perspective.

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🔐 Security Perspective

These exercises demonstrate why validating data in SQL is powerful:

• Reduces reliance on frontend-only checks
• Prevents bad data from entering critical systems
• Improves consistency across applications
• Aligns with real-world authentication, logging, and SIEM pipelines

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✅ Completion Criteria

Day 3 is considered complete when:

• All four SQL queries execute correctly
• The algorithm explanation clearly explains scaling behavior
• The student can explain how SQL replaces procedural loops

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Next Step: Week 1 Day 4 — deeper control flow and scripting (Bash or Rust, depending on track).