SQL Exercises

∙ Topic

SQL Exercises

SQL Exercises help you improve your practical database skills through real-world problems involving SELECT queries, joins, aggregation, filtering, and optimization. These exercises are designed for beginners to advanced learners.

📝Syntax

-- Basic Exercise Structure

SELECT column_name
FROM table_name
WHERE condition;

sql-exercises.sql

📝 Edit Code

-- =========================
-- PRACTICE DATABASE
-- =========================

CREATE TABLE employees (
    emp_id BIGINT PRIMARY KEY AUTO_INCREMENT,
    name VARCHAR(150),
    department VARCHAR(100),
    salary DECIMAL(10,2)
);

CREATE TABLE orders (
    order_id BIGINT PRIMARY KEY AUTO_INCREMENT,
    emp_id BIGINT,
    amount DECIMAL(10,2),
    created_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
    FOREIGN KEY (emp_id) REFERENCES employees(emp_id)
);

CREATE TABLE products (
    product_id BIGINT PRIMARY KEY AUTO_INCREMENT,
    name VARCHAR(150),
    price DECIMAL(10,2)
);

-- =========================
-- EXERCISES (BEGINNER)
-- =========================

-- 1. Select all employees
SELECT * FROM employees;

-- 2. Find employees with salary > 50000
SELECT * FROM employees
WHERE salary > 50000;

-- 3. Get employees from IT department
SELECT * FROM employees
WHERE department = 'IT';

-- 4. Count total employees
SELECT COUNT(*) AS total_employees FROM employees;

-- =========================
-- EXERCISES (INTERMEDIATE)
-- =========================

-- 5. Average salary per department
SELECT department, AVG(salary) AS avg_salary
FROM employees
GROUP BY department;

-- 6. Total order amount per employee
SELECT emp_id, SUM(amount) AS total_amount
FROM orders
GROUP BY emp_id;

-- 7. Employees with no orders
SELECT e.*
FROM employees e
LEFT JOIN orders o ON e.emp_id = o.emp_id
WHERE o.order_id IS NULL;

-- =========================
-- EXERCISES (ADVANCED)
-- =========================

-- 8. Top 3 highest paid employees
SELECT * FROM employees
ORDER BY salary DESC
LIMIT 3;

-- 9. Second highest salary
SELECT MAX(salary) AS second_highest
FROM employees
WHERE salary < (SELECT MAX(salary) FROM employees);

-- 10. Department with highest average salary
SELECT department, AVG(salary) AS avg_salary
FROM employees
GROUP BY department
ORDER BY avg_salary DESC
LIMIT 1;

-- =========================
-- REAL-WORLD EXERCISES
-- =========================

-- 11. Monthly revenue
SELECT DATE(created_at) AS date, SUM(amount) AS revenue
FROM orders
GROUP BY DATE(created_at);

-- 12. Employee order count
SELECT emp_id, COUNT(order_id) AS total_orders
FROM orders
GROUP BY emp_id;

👁 Preview

💡 This preview does not execute SQL; it’s for reading/editing the query.

💡Beginner Exercises

1Basic SELECT queries.
2Filtering with WHERE.
3COUNT and simple aggregations.
4Basic sorting.

💡Intermediate Exercises

1GROUP BY queries.
2JOIN operations.
3Aggregation functions.
4NULL handling.

💡Advanced Exercises

1Subqueries.
2Ranking queries.
3Top-N problems.
4Performance optimization.

💡Real-World Exercises

1Revenue reports.
2Employee analytics.
3Order tracking.
4Business dashboards.

💡Interview Focus

1Second highest salary.
2Duplicate records.
3Top customers.
4Join-based problems.
5Scenario-based queries.

💡Real-world use cases

1Used in coding interviews.
2Used in SQL practice platforms.
3Used for backend development training.
4Used in data analytics tasks.
5Used in certification preparation.
6SaaS products use SQL Exercises in services, dashboards, background jobs, and API workflows.
7ERP and banking systems apply SQL Exercises with validation, logging, review, and rollback plans.
8E-commerce and healthcare platforms use SQL Exercises carefully because reliability and data correctness matter.

💡Internal working

1A Sql program first evaluates the surrounding context, then applies the SQL Exercises rules to the current data.
2The important mental model is input, transformation, result, and failure path.
3In production, the same flow usually sits inside a larger layer such as a controller, service, repository, job, or UI component.

💡Performance considerations

1Choose the simplest implementation first, then measure real workloads.
2Watch for repeated work inside loops, unnecessary allocations, and slow I/O in hot paths.
3Prefer clear data structures and stable APIs before micro-optimizing syntax.

💡Security considerations

1Treat external input as untrusted until it is validated.
2Avoid hardcoded secrets and never print sensitive values in examples or logs.
3Use established libraries for authentication, encryption, parsing, and database access.

💡Common mistakes

1Skipping GROUP BY understanding.
2Misusing subqueries.
3Forgetting JOIN conditions.
4Using SELECT * unnecessarily.
5Not practicing real datasets.
6Skipping the small working example before adding framework code.
7Ignoring null, empty, duplicate, and boundary inputs.
8Mixing business logic, input handling, and output formatting in one place.
9Using broad error handling that hides the real failure.
10Forgetting to test the behavior after refactoring.

💡Professional best practices

1Practice daily SQL exercises.
2Solve step-by-step problems.
3Understand query execution flow.
4Use joins properly.
5Practice real-world scenarios.
6Start with clear requirements and one minimal working example.
7Use meaningful names that explain business intent.
8Keep examples small enough to debug line by line.
9Validate input at every trust boundary.
10Handle errors explicitly and preserve useful context.
11Prefer simple control flow over deeply nested logic.
12Separate domain logic from I/O and framework code.
13Write tests for normal, boundary, and failure cases.
14Review security assumptions before production use.
15Measure performance before optimizing.
16Document non-obvious decisions close to the code or in project notes.
17Use official documentation when behavior is version-specific.
18Keep dependencies current and remove unused code.
19Avoid hardcoded secrets, credentials, and environment-specific paths.
20Log operational events without exposing sensitive data.

💡Coding exercises

1Beginner: rewrite the example with different names and values.
2Intermediate: add validation and handle one expected failure case.
3Advanced: place SQL Exercises inside a small service-style design with tests.

💡Mini project

1Build a small Sql console feature that demonstrates SQL Exercises.
2Accept input, process it with the concept, print a clear result, and handle invalid input.
3Add a README note explaining the design choice and two edge cases you tested.

💡Troubleshooting

1If the program does not compile, check spelling, imports, braces, and file/class names first.
2If output is unexpected, print intermediate values and verify each branch of the logic.
3If the design feels complex, reduce it to the smallest working example and add pieces back one at a time.

💡Next steps

1Practice SQL Exercises with a second example from a business domain such as inventory, payroll, banking, or e-commerce.
2Review related Sql topics that cover data flow, error handling, testing, and clean design.
3Compare your solution with official documentation and simplify anything you cannot explain clearly.

🏢Real-world

1Used in coding interviews.
2Used in SQL practice platforms.
3Used for backend development training.
4Used in data analytics tasks.
5Used in certification preparation.
6SaaS products use SQL Exercises in services, dashboards, background jobs, and API workflows.
7ERP and banking systems apply SQL Exercises with validation, logging, review, and rollback plans.
8E-commerce and healthcare platforms use SQL Exercises carefully because reliability and data correctness matter.

⚠Common Mistakes

1Skipping GROUP BY understanding.
2Misusing subqueries.
3Forgetting JOIN conditions.
4Using SELECT * unnecessarily.
5Not practicing real datasets.
6Skipping the small working example before adding framework code.
7Ignoring null, empty, duplicate, and boundary inputs.
8Mixing business logic, input handling, and output formatting in one place.
9Using broad error handling that hides the real failure.
10Forgetting to test the behavior after refactoring.
11Adding clever code that future maintainers will struggle to read.
12Not checking performance on realistic input sizes.

✅Best Practices

1Practice daily SQL exercises.
2Solve step-by-step problems.
3Understand query execution flow.
4Use joins properly.
5Practice real-world scenarios.
6Start with clear requirements and one minimal working example.
7Use meaningful names that explain business intent.
8Keep examples small enough to debug line by line.
9Validate input at every trust boundary.
10Handle errors explicitly and preserve useful context.
11Prefer simple control flow over deeply nested logic.
12Separate domain logic from I/O and framework code.
13Write tests for normal, boundary, and failure cases.
14Review security assumptions before production use.
15Measure performance before optimizing.
16Document non-obvious decisions close to the code or in project notes.
17Use official documentation when behavior is version-specific.
18Keep dependencies current and remove unused code.
19Avoid hardcoded secrets, credentials, and environment-specific paths.
20Log operational events without exposing sensitive data.
21Design examples so learners can safely modify and rerun them.
22Prefer maintainability over short-term cleverness.

✅Quick Summary

SQL exercises improve practical skills.
Cover beginner to advanced levels.
Important for interviews and jobs.
Focus on real-world scenarios.
Essential for backend developers.

🎯Interview Questions

Q1. Why are SQL exercises important?

Answer: They improve practical query writing skills and interview readiness.

Q2. What is the best way to learn SQL?

Answer: Practice exercises daily with real-world scenarios.

Q3. Which topic is most important in SQL?

Answer: Joins, aggregation, and subqueries.

Q4. How to improve SQL skills quickly?

Answer: Solve daily exercises and build projects.

Q5. Are exercises enough for interviews?

Answer: No, you should also understand system design and optimization.

Q6. What is SQL Exercises?

Answer: SQL Exercises is a Sql concept used for database-related work. A strong answer explains its purpose, basic behavior, and one realistic use case.

Q7. When should you use SQL Exercises?

Answer: Use it when it makes the solution clearer, safer, or easier to maintain than a simpler alternative.

Q8. What mistakes should be avoided with SQL Exercises?

Answer: Querying without indexes or filters. Building commands with untrusted string input.

Q9. How do you debug problems with SQL Exercises?

Answer: Reduce the code to a minimal example, inspect inputs and outputs, then add logging or tests around the failing path.

Q10. How does SQL Exercises affect maintainability?

Answer: It improves maintainability when responsibilities are clear, names are meaningful, and edge cases are tested.

Q11. How would you use SQL Exercises in an enterprise project?

Answer: Place it behind a clear service, validate inputs, handle errors, log useful context, and cover the behavior with tests.

Q12. What performance concern should you check with SQL Exercises?

Answer: Measure realistic data sizes and look for repeated work, blocking I/O, excessive allocation, or unnecessary framework overhead.

Q13. What security concern should you check with SQL Exercises?

Answer: Validate untrusted input, avoid leaking sensitive data, and use proven libraries for security-sensitive work.

Q14. How do you explain SQL Exercises to a beginner?

Answer: Start with the problem it solves, show the smallest working example, then explain each line and one common mistake.

Q15. What should you test for SQL Exercises?

Answer: Test a normal case, an empty or invalid case, a boundary case, and one expected failure path.

Q16. How do you know if SQL Exercises is the wrong choice?

Answer: It is probably wrong if it adds complexity without improving clarity, safety, reuse, or performance.

Q17. How does SQL Exercises connect to clean code?

Answer: Clean code uses the concept with clear names, small scopes, predictable behavior, and minimal hidden side effects.

Q18. What documentation is useful for SQL Exercises?

Answer: Document assumptions, edge cases, version-specific behavior, and any production decision that is not obvious from the code.

Q19. How should code using SQL Exercises be reviewed?

Answer: Review correctness first, then readability, failure handling, security boundaries, performance, and tests.

Q20. What is a practical exercise for SQL Exercises?

Answer: Build a small feature, change the inputs, add one validation rule, and explain the result in your own words.

❓Quiz

Which SQL topic is most important for exercises?

Joins and AggregationsHTML DesignVideo EditingNetworking

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