SQL Fundamentals

The SELECT Statement

The foundation of every SQL query — retrieve exactly the data you need from your database.

Targeted Retrieval — select specific columns instead of entire tables
Computed Columns — calculate values on the fly with expressions
Clean Output — alias columns for readable, report-ready results

SELECT is how you ask your database questions.

What is SELECT?

DfSELECT Statement

A SQL command that retrieves data from one or more tables. It specifies which columns to return and optionally filters, sorts, and limits the results.

SELECT column1, column2
FROM table_name;

Component	Description	Required
`SELECT`	Columns to retrieve	Yes
`column1, column2`	Specific columns or `*` for all	Yes
`FROM`	Table to query	Yes
`table_name`	Source table	Yes

Select All Columns

SELECT * FROM customers;

id	first_name	last_name	email	city
1	Alice	Johnson	alice@email.com	New York
2	Bob	Smith	bob@email.com	Los Angeles
3	Carol	Williams	carol@email.com	Chicago

Avoid SELECT * in production queries. It returns all columns, increases network traffic, consumes more memory, and breaks if the schema changes.

Select Specific Columns

SELECT first_name, last_name, email
FROM customers;

first_name	last_name	email
Alice	Johnson	alice@email.com
Bob	Smith	bob@email.com

-- SLOW: Returns all columns
SELECT * FROM customers WHERE city = 'New York';

-- FAST: Returns only needed columns
SELECT first_name, last_name, email
FROM customers
WHERE city = 'New York';

Expressions in SELECT

DfComputed Columns

You can create new columns by applying expressions to existing data. These computed columns appear in the result set with the alias you provide.

SELECT
    name,
    price,
    price * 1.08 AS price_with_tax,
    price * stock AS inventory_value,
    ROUND(price * 0.9, 2) AS discounted
FROM products;

name	price	price_with_tax	inventory_value	discounted
Mouse	29.99	32.39	4498.50	26.99
Keyboard	89.99	97.19	6749.25	80.99

Common Functions

-- String functions
SELECT
    UPPER(first_name) AS upper_name,
    LOWER(last_name) AS lower_name,
    LENGTH(email) AS email_length,
    CONCAT(first_name, ' ', last_name) AS full_name
FROM customers;

-- Math functions
SELECT
    price,
    ROUND(price, 0) AS rounded,
    CEIL(price) AS ceiling,
    FLOOR(price) AS floor_price,
    ABS(-price) AS absolute
FROM products;

-- Date functions
SELECT
    hire_date,
    YEAR(hire_date) AS hire_year,
    MONTH(hire_date) AS hire_month,
    DATEDIFF(CURRENT_DATE, hire_date) AS days_employed
FROM employees;

Column Aliases

SELECT
    first_name AS "First Name",
    last_name AS "Last Name",
    salary AS annual_salary,
    salary * 12 AS monthly_salary
FROM employees;

First Name	Last Name	annual_salary	monthly_salary
Alice	Johnson	75000	6250
Bob	Smith	62000	5166.67

Use double quotes for aliases with spaces. Without quotes, aliases cannot contain spaces or special characters.

SELECT Without a Table

-- Perform calculations without any table
SELECT 1 + 1 AS result;                    -- 2
SELECT CURRENT_DATE AS today;              -- 2024-01-15
SELECT 'Hello, World!' AS greeting;        -- Hello, World!
SELECT RANDOM();                           -- Random number

SQL Execution Order

DfExecution Order

SQL queries execute in a specific order: FROM → WHERE → GROUP BY → HAVING → SELECT → ORDER BY → LIMIT. Understanding this helps you write correct queries.

Step	Clause	What It Does
1	FROM	Identify source tables
2	WHERE	Filter rows
3	GROUP BY	Group rows
4	HAVING	Filter groups
5	SELECT	Choose columns
6	ORDER BY	Sort results
7	LIMIT	Restrict row count

-- What you write:
SELECT first_name, salary
FROM employees
WHERE department = 'Engineering'
ORDER BY salary DESC
LIMIT 5;

-- How it executes:
-- 1. FROM employees        → All employee rows
-- 2. WHERE department='Engineering' → Only engineers
-- 3. SELECT first_name, salary → Just those two columns
-- 4. ORDER BY salary DESC  → Highest salary first
-- 5. LIMIT 5               → Top 5 only

Performance Tips

Tip	Bad Example	Good Example	Impact
Use specific columns	`SELECT *`	`SELECT name, price`	Faster
Add WHERE clause	No filter	`WHERE id > 1000`	Fewer rows
Use LIMIT	Unlimited results	`LIMIT 100`	Smaller result

Always select only the columns you need. This reduces memory usage, network transfer, and allows the database to use covering indexes.

Common Mistakes

-- BAD: SELECT * in production
SELECT * FROM customers;

-- GOOD: Specific columns
SELECT id, first_name, last_name, email FROM customers;

-- BAD: Missing WHERE clause
SELECT * FROM customers;

-- GOOD: Filter with WHERE
SELECT * FROM customers WHERE is_active = TRUE;

-- BAD: No LIMIT for large tables
SELECT * FROM logs;

-- GOOD: Limit results
SELECT * FROM logs ORDER BY created_at DESC LIMIT 100;

Practice Exercises

Exercise 1: Write a query to select name and price from products, and calculate a 10% discount as discounted_price.

SELECT
    name,
    price,
    price * 0.9 AS discounted_price
FROM products;

Exercise 2: Select all employees with their annual salary (salary * 12).

SELECT
    first_name,
    last_name,
    salary,
    salary * 12 AS annual_salary
FROM employees;

Exercise 3: Select customers with formatted names and email length.

SELECT
    UPPER(first_name) AS first_name,
    UPPER(last_name) AS last_name,
    CONCAT(first_name, ' ', last_name) AS full_name,
    LENGTH(email) AS email_length
FROM customers;

Key Takeaways

SELECT retrieves data from a database — it's the most common SQL command
Use specific column names instead of * in production for better performance
Expressions compute new values — calculations, formatting, and transformations
Aliases (AS) make output cleaner — rename columns for readability
SQL executes in a specific order — FROM → WHERE → SELECT → ORDER BY

SELECT Statement