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📘 SQL Getting Started Guide

This guide is for absolute beginners. It covers the most common SQL clauses that form the foundation of nearly every query you'll write, including how to combine data from multiple tables.

🎯 Purpose

To provide a clear, simple introduction to the core building blocks of SQL. Use this as your very first step before diving into more complex topics.

🧱 The Core Building Blocks

A standard SQL query follows a logical order. Think of it as building a sentence to ask your database a question.

SELECT   -- What columns do you want to see?
FROM     -- Which table is the data in?
JOIN     -- What other table should be linked?
WHERE    -- How do you want to filter the rows?
GROUP BY -- How should you aggregate the data?
ORDER BY -- In what order should the results be?
LIMIT    -- How many rows should be returned?

1. SELECT and FROM

These are the only two mandatory clauses. SELECT specifies the columns you want, and FROM specifies the table they live in.

Task Example Query
Get all columns from a table SELECT * FROM customers;
Get specific columns from a table SELECT first_name, email FROM customers;
Rename a column in the output SELECT order_id, amount AS order_value FROM orders;

✔️ Tip: Using * is great for exploration, but in production, always list the specific columns you need. It's more efficient and predictable.

2. LIMIT

The LIMIT clause restricts the number of rows returned by your query. It's perfect for peeking at a table without fetching all the data.

Task Example Query
Get the first 10 rows from a table SELECT * FROM customers LIMIT 10;

✔️ Tip: Always use LIMIT when exploring large tables to save time and resources. It's usually one of the last clauses in a query.

3. WHERE

The WHERE clause filters your data to only include rows that meet a certain condition.

Task Example Query
Filter for a specific value SELECT * FROM products WHERE category = 'Books';
Filter based on a number SELECT * FROM orders WHERE amount > 100;
Combine multiple conditions SELECT * FROM users WHERE country = 'USA' AND last_seen > '2024-01-01';

✔️ Tip: You can use operators like =, !=, >, <, >=, <=, IN, LIKE, and BETWEEN.

4. JOINs

Most of the time, the data you need is split across multiple tables. JOINs are used to combine rows from two or more tables based on a related column between them.

Join Type Purpose Example Query
INNER JOIN Returns only the rows where the join key exists in both tables. SELECT * FROM customers c JOIN orders o ON c.id = o.customer_id;
LEFT JOIN Returns all rows from the left table, and matched rows from the right. SELECT * FROM customers c LEFT JOIN orders o ON c.id = o.customer_id;

✔️ Tip: LEFT JOIN is great for finding things that don't have a match. For example, finding all customers who have never placed an order.

5. GROUP BY

The GROUP BY clause is used with aggregate functions (like COUNT, SUM, AVG) to group rows that have the same values in specified columns into summary rows.

Task Example Query
Count orders per customer SELECT customer_id, COUNT(order_id) FROM orders GROUP BY customer_id;
Calculate total sales per category SELECT category, SUM(sales) FROM products GROUP BY category;

✔️ Tip: Any column in your SELECT statement that isn't an aggregate function must be in your GROUP BY clause.

6. ORDER BY

The ORDER BY clause sorts the final result set in ascending (ASC) or descending (DESC) order.

Task Example Query
Sort products by price (low to high) SELECT * FROM products ORDER BY price ASC;
Sort users by signup date (newest first) SELECT * FROM users ORDER BY signup_date DESC;

✔️ Tip: ASC is the default, so you can omit it. For descending order, you must specify DESC.

🧩 Putting It All Together

Here’s a complete query that uses all of these clauses to find the total sales for each product category, but only for orders placed in the USA. It then shows the top 10 highest-selling categories first.

-- Find the total sales for each product category in the USA
SELECT
    p.category,
    SUM(o.order_amount) AS total_sales
FROM
    orders AS o
INNER JOIN
    products AS p ON o.product_id = p.id
WHERE
    o.country = 'USA'
GROUP BY
    p.category
ORDER BY
    total_sales DESC
LIMIT 10;

This query answers a specific business question by combining filtering, aggregation, and sorting. Master these five clauses, and you're well on your way to writing powerful SQL!