Index selection strategy in MySQL - Mini Project: Build & Apply

Index Selection Strategy in MySQL

📖 Scenario: You are managing a small online bookstore database. You want to improve the speed of searching for books by their title and author.

🎯 Goal: Build a simple table for books and add indexes to optimize search queries on title and author.

📋 What You'll Learn

Create a table called books with columns id, title, and author

Add an index on the title column

Add an index on the author column

Write a query to select books by a specific title using the index

Write a query to select books by a specific author using the index

💡 Why This Matters

🌍 Real World

Indexing is used in real databases to speed up searches, like finding books quickly in an online bookstore.

💼 Career

Database administrators and developers use index selection strategies to optimize query performance and improve user experience.

1

Create the books table

Create a table called books with columns id as an integer primary key, title as VARCHAR(100), and author as VARCHAR(100).

MySQL

-- Your code here to create the books table

Hint

Use CREATE TABLE books and define the columns with their types and primary key.

2

Add indexes on title and author

Add an index named idx_title on the title column and an index named idx_author on the author column of the books table.

MySQL

CREATE TABLE books (
  id INT PRIMARY KEY,
  title VARCHAR(100),
  author VARCHAR(100)
);
-- Your code here to add indexes

Hint

Use CREATE INDEX index_name ON books(column_name) to add indexes.

3

Write a query to find books by title

Write a SELECT query to find all columns from books where the title is exactly 'The Great Gatsby'. Use the title column in the WHERE clause to utilize the index.

MySQL

CREATE TABLE books (
  id INT PRIMARY KEY,
  title VARCHAR(100),
  author VARCHAR(100)
);

CREATE INDEX idx_title ON books(title);
CREATE INDEX idx_author ON books(author);

-- Your code here to select books by title

Hint

Use SELECT * FROM books WHERE title = 'The Great Gatsby' to find books by title.

4

Write a query to find books by author

Write a SELECT query to find all columns from books where the author is exactly 'Jane Austen'. Use the author column in the WHERE clause to utilize the index.

MySQL

CREATE TABLE books (
  id INT PRIMARY KEY,
  title VARCHAR(100),
  author VARCHAR(100)
);

CREATE INDEX idx_title ON books(title);
CREATE INDEX idx_author ON books(author);

SELECT * FROM books WHERE title = 'The Great Gatsby';

-- Your code here to select books by author

Hint

Use SELECT * FROM books WHERE author = 'Jane Austen' to find books by author.

Practice

1. What is the main purpose of using an index in a MySQL database?

easy

A. To increase the size of the database

B. To speed up data retrieval by creating shortcuts

C. To backup the database automatically

D. To store data in a compressed format

Solution

1. Step 1: Understand what an index does

   An index creates a shortcut to quickly find data without scanning the whole table.

2. Step 2: Compare options with index purpose

   Only To speed up data retrieval by creating shortcuts describes speeding up data retrieval, which is the main use of indexes.

3. Final Answer:

   To speed up data retrieval by creating shortcuts -> Option B

4. Quick Check:

   Index = Speed up search [OK]

Hint: Indexes speed up searches by creating shortcuts [OK]

Common Mistakes:

• Thinking indexes compress data
• Confusing indexes with backups
• Believing indexes increase database size

2. Which of the following is the correct syntax to create an index on the column email in a table users?

easy

A. CREATE INDEX email_index ON users (email);

B. CREATE INDEX ON users email_index (email);

C. CREATE INDEX users.email_index (email);

D. INDEX CREATE email_index ON users (email);

Solution

1. Step 1: Recall correct CREATE INDEX syntax

   The correct syntax is: CREATE INDEX index_name ON table_name (column_name);

2. Step 2: Match syntax with options

   CREATE INDEX email_index ON users (email); matches the correct syntax exactly, others have wrong order or keywords.

3. Final Answer:

   CREATE INDEX email_index ON users (email); -> Option A

4. Quick Check:

   CREATE INDEX index_name ON table (column) [OK]

Hint: Remember: CREATE INDEX name ON table (column) [OK]

Common Mistakes:

• Swapping index name and table name
• Omitting ON keyword
• Wrong keyword order

3. Given a table orders with an index on customer_id, what will happen when you run this query?

SELECT * FROM orders WHERE customer_id = 123;

medium

A. The query will fail with a syntax error

B. The query will scan the entire table ignoring the index

C. The query will use the index to quickly find matching rows

D. The query will update the customer_id values

Solution

1. Step 1: Understand index usage in WHERE clause

   When a column in WHERE has an index, MySQL uses it to find rows faster.

2. Step 2: Analyze query behavior

   The query filters by customer_id, which has an index, so it uses the index to speed up search.

3. Final Answer:

   The query will use the index to quickly find matching rows -> Option C

4. Quick Check:

   Indexed column in WHERE = index used [OK]

Hint: WHERE on indexed column uses index automatically [OK]

Common Mistakes:

• Assuming full table scan always happens
• Confusing SELECT with UPDATE
• Expecting syntax errors in correct queries

4. You created an index on last_name but your query SELECT * FROM employees WHERE first_name = 'John'; is slow. What is the likely problem?

medium

A. The index on last_name is not used because the query filters on first_name

B. The index on last_name causes a syntax error

C. The query is missing a JOIN clause

D. The index automatically updates first_name values

Solution

1. Step 1: Identify which column is indexed

   The index is on last_name, but the query filters on first_name.

2. Step 2: Understand index usage

   Indexes only help if the filtered column is indexed; here first_name is not indexed, so index is unused.

3. Final Answer:

   The index on last_name is not used because the query filters on first_name -> Option A

4. Quick Check:

   Index column ≠ filtered column = no index use [OK]

Hint: Index helps only if filtered column matches indexed column [OK]

Common Mistakes:

• Expecting index on different column to help
• Thinking index causes syntax errors
• Confusing filtering with updating

5. You have a table products with columns category, price, and stock. You often run this query:

SELECT * FROM products WHERE category = 'Books' AND price < 20;

Which index strategy is best to speed up this query?

hard

A. Create an index only on price

B. Create separate indexes on category and stock

C. Create a composite index on (stock, price)

D. Create a composite index on (category, price)

Solution

1. Step 1: Analyze query filter columns

   The query filters on category and price together.

2. Step 2: Choose index covering both columns

   A composite index on (category, price) helps MySQL filter efficiently on both conditions.

3. Step 3: Evaluate other options

   Separate indexes or indexes on stock do not help this query's WHERE clause.

4. Final Answer:

   Create a composite index on (category, price) -> Option D

5. Quick Check:

   Composite index on filtered columns = best speed [OK]

Hint: Composite index on all filtered columns speeds queries best [OK]

Common Mistakes:

• Indexing unrelated columns
• Using separate indexes instead of composite
• Ignoring query filter columns