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Course Content
MySQL Tutorial
Welcome to the MySQL tutorial — crafted for everyone, whether you're taking your first steps into the world of databases or you're a developer looking to refine your skills with advanced MySQL techniques. From understanding the fundamentals of relational data to mastering complex SQL queries, transactions, stored procedures, and performance tuning — this guide has you covered.
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MySQL Environmental Setup
Setting up MySQL is the first step toward working with relational databases. Below is a complete guide to help you install and run MySQL on your system, whether you are using Windows, Linux, or macOS. The second step is to start and stop MySQL service on your system. This ensures the MySQL server is running and ready to accept connections and execute queries.
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MySQL Basics
SQL (Structured Query Language) is the standard language used to communicate with relational databases like MySQL. It allows you to create, modify, manage, and retrieve data from tables using simple and powerful commands.
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MySQL Crud Operations
CRUD stands for Create, Read, Update, and Delete — the basic operations you perform on data in any MySQL database. These operations allow you to insert new records, retrieve data, update existing values, and remove records when needed.
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MySQL Joins
In MySQL, JOINs are used to combine rows from two or more tables based on related columns. They are essential when your data is spread across multiple tables and you need to bring it together in one query result.
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Stored Procedures & Functions in MySQL
This section explains the concepts of stored procedures and user-defined functions (UDFs) in MySQL, covering their creation, usage, parameters, differences, control flow, determinism, and advanced behavior — nothing is skipped.
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MySQL Triggers
This section covers everything about Triggers and Events in MySQL — including what they are, how they work, when to use them, all the types available, and how to manage them. Each point comes with simple explanations and examples.
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User Management and Security in MySQL
Managing users and securing your MySQL server is essential to control access, protect data, and prevent unauthorized operations. MySQL provides powerful tools to handle users, assign roles, and enforce fine-grained access control using privileges.
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MySQL Performance Tuning
MySQL Performance Tuning is the process of optimizing how your database server, queries, indexes, and schema work together to provide the fastest and most resource-efficient responses. When a database starts to slow down under load, tuning ensures better speed, reduced CPU/memory usage, and quicker access to data — especially for high-traffic applications or large datasets. It involves query optimization, proper indexing, schema design, and server-level configurations that reduce delays and improve efficiency across all operations.
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Query Optimization Techniques in MySQL
Query optimization is the process of writing SQL queries in a way that minimizes execution time and resource usage (like CPU, memory, and disk I/O). MySQL’s optimizer decides the best way to execute your SQL query, but your query structure can drastically impact performance. By following smart query practices, using indexes, avoiding expensive operations, and understanding how MySQL executes your statements, you can dramatically boost your database performance.
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Replication in MySQL
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MySQL

When you use SELECT *, MySQL retrieves every column from a table — even if your application only needs a few of them. While this might seem convenient during development, it can seriously affect performance in production environments.

Why it’s a problem:

  • Increased I/O and memory usage: Retrieving unnecessary columns increases the size of the result set, consuming more memory on both the database server and client side.

  • Slower network transfer: The more data sent over the network, the longer it takes for queries to complete, especially when working with large tables or remote servers.

  • Reduced query optimization: MySQL’s query optimizer performs better when it knows exactly which columns are needed. With SELECT *, the optimizer has to work harder, sometimes generating less efficient execution plans.

  • Fragile code maintenance: If new columns are added to the table later, queries using SELECT * will automatically return them — which might break application logic or display unwanted data.

     

Instead of:

SELECT * FROM customers;

( Use only required columns: )

SELECT name, email FROM customers;

This reduces the amount of data transferred and processed, especially in large tables.