How MySQL Indexes Work

Introduction

• Discussion about MySQL indexes
• Highlighted effectiveness of MySQL indexes (reducing query time)
• Reference to a previous video demonstrating speed improvements

Example Scenario

• Using the authors table with 3 million records
• Query to find instances where the first name is "Jonas"
  • Initial query result: ~103 milliseconds
• Adding an index to the first name column
  • How to add an index: ALTER TABLE authors ADD INDEX author_index (first_name);
  • Indexed query result: ~2.7 milliseconds

Understanding MySQL Indexes

• Without Indexes: MySQL scans each row until it finds the matching value
  • Time-consuming process as it checks each row one by one
• With Indexes: MySQL uses a separate storage and ordered list for indexed column values
  • Efficient searching mechanism

How Indexing Works

• Compares database indexing to a book index
• Indexing process:
  1. Create separate storage for the indexed column, ordered list
  2. MySQL stores pointer locations (e.g., p10) linking back to the original table

Binary Search (B-Tree Indexing)

• MySQL uses a binary search-like method, called B-Tree
  • Start at the middle of the ordered index list
  • Eliminate half the search space based on comparison
  • Continue narrowing down the search area until the value is found
  • Retrieve matching records using pointer locations to the main table

Advantages of Indexes

• Significant reduction in query time
• Efficient data retrieval without scanning all rows

Types of Indexes

• Primary Key
• Unique
• Regular Index (demonstrated in example)
• Full Text Index
• All use the B-Tree structure for indexing

Conclusion

• Understanding of MySQL indexes and how they improve query performance
• Mention of future content on different types of indexes
• Call to action to like and subscribe the channel