Indexing for Performance

Introduction

Indexing is a critical component in database design that significantly improves the performance of data retrieval operations. In this lesson, we will explore the concept of indexing, its types, and best practices for implementing indexes effectively.

What is Indexing?

Indexing is the process of creating a data structure that improves the speed of data retrieval operations on a database table. An index is similar to an index in a book, where it allows quick lookup of information without scanning the entire table.

Key Takeaway: Indexes can drastically reduce the amount of data the database engine needs to scan.

Types of Indexes

• Single-Column Index
• Composite Index (Multi-Column Index)
• Unique Index
• Full-Text Index
• Clustered Index
• Non-Clustered Index

How Indexes Work

When a query is executed, the database engine checks for indexes that match the query conditions. If an appropriate index exists, the engine uses the index to quickly locate the rows in the data pages. Here’s a simplified flowchart of index utilization:

            graph TD;
                A[Query Execution] --> B{Index Exists?};
                B -- Yes --> C[Use Index];
                B -- No --> D[Full Table Scan];
                C --> E[Retrieve Data];
                D --> E;
            

Best Practices

1. Identify Columns for Indexing: Focus on columns used in WHERE clauses, JOIN conditions, and ORDER BY clauses.
2. Limit the Number of Indexes: Too many indexes can slow down INSERT, UPDATE, and DELETE operations.
3. Regularly Analyze and Tune Indexes: Use database tools to analyze index usage and performance.
4. Consider Composite Indexes: For queries that filter on multiple columns, composite indexes can be beneficial.
5. Use Unique Indexes: Enforce data integrity by using unique indexes on columns that should not have duplicate values.

FAQ