SQL Performance Tuning: Index Optimization

Understanding Indexes

An index is a database structure that improves the speed of data retrieval operations on a table at the cost of additional writes and storage space.

Indexes store a sorted copy of selected columns, allowing the database engine to quickly locate rows matching query conditions.

• Indexes reduce the need for full table scans.
• They can be created on one or multiple columns (composite indexes).
• Indexes must be maintained during data modifications (INSERT, UPDATE, DELETE).

Best Practices for Index Optimization

Effective index optimization requires understanding query patterns and balancing read and write performance.

• Create indexes on columns frequently used in WHERE clauses, JOIN conditions, and ORDER BY clauses.
• Use composite indexes when multiple columns are often queried together.
• Avoid indexing columns with high update frequency to reduce maintenance overhead.
• Limit the number of indexes to avoid excessive storage and slower writes.
• Regularly analyze query execution plans to identify missing or unused indexes.
• Consider index fill factor and fragmentation; rebuild or reorganize indexes as needed.

Common Mistakes in Indexing

Misusing indexes can degrade performance instead of improving it.

• Creating too many indexes leading to slower INSERT/UPDATE/DELETE operations.
• Indexing columns with low selectivity (e.g., boolean flags) that do not filter data effectively.
• Ignoring the order of columns in composite indexes, which affects index usage.
• Not updating statistics or ignoring index fragmentation.
• Relying solely on indexes without considering query rewriting or schema design.

Practical Example: Creating and Using Indexes

Let's consider a table named 'Employees' with columns 'EmployeeID', 'LastName', 'DepartmentID', and 'HireDate'.