In this article, we will explore the important points to consider when designing an optimal SQL index. A well-designed index can significantly improve the performance of your SQL Server queries. Let’s dive into the key considerations for index design.

1. Database Design

Before creating an index, it is crucial to understand the characteristics of your database. For Online Transaction Processing (OLTP) workloads with frequent data modifications, it is recommended to minimize the number of indexes to reduce the overhead on data modification operations. On the other hand, for Online Analytical Processing (OLAP) workloads, where SELECT queries are predominant, creating a larger number of indexes can enhance query performance.

Additionally, consider the size of the table. Indexing small tables with less than 1000 pages may not provide performance improvements. It’s also important to examine database views containing multiple joins and aggregations and create indexes on these views to optimize reading operations.

2. T-SQL Query Analysis

Studying frequently executed queries is essential for designing an effective SQL index. Identify the columns used in predicates and join conditions in these queries. By adding these columns to the index, you can speed up data retrieval operations. It is recommended to write data modification queries that affect multiple rows in a single query to reduce the index overhead on data modification statements.

3. Column Selection

When selecting columns for the index key, consider the characteristics of the column. Integer columns are often the best candidates for index keys due to their small size. Avoid using text, ntext, image, varchar(max), nvarchar(max), and varbinary(max) columns as index keys, although they can be added as non-key columns. UNIQUE and NOT NULL columns with high selectivity levels are good candidates for index keys.

Consider the location of the column in the query. Columns used in the WHERE clause, JOIN predictions, LIKE, and ORDER BY clauses are ideal candidates for indexing. Computed columns and foreign key columns can also benefit from indexing. When creating an index with multiple columns, prioritize the columns used in query conditions and match the sorting criteria with the ORDER BY clause to optimize query performance.

4. Index Types

Choose the appropriate index type based on query requirements. SQL Server offers various types of indexes, including clustered, non-clustered, unique, non-unique, columnstore, and rowstore indexes. Utilize specialized indexes like Filtered indexes for columns with well-defined data subsets. Start by creating a clustered index that covers frequently accessed columns, followed by non-clustered indexes for other queries. This approach ensures non-clustered indexes are built over the clustered index, minimizing the overhead of recreating non-clustered indexes.

5. Index Storage

Consider the storage location of the index to improve query performance. Storing non-clustered indexes on a different filegroup or disk drive than the main table can enhance I/O performance. Partitioning clustered and non-clustered indexes across multiple filegroups on separate disk drives can improve concurrent data access and retrieval operations. Additionally, use the FILLFACTOR option to specify the percentage of space filled on each leaf-level data page. This helps accommodate new or modified data without causing index fragmentation.

Remember to test the index on a development environment before implementing it in production. Regularly monitor and maintain the index to ensure its continued effectiveness.

By considering these key points, you can design an optimal SQL index that significantly improves the performance of your SQL Server queries.