The INCLUDE Clause in SQL Server Indexing (2005, 2008)

The INCLUDE Clause in SQL Server Indexing (2005, 2008)

Here's why you'd use it:

• Covering Queries: Imagine a table storing employee data with columns for ID, department ID, and lastname. You have a non-clustered index on EmployeeID and DepartmentID. If you query for SELECT ID, DepartmentID, LastName FROM Employees WHERE DepartmentID = 10, the index can find employees in department 10, but it wouldn't have the LastName directly. Normally, the database would need to do an additional lookup to fetch the full data from the main table.

  By including LastName in the index using INCLUDE, the query can be entirely satisfied using just the index itself, avoiding the extra lookup and improving performance. This is called a covering index.

Things to Consider:

• Index Size: Including additional columns increases the size of the index, impacting storage and maintenance overhead.
• Balance is Key: Use INCLUDE strategically for frequently used queries that benefit from covering them.

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Example Code for INCLUDE Clause in SQL Server (2005 & 2008)

CREATE TABLE Customers (
  CustomerID int PRIMARY KEY,
  FirstName nvarchar(50) NOT NULL,
  LastName nvarchar(50) NOT NULL,
  DepartmentID int NOT NULL,
  FOREIGN KEY (DepartmentID) REFERENCES Departments(DepartmentID)
);

CREATE NONCLUSTERED INDEX idx_Customer_Dept_LastName
  ON Customers(DepartmentID) INCLUDE (LastName);

Explanation:

1. This code creates a table Customers with various columns.
2. We define a non-clustered index named idx_Customer_Dept_LastName on the DepartmentID column.
3. The INCLUDE clause specifies that the LastName column should also be included in the index structure.

Scenario:

Imagine a query that retrieves CustomerID, DepartmentID, and LastName for customers in a specific department (e.g., SELECT CustomerID, DepartmentID, LastName FROM Customers WHERE DepartmentID = 10).

• If all the columns needed in the SELECT clause are part of the leading key columns in the non-clustered index, it already acts as a covering index.
• This avoids the need for the INCLUDE clause altogether, potentially keeping the index size smaller.
• However, this approach might not be flexible if additional columns are frequently queried with the key columns.

Multiple Non-Clustered Indexes:

• Create separate non-clustered indexes for frequently used query patterns.
• One index can target the main filter condition (e.g., DepartmentID), while another focuses on frequently used additional columns (e.g., LastName).
• This approach can be effective but requires managing multiple indexes and can potentially increase storage overhead.

Materialized Views (SQL Server 2008 and Later):

• Materialized views are pre-computed copies of a query result stored as a separate table.
• If a specific query retrieves the same data frequently, a materialized view can significantly improve performance by pre-fetching and storing the results.
• However, materialized views require additional maintenance to keep them synchronized with the base table.

Choosing the Right Method:

The best approach depends on your specific data access patterns and workload. Here are some factors to consider:

• Frequency of Queries: Prioritize covering frequently used queries.
• Number of Included Columns: Balance performance gain with index size increase due to INCLUDE.
• Data Modification Frequency: If data changes often, materialized views require additional maintenance.