SQL Server Indexing: A Guide to Covering Indexes and Included Columns
Introduction
Indexing is a powerful tool in the world of databases, one that when used wisely, can dramatically improve the performance of queries. In SQL Server, indexes are crucial for speeding up the retrieval of data and ensuring efficient operation of the database system. Covering indexes and included columns are special types of indexes that further enhance SQL Server’s efficiency. Let’s delve into the detailed aspects of these indexes, unveil their benefits, and provide guidance on when and how to use them appropriately.
Understanding Indexes in SQL Server
An index in SQL Server is similar to an index in a book – it helps you to quickly find the data without going through all the pages. The indexes contain keys, a small set of columns, chosen from the table across which they are created, that determine the order of data. When searching for data, SQL Server consults the index to find the location of the data in the table quickly, significantly reducing query times.
There are several types of indexes in SQL Server, the most commonly used being:
- Clustered Index: Dictates the physical storage order of the table data itself and can be viewed as a dictionary organized alphabetically. Each table can have only one clustered index.
- Non-Clustered Index: Does not alter the physical storage of the Table data like a clustered index and typically considers a separate structure from the data stores. A table can have multiple non-clustered indexes.
What are Covering Indexes?
Covering indexes are a form of non-clustered index tailor-made for specific queries. An index is said to be a covering index if it contains all the columns referenced by a query, including columns in the SELECT, JOIN, WHERE, GROUP BY, and ORDER BY clauses. When a query is executed using covering indexes, SQL Server can obtain all the necessary data from the index without having to reference the base table. This result can lead to significant improvement in query performance as it avoids unnecessary disk I/O operations.
The Power of Included Columns
Included columns complement covering indexes by providing a way to add non-key columns to an index. These are columns included in the index as leaf-level data, and they only exist in the non-clustered index’s leaf node, not affecting the index order but available to queries as if they were).
Included columns are beneficial when:
- A query needs to select columns not used for filtering, sorting or joining.
- Columns are too wide to be part of the index key.
- Columns are frequently used by queries that don’t qualify for a full covering index.
Designing a Covering Index
Creating an effective covering index involves identifying the queries that are most frequently executed or are performance-critical. It also requires understanding the columns that these queries use. The following steps should be observed while designing a covering index:
- Identify the columns that need to be included in the index’s key based on query predicates (WHERE, JOIN, GROUP BY, ORDER BY clauses).
- Determine the key columns’ order since the sequence can influence the index efficiency. Most of the time, the column with the most distinctive values should come first to maximize the index filtering potential.
- Add any remaining columns referenced in the queries as included columns in the non-clustered index.
Let’s consider an example of a simple query to illustrate the creation of a covering index:
SELECT LastName, FirstName, DOB
FROM Employees
WHERE DepartmentID = 5
AND EmploymentStatus = 'Active'
ORDER BY LastName
In the query above, a suitable covering index might involve including ‘DepartmentID’, ‘EmploymentStatus’, and ‘LastName’ as part of the index key columns because they are used in filtering and sorting. ‘FirstName’ and ‘DOB’ might then be included as included columns, as the query must return these but doesn’t filter or sort based on them.
Performance Benefits of Covering Indexes
Covering indexes provide many performance benefits, such as:
- Reduced I/O: Since all the data needed for a query can be found in the index, SQL Server can bypass scanning the table data, which reduces the disk I/O operations.
- Increased Index Efficiency: Index keys are smaller than the full table rows, so more index rows fit on a page. This means that SQL Server can read and process data more quickly.
- Improved Query Performance: By avoiding unnecessary reads and making more efficient use of memory, covering indexes drastically shorten query execution times.
- Minimized Lock Contention: Using covering indexes means that fewer data needs to be locked for reading; this reduces lock contention on the underlying table during high-concurrency scenarios.
It’s important to remember that while covering indexes can incredibly increase performance, they also incur overhead. More indexes increase the storage requirement and the maintenance work needed when the underlying data is updated (INSERT, UPDATE, DELETE operations).
Case for Included Columns
Included columns can make an existing non-clustered index into a covering index without changing the index’s key columns. This comes handy in situations where the maximum number of key columns (16) or the maximum index key size (900 bytes) limit has been reached. Since included columns do not contribute to the key size limit, they allow us to circumvent those restrictions.
Advantages of included columns comprise:
- Overall less cost than key columns, as they are only added to the non-clustered index leaf nodes.
- Better indexing options for queries with non-unique, wide, or multiple columns included in the SELECT clause that are not used in WHERE or JOIN conditions.
- Equipping the optimizer with more information thus potentially creating better execution plans.
Considerations for Implementing Covering and Included Column Indexes
When it comes to implementing covering and included column indexes, there are several considerations to keep in mind:
- Balance between Query Performance and Maintenance Overhead: Each additional index requires additional disk space and can impact insert, update, and delete performance. Regularly assess whether each index provides a sufficient performance benefit to justify its overhead.
- Monitor Index Usage: SQL Server provides Dynamic Management Views (DMVs) that allow you to check how often indexes are being used. Ensure that your covering and included column indexes are being utilized effectively.
- Avoid Redundant Indexes: Having multiple indexes with slight differences can lead to unnecessary overhead. Aim to have indexes that serve multiple queries instead of creating a new index for each query variant.
Conclusion
SQL Server indexing is a powerful feature, and mastering the use of covering indexes and included columns can yield significant performance gains. They make queries run faster by minimizing I/O operations and making more effective use of memory and CPU. A well-designed index will pay dividends in the form of quicker data retrievals, reports, and an overall smoother user experience. Remember to monitor and analyze the performance to fine-tune your indexes over time and adapt to changing query patterns in your environment. With these techniques in your arsenal, you are well-equipped to elevate the efficiency of your SQL Server databases.
