Advanced SQL Server Index Maintenance for DBAs
Understanding SQL Server Indexes
Maintaining indexes is a vital task for database administrators that requires a deep understanding of the underlying structures and principles. SQL Server indexes are crucial for improving database performance by allowing the server to find and retrieve data much more quickly than it could otherwise. Similar to the index in a book, a SQL Server index allows the database engine to jump directly to the information needed, skipping over the unnecessary data.
There are two main types of indexes in SQL Server: clustered and non-clustered. A clustered index sorts and stores the data rows of the table or view physically in order based on the index key. There can be only one clustered index per table because the data rows can be sorted in only one order. In contrast, a non-clustered index is a separate structure from the data rows. It contains a sorted list of references to the table itself and can have multiple per table. Additionally, columnstore indexes offer a unique method for storing and querying large data sets, providing a high level of compression and performance for data warehousing queries.
Index Maintenance Basics
Regular maintenance of SQL Server indexes is essential to ensure that queries are executed as efficiently as possible. Index maintenance primarily involves two operations: rebuilding and reorganizing. Index rebuilding creates a new copy of the index and allows SQL Server to directly rebuild the index efficiently. Rebuilding indexes is a resource-intensive operation that typically requires database downtime. Index reorganizing, on the other hand, helps to de-fragment a clustered or a non-clustered index by physically reordering the leaf-level pages to match the logical order. Reorganizing is less intensive than rebuilding and can often be done online without significant downtime.
Understanding when to rebuild or reorganize an index is crucial. As a rule of thumb, if the indexstrong>fragmentation is between 5% and 30%, reorganizing the index may be beneficial. For fragmentation over 30%, consider rebuilding the index.
Fighting Fragmentation Strategies
Index fragmentation occurs over time as continual insert, delete, and update operations cause the index’s data to become scattered, or ‘fragmented’. This scattering results in inefficient reads and can adversely affect query performance. To fight fragmentation, DBAs should build a strategy that includes both proactive and reactive measures. Proactive measures may involve careful selection of index FILLFACTOR, which determines how full the leaf level of an index page will be when it is first created, thus leaving room for future growth. On the reactive side, index maintenance jobs should be scheduled to regularly rebuild or reorganize indexes.
Automated Index Maintenance
One way to ensure that index maintenance does not fall by the wayside is through automation. SQL Server offers the ability to create maintenance plans that can schedule the rebuilding or reorganizing of indexes on a set schedule. By using tools like SQL Server Agent, databases can run index maintenance tasks during periods of low activity without the need for direct DBA intervention. However, automated maintenance should not be completely ‘set and forget’. It’s important to monitor and adjust maintenance plans to align with evolving database use patterns over time.
Online Index Operations
In an effort to minimize downtime, SQL Server has capabilities for online index operations. These operations allow users to access the underlying data, even as indexes are being rebuilt or reorganized. It’s important to note that online index operations can still impact database performance due to increased resource usage. Therefore, these types of operations should still be strategically scheduled.
Monitoring Index Usage and Performance
DBAs should constantly be monitoring index usage and performance to understand how their indexing strategy is affecting the database. Using Dynamic Management Views (DMVs) and functions like sys.dm_db_index_usage_stats can assist in identifying indexes that are not being used and may be candidates for removal, potentially freeing up resources.
