10 SQL Server Index Maintenance Best Practices

Indexes are a vital part of every SQL Server database. They are used to speed up the performance of queries by reducing the amount of data that needs to be scanned.

However, indexes can also become a performance bottleneck if they are not maintained properly. In this article, we will discuss 10 best practices for index maintenance in SQL Server.

1. Keep indexes as small as possible

The larger an index is, the more disk space it will consume. Not only that, but large indexes can also negatively impact query performance because they take longer to read from disk.

To keep indexes small, you should regularly check for and remove unused or unnecessary indexes. You can also consider using filtered indexes, which only index a subset of data, rather than the entire table.

2. Use the correct index type for your workload

If you have a workload that is write-heavy (lots of INSERT, UPDATE, and DELETE operations), then using a clustered index will not be as efficient as using a nonclustered index. This is because every time a row is inserted or deleted in a clustered index, the entire index must be rebuilt.

On the other hand, if your workload is read-heavy (lots of SELECT queries), then using a clustered index can be more efficient than using a nonclustered index. This is because a clustered index stores the data rows in the index, so when a query is run against the index, the data is already there and does not need to be retrieved from the underlying table.

Therefore, it is important to choose the right index type for your workload in order to optimize SQL Server performance.

3. Don’t over-index

Over-indexing can lead to:

1. Unused indexes taking up valuable storage space and negatively impacting performance
2. Wasted resources as the optimizer attempts to use too many indexes
3. Excessive index maintenance overhead
4. Difficulty troubleshooting query performance issues

It’s important to strike a balance when it comes to indexing. You don’t want too few indexes, as that will impact query performance, but you also don’t want too many indexes, as that will lead to the problems listed above.

The best way to find this balance is to start with a baseline of indexes and then add or remove indexes as needed based on query performance. Use tools like SQL Server Management Studio (SSMS) to help you identify which indexes are being used and which ones are not.

4. Rebuild or reorganize fragmented indexes

Over time, as data is inserted, deleted, and updated in a database, indexes can become fragmented. This means that the index pages are no longer stored in contiguous pages on disk, which can lead to performance issues.

When an index is rebuilt, the entire index is dropped and recreated from scratch. This means that all of the index pages will be stored contiguously on disk, which can improve performance.

Reorganizing an index is similar to rebuilding an index, but instead of dropping and recreating the entire index, only the index pages that are out of order are reorganized. This can be less disruptive than rebuilding an index, but it may not provide as much of a performance boost.

5. Update statistics regularly

Out-of-date statistics can cause the query optimizer to make suboptimal decisions when creating execution plans. This can lead to slow performance and, in some cases, incorrect results.

To avoid these problems, it’s important to update statistics regularly, especially after data changes. The frequency of updates will depend on your application’s workload and how often data changes. In most cases, though, it’s a good idea to update statistics at least weekly.

There are two ways to update statistics: manually or using an automated process. If you have a small database with infrequent data changes, you can update statistics manually as needed. For larger databases, though, it’s usually best to automate the process.

SQL Server provides two built-in tools for automating index maintenance: SQL Server Agent and Maintenance Plans. SQL Server Agent is a more powerful tool that gives you more control over the process, but it requires more setup and configuration. Maintenance Plans, on the other hand, are easier to use but provide less control.

Which tool you use is up to you, but in most cases, either one will work just fine.

6. Monitor and troubleshoot performance issues

If you’re not monitoring your SQL Server indexes, you won’t know when they need to be rebuilt or reorganized. This can lead to suboptimal performance and, in some cases, data corruption.

Additionally, if you’re not troubleshooting performance issues, you won’t be able to identify and fix the root cause of the problem. This can lead to a never-ending cycle of index rebuilds and reorganizations that don’t actually improve performance.

To avoid these problems, it’s important to monitor your SQL Server indexes on a regular basis and troubleshoot any performance issues that arise.

7. Consider partitioning large tables

Partitioning can improve query performance by allowing the SQL Server query optimizer to more easily identify which partitions of a large table contain the data that is required for a particular query. In addition, partitioning can help to reduce index fragmentation because indexes can be rebuilt or reorganized on a per-partition basis rather than on the entire table.

Finally, partitioning can make it easier to manage large tables by allowing them to be divided into smaller logical units. For example, you could partition a large table by date so that data for each year is stored in a separate partition. This would make it easier to delete old data or to move data to a different storage device (such as a slower-performing hard drive) when it is no longer needed.

8. Use filtered indexes to improve query performance

Filtered indexes are a special type of index that only includes a subset of the rows in a table. This can be useful when you have queries that only need to access a small percentage of the data in a table. By only including the relevant data in the index, you can reduce the size of the index and improve query performance.

To create a filtered index, you use the WHERE clause in the CREATE INDEX statement. For example, let’s say you have a table of orders with a column for the order status. You could create a filtered index on this table that only includes orders with a status of ‘Shipped’.

CREATE INDEX IX_Orders_Status ON Orders(Status) WHERE Status = ‘Shipped’

This index would be much smaller than an index that included all of the data in the table, and it would be more efficient for queries that only need to access shipped orders.

You should also consider using filtered indexes when you have large tables with infrequently accessed data. For example, you might have a history table that only gets queried once a month. In this case, you could create a filtered index that only includes data from the current month. This would reduce the size of the index and improve query performance.

9. Avoid using indexed views in OLTP systems

Indexed views can greatly improve query performance in data warehouses and other reporting systems that primarily use read-only workloads. However, in OLTP systems where data is constantly being inserted, updated, and deleted, indexed views can actually degrade performance.

This is because every time data in the underlying table is modified, the index must be updated as well. This can lead to increased disk IO and CPU usage, which can impact the performance of the entire system.

If you do need to use an indexed view in an OLTP system, make sure to carefully monitor performance and make sure the benefits outweigh the costs.

10. Implement a maintenance plan

A maintenance plan gives you a centralized way to schedule and automate all of your index maintenance tasks. This includes creating new indexes, rebuilding or reorganizing existing indexes, and deleting unused indexes.

Without a maintenance plan, you would have to manually perform these tasks on an ad-hoc basis, which is not only time-consuming, but it’s also prone to human error. A maintenance plan ensures that your index maintenance tasks are carried out consistently and reliably.