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We can use views to aggregate data in a meaningful way.
Let’s say we need to run various queries against the database to return information regarding items that customers have purchased.
Let’s see what happens, however, if we turn our standard view into an indexed view.
Before we start, I should mention that there are a host of requirements attached to the creation of indexed views, in any SQL Server Edition.
These examples assume you’re running SQL Server Enterprise Edition, which will automatically consider indexes on a view when creating a query execution plan, whereas SQL Server Standard Edition won’t; you’ll need to use the clause of any query you wish to use the view (more on this shortly).
When we re-run the query from Listing 3, we get the same result set, but the execution plan, shown in Figure 4, looks very different.
In other words, when we query a simple view, the optimizer still has to access all of the underlying tables and perform the necessary s and aggregations.
Views make queries faster to write, but they don’t improve the underlying query performance.
However, we can add a unique, clustered index to a view, creating an indexed view, and realize potential and sometimes significant performance benefits, especially when performing complex aggregations and other calculations.
In short, if an indexed view can satisfy a query, then under certain circumstances, this can drastically reduce the amount of work that SQL Server needs to do to return the required data, and so improve query performance.
To make it easier for our application to consume this data, we can create a view Listing 2 creates a view based on our query definition, as shown in Listing 2. In order to make one of these changes, we would have to drop the view, change the table, and then recreate the view (and any indexes on the view).
Now, each application simply has to run a much simpler query referencing the view, as shown in Listing 3.