Pro tip: SQL Server will let you know if you are missing an index that it could be using in your query. The suggestion will appear at the top of the query plan. If you right-click on the query plan where an index is suggested and select “Missing Index Details,” it will even generate the index creation script for you!
There is plenty of nuance that an experienced SQL wizard can pull from a query plan. However, for the standard developer, what you need to know is the difference between a seek and a scan.
There are many indexes that you can set on a field for specific purposes, but if you are attempting to improve performance, you will generally be creating a generic non-clustered index.
Note: The trade-off for more efficient queries is increased storage. Non-clustered indexes require their own storage since they are kept separate from the table data. Only index the fields that you need to filter or join on in order to find the best balance between storage and performance.
View: A view is essentially a stored query and it allows you to select from a dynamic set of data. I have often replaced cached tables with views if the data needs to be fresh and possibly transformed in some way. No changes are actually being stored, but you can include calculated fields, which make views a great option when you need dynamic, up-to-date data.
The SQL statement to create an index is pretty straightforward. The following statement will create a non-clustered index with the name idx_orderdate on the given field of the Orders table:
Stored procedure: This is the go-to for processing or transforming data. Stored procedures can be created and then run on a schedule if you need to make updates at certain times of the day or on a certain cadence.
Non-clustered index: Stores the indexed field separately from the table. This indexed field points to the data stored in the table, just like the index of a book. You can have as many non-clustered indexes as you want!
Indexing is the #1 way to optimize database performance. Indexing affects the way that data is stored in pages. By default, records are not stored in any guaranteed order, so essentially indexing a field causes the data to be stored in a predictable manner. Therefore, when you filter on that field, the query will run faster because SQL Server knows exactly where to start looking.
If you are interested in understanding database performance on a deeper level, being able to read a query execution plan is a useful skill. When you run a query, SQL Server is processing it based on an execution plan. You can generate the plan upon running your query or view a cached plan if your query has been running. This allows you to see how much time is being spent on each step in the query.
As a rule, seeks are more efficient. Typically, if you are looking to optimize a query, you should identify where scans are happening in your query and fix them. The easiest way to fix them is to make sure you’re joining on indexed fields.
However, there are other kinds of objects that access and transform that data in different ways. Using the best object for the job is important. Here are the basic rules that I use when deciding which to use for a use case:
You have now leveled up your SQL skills! Using these concepts, you can now optimize your database and query more efficiently. Whether you are querying from an application or building out your own stored procedures and views, these tips will make your job easier!
Pro tip: If you are creating indexes, you have to maintain them. Inserts, updates, and deletes cause fragmentation of your indexes. Therefore, unless your data is completely stagnant, you will need to rebuild your indexes based on how often the data is changing. Ideally, you should do this with a scheduled stored procedure so that performance is maintained consistently.
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