The efficiency of an SQL server will be reliant on how well queries are composed, and taking the time to check for issues in this area can deliver big benefits. Optimizing queries is a key part of SQL server performance tuning, further details about which can be found here sentryone.com/sql-server/sql-server-performance-tuning. If you are looking for ways to improve queries but are not sure where to start, these quick tips should set you on the right path.
Striking a balance
Perhaps the most important tip for those aiming to optimize SQL server queries is that the term ‘optimal’ should have a different meaning in this context to what you might usually assume.
This is because query optimization can be an incredibly time consuming process, and so it is better to aim to strike a balance between the amount of energy you invest in addressing inefficiencies and the benefits that this work brings to the table.
Acceptable performance is really what you are looking for from optimization, rather than total perfection. Keeping this in mind before you proceed will help you adjust expectations and avoid unnecessary legwork.
Establishing purpose
Another important step to take before you make any changes to your queries is to work out what role a query plays and what the ideal outcome would look like.
Part of this process should include determining the size of the result set, the frequency with which the query will need to be executed and the performance parameters which will need to be met for end users to be satisfied.
Once you have thought about the purpose and importance of each query, you will be better able to prioritize your optimization efforts, rather than spending ages tinkering with a query that is a long way from being a lynchpin of the database’s ecosystem.
Using execution plans
Assessing an SQL query for suboptimal performance is much easier if you make use of an execution plan to map out its operations graphically, rather than simply scrolling through line after line of code manually and relying on your intuition.
Of course you still need to know what to look for when using execution plans, and the main aim here should be seeing which aspect of a query is the most resource-intensive. For example, if a particular portion is hammering the CPU or bottlenecking the I/O, it will probably need to be scrutinized.
Avoiding index overheads
When writing a query, one way of making it return relevant information in less time and without putting as much strain on the database’s hardware resources is to ensure that the index is being used efficiently.
This comes down to the difference between scanning the entire index as part of a query or seeking out results within a more specific range. The bigger the index, the longer a full scan will take. In some cases scanning will be more suitable than seeking, but more often than not it is far more optimal to be precise here.
Another way to leverage indexes to improve query performance is to create indexes in the case that there is an obvious gap in the current database that could be filled by one. Before you go ahead with the process of building a new index for a given use case, make sure to check to see whether it will be quicker and easier to alter an existing index to accommodate this requirement, rather than getting ahead of yourself. Also assess what improvements the new index will bring; if they are negligible, it may not be worthwhile.
Addressing query size
In the most basic terms, the larger a query becomes, the more time it will take to execute, which of course means that heftier queries are more of a burden.
This might make you assume that trimming queries to within an inch of their life is the most optimal way to manage a database. However, if this compromises the functionality of the supported services, you will actually be creating more problems than you solve. The popularity of SQL servers means that getting support with everything from query optimization to security is straightforward, but administrators still need to be able to handle basic maintenance tasks like this themselves.
