Optimize SQL Queries: Make Your Database Run Faster

Optimize SQL Queries: Make Your Database Run Faster

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Optimize SQL Queries: Make Your Database Run Faster

As a business or project owner, you know the importance of efficiently using resources. You know that time wasted on inefficient queries is expensive. Your business may rely on cloud database technology for its robust ability to store and analyze data. But unless you optimize SQL queries, you’re likely wasting resources, overspending, and missing out on the full potential of your data. 

The good news is, that there are several ways you can improve your query quality and runtime, making the most of your data while reducing costs. Here, we’ll look at six ways to optimize SQL queries, to help your business analyze more data, faster. 

Know Your Data

The first rule is the most important of all. You need to understand the data itself.  Which tables contain the information you need?  How are they structured?  What indexes are present?  Do you know the difference between a table (which contains the data) and a view (which is just a saved query)?  The more you understand the data within the database, the easier it will be to design efficient queries.  

Go Minimal

Just as you wouldn’t add items to a shopping list you don’t need, when you set out to optimize SQL queries, you want to be efficient and precise. This means avoiding unnecessary retrievals or redundant data wherever possible. By reducing the amount of information you retrieve from a dataset, you also reduce the amount of fine-tuning and analysis required, once you have it. 

In our shopping example, a wasteful list might include flashlights, pens, and coffee mugs, when you only need a new coffee mug. By making the effort to go to separate locations to find flashlights and pens, you waste time and money. In addition, you need to sort through the items when you’re home from the store to find the coffee mug you want. 

An important way to optimize SQL queries is to reduce the number of columns and data rows retrieved. While typing “SELECT *” may be easier than identifying the specific set of columns you need, it can return much more data than needed, causing wasted resources (and reducing the impact of indexes, covered below). If you leave out proper JOIN and WHERE conditions, you’ll return extra rows you don’t need, resulting in a similar inefficiency. 

Organize Queries

Sometimes not understanding how the data is organized can have catastrophic results. Views – which are just saved queries – are often indistinguishable from tables to applications and often return data in the same way that tables do. However, a view can join several tables together and users can be tempted to join several views, resulting in highly complex queries containing redundant data sets and – you guessed it – wasted resources.

Even worse, views are sometimes used as source data for another view, which can be nested several layers deep. This is not to say that views are inherently bad or good. They are simply a tool that can be used properly or improperly.  

Know your data and how it is organized. Make sure that taking the easy path doesn’t lead to terrible performance and high resource costs.

Keep Indexes Efficient

If you’re using a relational database, it is important to use indexes effectively if you want to optimize SQL queries. Indexes can help to access data quickly and join tables efficiently. 

Make sure you understand how clustered and non-clustered indexes operate and organize your data. Practice creating and using clustered and non-clustered indexes, being careful not to create too many on any given table. An excess of indexes can slow operations such as UPDATE and INSERT.

If you build your query properly and design your indexes to match them, often your query will only use the index to obtain results, which usually uses far fewer resources than querying the whole table. Study the use of INCLUDE columns in a nonclustered index and how they can be used to help satisfy queries without requiring a large composite key.

Make Your JOIN Operations Work

If you’ve been working to optimize SQL queries, you know the importance of joins, especially if you work with complex queries. It’s important to understand how joins work and the differences between types of joins, as using the wrong join can create duplicates within data and slow down query runtime.

When you are joining two tables together, it is important to join them on a common column, otherwise your query may run long, wasting time and money. Beyond this important piece, you’ll want to know the nature of each join type. 

Left and right JOINS return all records from the primary table and only matching records from the joined, or secondary, table. In general, because we are used to reading left to right, a left join is easier to read than a right join. To facilitate this order of operation in your SQL query, simply change the order you are joining your tables. 

Inner joins return only matching records between the two tables, and are more common than outer joins. Cross joins return matched and unmatched rows from both tables, which creates duplicates and returns unnecessary data. While there may be a specific reason you need to rely on an outer join or cross join, usually, an inner join is a more efficient way to optimize SQL queries.

When possible, make sure the columns you are joining match with indexes using that column as the first (or only) key.

Monitor Query Progress and Performance

Sometimes your users will tell you which queries are causing problems, but oftentimes you will be left to identify complaints of overall sluggishness (ie “everything is slow”) from your users.  SQL Server has several built-in tools to help.

The Query Store is a fantastic feature available in versions of SQL starting with SQL 2016.  It can identify queries by long duration, most CPU usage, or highest disk utilization.  Once you’ve identified them, you can use the query plans to identify opportunities for improvement.

In versions where Query Store is not available, the use of Dynamic Management Views (DMVs) – a feature of SQL available since SQL 2005 – can help identify the top queries on your system.

As you’re tuning, you can use SET STATISTICS TIME and SET STATISTICS IO to identify what areas of your query are using the most CPU and I/O and work on making those parts more efficient using the techniques outlined above.

Whether your business is new to data analysis or your dataset has grown over time, it is important to optimize SQL queries. While cloud databases are both powerful and flexible, you need to be up-to-speed with best practices in SQL tactics to make the most of the technology while keeping costs down. 

One of the best ways to optimize SQL queries is to get to know the technology inside out. Knowing when to use which features and functions will deliver more reliable results. While we’ve covered a handful of ways to optimize SQL queries here, there are many more details to keep in mind. Unless you have highly-trained in-house expertise, you may want to seek the help of professionals. An experienced SQL team will set your business up for success, using SQL strategies and techniques that deliver precision and peace of mind. 

At SQL Tailor Consulting, we help our clients trade guesswork for precision. Using diagnostic tools and techniques, we’ll pinpoint the root cause of your SQL server’s performance issues to help you put an end to sluggish queries that waste time and money.    

Start with a free consultation. Whether you’re looking to eliminate slow queries, CPU or IO bottlenecks, inefficient joins, or nested loops, we take a proven, strategic approach to your data issues, eliminating problems while fine-tuning your SQL environment. At SQL Tailor Consulting, we’re ready to tackle your pain points while optimizing overall system performance. 

To get your Microsoft SQL server running at peak speed, call us for a free, no-obligation consult: 248-919-8086 or e-mail consult@sqltailor.com.

Picture of Joe Fleming (Farmington, MI)
Joe Fleming (Farmington, MI)

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