How To Optimize SQL Query Performance and Best Practices

By on November 1, 2021

If you use a database, you’ll need to use a query language to communicate with and retrieve valuable information from your database. While there are many different query languages, Microsoft Structured Query Language, also known as SQL, is the most popular. Proactively monitoring and maintaining your SQL database can go a long way toward helping you optimize your SQL query performance. However, there are also several best practices you can follow to optimize SQL queries.

Databases are becoming increasingly large and more complex, making SQL database query optimization a top priority. In this article, I’ll discuss what SQL queries are and best practices for improving their performance.

I’ll also recommend investing in tools like SolarWinds® Database Performance Analyzer or SolarWinds Database Performance Monitor to simplify the SQL query optimization process.

  • What Are SQL Queries?
  • How Can You Select Which Queries to Optimize?
  • What Are Some Best Practices for Optimizing SQL Query Performance?
  • Using an MS SQL Query Optimization Tool
  • Final Thoughts on Optimizing SQL Query Performance and Following Best Practices
  • What Are SQL Queries?

    SQL stands for Standard Query Language, and it’s the most popular database query language. First developed in the 1970s and previously named Structured English Query Language (SEQUEL), SQL was designed to manage, organize, and extract data found in relational database management systems (RDBMS).

    By using SQL, you can communicate with your databases. For example, if you need to retrieve specific information from a database, you can perform a SQL query. However, databases are limited by their hardware’s processing capabilities, which can result in slow queries. By engaging in SQL table optimization and reducing the number of calculations your software and hardware must perform, you can optimize SQL query performance and reduce their execution time.

    How Can You Select Which Queries to Optimize?

    Before you can optimize any queries, you have to decide which ones are best to optimize. Unfortunately, many people skip this critical step, but by targeting specific, troublesome queries with significant impacts on execution time, you can dramatically increase performance.

    If you are less selective when deciding which queries to optimize, you may end up wasting time and money by optimizing those that don’t significantly contribute to performance, don’t impact other queries, or don’t result in problems users will notice.

    When starting the MS SQL database query optimization process, look for queries that are consistently or occasionally slow, have red flags, or are major contributors to the total execution time.

    Consistently Slow Queries

    If you have a consistently slow query, it may be time to optimize it. When executed frequently, queries with high latency can cause performance issues, so it’s crucial to monitor and optimize them.

    Occasionally Slow Queries

    If a query is only occasionally slow, you may be wondering whether it’s worth the time, effort, and resources to optimize. Of course, the answer depends on which specific query is occasionally slow and whether its longer-than-average runtime is due to the query itself or something else. Sometimes a slow query can be the result of cache misses or poor overall server performance.

    However, if you notice an occasionally slow query—whether you decide to optimize it or not—it’s a good idea to monitor it carefully. Slow queries can indicate small, potentially server-wide problems and may worsen over time. Occasionally slow queries can also be a sign of occasionally broken functionality or long-tail latency problems.

    Queries With Red Flags

    Even if you haven’t noticed any performance issues yet, you may want to optimize some queries. It may be time to optimize any queries that have returned warnings and errors. If a query doesn’t use indexes, consider optimizing it. By proactively optimizing queries, you can prevent issues from occurring in the first place.

    Queries That Majorly Contribute to Total Execution Time

    If more than five percent of total execution time can be attributed to a single query, try to optimize the query in question. Focusing your efforts on optimizing major contributors rather than those that don’t significantly contribute to performance will enable you to use your time more efficiently.

    What Are Some Best Practices for Optimizing SQL Query Performance?

    Once you’ve identified which queries need improvement, it’s time to optimize them. As previously mentioned, reducing the number of calculations your software and hardware perform during a query can lead to optimal SQL query performance and a reduced execution time. Here are some tips and best practices for MS SQL database query optimization.

    Define Your Requirements

    When trying to find specific data, it’s essential to use an appropriate query, and the first step to finding the right one is deciding which data you want to retrieve. You should clearly define your requirements before writing the query, enabling you to receive only the information you need, potentially reduce runtime, and optimize SQL queries.

    Reduce Table Size

    SQL table optimization is an essential part of MS SQL database query optimization. To ensure you only receive the information you need, you can filter your data. Filtering data will reduce table size and optimize SQL queries’ runtime. Popular methods for SQL table optimization and query speed improvement include:

    • Providing a limited range of dates for time series data
    • Limiting the dataset in a subquery
    • Avoiding duplicate data

    Simplify Joins

    Sometimes, when a query joins tables, it drastically increases the result set’s row count, which can lead to a slow execution time. Before joining tables, try to reduce their size, as explained above.

    Something as simple as changing the order you join tables in can also optimize SQL queries. When joining two tables, start with the one that will return the fewest results after filtering.

    Use SELECT Fields FROM Instead of SELECT * FROM

    By using SELECT fields FROM instead of SELECT * FROM, you can narrow down the data fetched from the table during a query, increasing your query’s speed. The command SELECT * will fetch all the data from your table, whereas specifying fields can reduce query runtime by ensuring you only receive the necessary data.

    Similarly, using SELECT ID instead of SELECT DISTINCT can reduce the processing power required to perform the query while still returning unduplicated records. For example, if you want to find a specific customer, the query SELECT DISTINCT John, Smith, Canada FROM Customers might return several results, as many people in Canada are named John Smith. SELECT DISTINCT relies on the GROUP BY clause, which requires a lot of processing power. To further filter your results and use less processing power, try SELECT ID, John, Smith, Canada, Manitoba, Winnipeg, R2C 0A1 FROM Customers.

    Use EXISTS() Instead of COUNT()

    Though you can use both EXIST() and COUNT() to discover whether the table has a specific record, using EXIST() is more effective. While COUNT() will search the entire table to provide the total number of matching records, EXIST() will only run until it locates the record’s first entry in the table, saving you time and computing power and enabling you to optimize SQL queries.

    Use WHERE Instead of HAVING

    Another SQL query optimization technique is using WHERE instead of HAVING. WHERE queries execute more quickly than HAVING queries. WHERE queries filter records before groups are created, while HAVING queries filter data from groups. As a result, using WHERE in place of HAVING is an easy strategy for SQL query optimization.

    Add EXPLAIN to the Beginning of a Query

    By adding EXPLAIN to the beginning of a query, you can view your query execution plan and get a better idea of how long your runtime will be. Though it’s not always completely accurate, your query execution plan will display both your query’s execution order and its cost (higher cost numbers signify a longer run time). To understand the order of execution, start reading your query execution plan from the bottom up.

    When you insert EXPLAIN at the beginning of a query, you can locate and modify the most expensive steps. Then run EXPLAIN again to determine whether the changes you made significantly reduced runtime. However, running EXPLAIN takes time and computing power, so you should only use it during the MS SQL query optimization process.

    Create SQL Server Indexes

    You can retrieve data faster and optimize SQL queries by using clustered and non-clustered SQL Server indexes. Indexes can reduce runtime, but it’s also important to consider how much disk space they require.

    In Microsoft SQL Server, you won’t need additional disk space for your clustered indexes. However, if you use non-clustered indexes, these indexes are stored separately and require more disk space.

    In addition to knowing how to properly create indexes, it’s key to understand when not to use indexes. If you have an incredibly large range of values, it might be better to scan the whole table rather than use an index. In cases where functions or operations are applied to a column, you shouldn’t use indexes. You should also evaluate your existing indexes.

    Avoid Running Queries in a Loop

    Running queries in a loop can significantly slow your runtime. In some cases, you may be able to bulk insert and update data, which is far more efficient than using loops.

    Using a Microsoft SQL Query Optimization Tool

    If you know your system has poor performance and needs refinement, but you can’t locate what specific queries need to be optimized, using an SQL query optimization tool will enable you to quickly and accurately identify queries for optimization.

    The query itself may not always be responsible for slow execution times, as other events occurring elsewhere can sometimes result in suboptimal performance. Without the help of an MS SQL query optimization tool, you may have difficulties differentiating between SQL queries in need of optimization and those that were simply slow at one point in the past due to other factors.

    While you can find queries in the MySQL Performance Schema, PostgreSQL pg_stat_statements, and query logs, using an MS SQL query optimization tool can save you time and frustration.

    SolarWinds Database Performance Analyzer (DPA)

    database performance analyzer
    © 2021 SolarWinds Worldwide, LLC. All rights reserved.

    DPA simplifies the process of monitoring, analyzing, and optimizing SQL query performance. Use the mass registration feature or the wizard to register database instances. Once DPA has been configured, you can easily find underperforming queries, tables, and applications. Then, you can move on to MS SQL database query optimization and SQL table optimization.

    Thanks to DPA’s continuous, down-to-the-second SQL database monitoring, you can perform real-time and historical SQL query performance analyses to identify and solve performance issues. DPA also can make searching for, filtering through, and managing SQL query statements fast and easy.

    Highly scalable, compatible with most common databases, and ready to support virtual, physical, and cloud-based databases, DPA can continue to support your organization as you grow or switch databases. You can integrate DPA data with SolarWinds Server & Application Monitor (SAM) via the Orion® Platform to access end-to-end monitoring throughout your servers and applications.

    SolarWinds Database Performance Monitor (DPM)

    database performance monitor
    © 2021 SolarWinds Worldwide, LLC. All rights reserved.

    You don’t have to rely on slow query logs to capture traffic and monitor your database or worry about accidentally taking down your entire server when logs are left running for an extended time. Instead, use DPM to gain better visibility into your databases and their performance. DPM can monitor traditional, open-source, and cloud-based databases, so you can quickly view key database and query information from a centralized location, regardless of where it originated, by taking advantage of DPM’s custom side-by-side views.

    Powerful and reliable, DPM simplifies database performance monitoring and MS SQL database query optimization. Monitoring SQL database performance with DPM can be more efficient than using a slow query log, but it’s also more thorough. For example, slow query logs don’t track CPU usage and can only run for short periods, as they require an immense amount of storage. By contrast, DPM is built to offer 24/7 database performance monitoring, capture valuable information, and supply comprehensive database performance analytics. You can access query samples and explain plans or correlate query behavior with system metrics to troubleshoot performance issues and optimize SQL queries more efficiently.

    Thanks to its customizable alerts, daily summary reports, and weekly summary reports, you can stay on top of database performance with DPM and gain a better understanding of your queries’ performance and your databases’ health.

    Final Thoughts on Optimizing SQL Query Performance and Following Best Practices

    Optimizing SQL query performance and following best practices starts with choosing which queries to optimize. Once you’ve decided which queries are worth optimizing, you can follow the recommendations above to minimize the number of calculations your software and hardware are responsible for performing and improve SQL query performance.

    When it comes to Microsoft SQL query optimization, SolarWinds Database Performance Analyzer (DPA) and Database Performance Monitor (DPM) are two of the best tools on the market. Register for a free, fully functional 14-day trial of Database Performance Analyzer or Database Performance Monitor today.

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