SQL query optimization reduces the resources required for queries and improves overall system performance. In this article, we discuss SQL query optimization, how it is done, best practices, and its importance.
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What Is SQL Query Optimization?
SQL query optimization is an iterative process of writing thoughtful SQL queries and enhancing query performance in terms of execution time and representation of the database. Query optimization is an important feature for several relational database management systems (RDBMS).
Poorly written queries consume more system resources, take a long time to execute, and potentially cause service losses.
A query is a question or request for data or information from a database, and requires writing a set of pre-defined code that is understandable to the database. Structured query language (SQL) and other query languages are designed to retrieve or manage data in relational databases.
The queries in databases can be written in many different structures and can be executed through different algorithms. Poorly written queries consume more system resources, take a long time to execute, and potentially cause service losses. A perfect query can reduce execution time and lead to optimal SQL performance.
The major purposes of SQL query optimization are to:
- Reduce the response time and enhance query performance
- Reduce the CPU execution time to get faster results
- Minimize the number of resources used to improve throughput
How Is SQL Query Optimization Done?
It is important to ensure queries are in the optimal pathways and forms. SQL query processes need the best execution plan and computing resources, as they are CPU-intensive operations. SQL query optimization is done with three basic steps:
- Query parsing
- Query execution
Parsing ensures the query is syntactically and semantically correct. If the query syntax is correct, then it turns into expressions and passes to the next step.
Optimization plays an important role in a query’s performance, and it can be difficult. Any query execution plan considered for optimization must return the same results as before, but the performance should improve after optimization.
SQL Query optimization includes basic tasks like:
- Detecting critical parts that require improvement
- Analyzing query execution to find issues causing poor performance
- Improving query execution plans to optimize the queries
Finally, query execution involves taking the plan generated by the query optimization step and turning it into operations. This step returns results to users if no error occurred.
Read more: SQL Performance Tuning Best Practices
What Are the Best Practices?
Once users identify that a query needs improvement to optimize SQL performance, they can choose any optimization approach — there are many different ways to optimize SQL query performance. Some best practices are represented below.
Avoid SELECT *
A simple way to improve query performance is to replace SELECT * with actual column names. When developers use the SELECT * statement in the table, it reads every column’s available data.
When using the SELECT fields FROM instead of SELECT * FROM, you narrow down the data fetched from the table during a query, which helps increase the query’s speed.
Avoid Queries Inside a Loop
SQL query in a loop is run more than once, which can significantly slow down runtime. These queries unnecessarily consume memory, CPU power, and bandwidth. This impacts performance, especially when the SQL server is not on a local machine. Removing queries inside loops improves overall query performance.
Create SQL Server Indexes
Using SQL server indexes can reduce runtime and retrieve data faster. SQL queries can be optimized by using clustered and non-clustered SQL indexes. Non-clustered indexes are stored separately, and require more disk space. As such, it is important to understand when to use indexes.
Use OLAP Functions
The OLAP functions “extend the syntax of the SQL analytic function.” OLAP functionalities in SQL are faster and easy to use. SQL developers and DBAs who are familiar with the syntaxes can easily adapt and use them whenever possible.
OLAP functions can create all standard calculated measures, such as rank, moving aggregates, share, period-to-date, prior and future periods, parallel period, etc.
Keep Statistics Updated
The query optimizer uses statistics to determine how best to join tables, when the indexes should be used, and how to access those indexes, among other things. The SQL server statistics should be kept up to date, whether manually or automatically.
Out-of-date SQL server statistics can affect table, index, or column statistics, and cause poor-performing query plans.
Why Is SQL Query Optimization Important?
SQL query optimization can easily improve system performance, resulting in cost savings. Optimizing SQL queries can increase operational efficiency and accelerate performance time to market.
SQL query optimization is important for many reasons, including:
- Providing faster results in the SQL database
- Reducing the cost per query for processing
- Reducing the query processing stress of the database
- Consuming less memory for query processing
- Improving the overall performance of the system
Organizations enjoy reliable access to data and a high level of performance with faster response times. Optimizing SQL queries can not only improve overall system performance, but also the reputation of the organization. Ultimately, the best practices of SQL query optimization help users to achieve accurate and fast database results.