Master SQL with Top 10 Performance Boosting Tips

Top 10 Tips to Improve SQL Query Performance

Quick Summary: This article provides a comprehensive list of ten valuable tips to enhance SQL query performance, catering to beginners and seasoned developers. The article offers actionable insights for minimizing query execution times, reducing resource consumption, and ultimately improving overall database performance by covering a variety of indexing strategies, query optimization techniques, and database maintenance practices. By implementing these tips, developers can streamline SQL query optimization and unlock the full potential of their relational databases.

Introduction

Working with SQL is fun when one knows the best tips and tricks to work with it efficiently. So many aspects are a must to keep in mind while working with it.

SQL performance tuning is challenging; small changes can significantly affect performance. Furthermore, it involves optimizing queries, indexes, and server settings to enhance database responsiveness and efficiency.

Partnering with a custom software solution provider can enhance SQL query performance through optimization, strategies, indexing, querying tuning, and efficient database management techniques.

If you are new to SQL, writing SQL queries can be challenging, but don’t worry and keep reading.

In this article, we will help you learn about tips to write efficient SQL queries, how to improve performance tuning in SQL, how to optimize SQL queries, and SQL code optimization techniques, and we will also be exploring Python’s database connectivity. Without further ado, let’s get started!

How to Check SQL Server Query Performance: Step-by-Step Guide:

Checking SQL Queries is a task in itself. Undoubtedly, people need to keep several factors in mind while checking out the same. However, the steps they must follow are crucial. The steps that are needed to follow for knowing how to check query performance in an SQL server are as follows:

Enabling the Query Store:

Step 1: Move to SQL Server management and open it. One can use the query store feature of SQL server to monitor the performances of the database available. If you have the SQL server before 2016, you need to enable it manually.

Step 2: move to object explorer. A user can locate the option by clicking View Menu at the top of the screen and then hitting “Object. Explorer”

Step 3: The list of databases will appear here. A user needs to select the database they want to work with. After that, click on “Properties.”

Step 4: Hit on the Query Store option that appeared. After that, Select “On” under ″Operation Mode (Requested). After doing this, all the queries will be detected.

Step 5: Finally, refresh the database in the Object Explorer panel. Within a while, you will see the query folder added to the panel.

Step 6: Now, how you wish to customize the data is on you. By default, every 60 minutes, new stats get aggregated by the Query Store. If you want, you can change the interval for it as well.

SQL Performance Tuning: 7 Practical Tips for Developers

SQL performance tuning is an essential aspect of database development that focuses on optimizing the execution speed and efficiency of SQL queries. Improving SQL performance can significantly enhance the application’s speed and responsiveness, leading to a better user experience. Here are a few practical tips for developers to achieve SQL performance tuning:

Use Indexes Wisely:

An index is a data structure that efficiently finds and retrieves database rows. Properly chosen indexes can speed up SELECT, UPDATE, and DELETE operations. However, excessive or inappropriate indexing can slow down write operations. As a result, it creates indexes on columns utilized in WHERE clauses and JOIN conditions by analyzing query patterns. Avoid making too many indexes, especially on columns with low selectivity.

Optimize Your Queries:

Developers should carefully design SQL queries to be efficient and use the database’s full potential. Avoid using SELECT * and, instead, specify only the necessary columns. Minimize subqueries or correlated subqueries, as they can be performance bottlenecks. Based on the data relationship, use appropriate JOIN techniques (INNER JOIN, LEFT JOIN, etc.).

Be Cautious with Joins and Subqueries:

Joins and subqueries can be resource-intensive, especially if dealing with large datasets. Optimize your queries using appropriate JOIN conditions and ensuring that subqueries are written efficiently. Avoid using nested subqueries whenever possible.

Limit the Result Set:

Retrieve only the data that you need. If your query returns many rows, consider adding filters (WHERE clause) or pagination to limit the result set. Furthermore, it minimizes the data transferred between the database and the application, improving performance.

Appropriately Size and Configure the Database:

Ensure that the database is appropriately sized and configured for the workload it needs to handle. Adjust memory, cache sizes, and buffer pool settings based on the available hardware resources and expected query load. Regularly analyzing database performance helps developers to identify issues.

Batch Operations:

Consider using batch processing instead of executing individual SQL statements for repetitive operations. Batch operations reduce the overhead of establishing connections and can significantly improve performance, especially for INSERT, UPDATE, or DELETE operations.

Avoid Cursors:

Cursors are often used for iterative processing of rows in a result set, but they can be inefficient and resource-consuming. Furthermore, developers can use set-based operations instead of cursors to work on data.

Regularly Update Statistics:

Database management systems use statistics to optimize query execution plans. Regularly update statistics for tables and indexes to ensure the query optimizer can make informed decisions about the best execution plan.

Monitor and Fine-tune:

Implement monitoring and profiling tools to identify slow or frequently executed queries. Regularly review query execution plans, identify performance bottlenecks, and fine-tune the queries and database settings accordingly.

Tips to Improve SQL Query Performance

Best practices for Improve SQL Query Performance. Let’s have a look,

Do Not Use * In Select Statment.
If we use * then it gives all columns of the particular table and it takes time so that’s why it’s better to use the column name which is required for the result.

Example:-

SELECT * 
             FROM Department - - - Bad Parctice
             
             SELECT Id,DeptName,Description 
             FROM Department - - - Good Practice

Use Exists instead of Sub Query

If sometimes need to use subquery at that time first use Exist() function of the SQL server only when the subquery returns large data. In this case, Exist() function works faster than In because Exist() function returns a boolean value based on the query.

Example:-

SELECT Id, Name 
             FROM Employee 
             WHERE DeptId In (SELECT Id 
             FROM Department
             WHERE Name like ‘%Management%’) - - - Bad Practice
             
             SELECT Id, Name 
             FROM Employee 
             WHERE DeptId Exist (SELECT Id 
             FROM Department 
             WHERE Name like ‘%Management%’) - - - Good Practice

Use Proper join instead of subqueries

It’s better to use join instead of subquery because based on join like left or right query only checked that records which are matched with criteria while in subquery they check all records and then return result so it’s time-consuming that’s why in this case use proper join as per requirement.

Example:-

SELECT Id, Name 
             FROM Employee 
             WHERE DeptId in (SELECT Id 
             FROM Department
             WHERE Name like ‘%Management%’) - - Bad Practice
             
             SELECT Emp.Id, Emp.Name,Dept.DeptName 
             FROM Employee Emp
             RIGHT JOIN Department Dept on Emp.DeptId = Dept.Id
             WHERE Dept.DeptName like ‘%Management%’ - - - Good Practice

Use “Where” instead of “Having” a clause

Here if we use “Where” then it will check in all records with the specific condition while if we use “Having” at that time user must need to apply “Group by” and through the “Group by” all data are displayed in group-wise and then after “Having” clause find the data from only that grouping which are filtered by

“Group by“, that’s why it’s executing fastly compare to “Where” while any table has much more data.

Example:-

SELECT Emp.Id, Emp.Name,Dept.DeptName,Emp.Salary
             FROM Employee Emp
             RIGHT JOIN Department Dept on Emp.DeptId = Dept.Id
             WHERE Emp.Salary >= 20000; - - Good Practice
             
             SELECT Emp.Id, Emp.Name,Dept.DeptName,Emp.Salary
             FROM Employee Emp
             RIGHT JOIN Department Dept on Emp.DeptId = Dept.Id
             GROUP BY dept.DeptName
             HAVING Emp.Salary >= 20000; - - - Bad Practice

Apply index on necessary columns

An index creates a unique data column without overlapping each other. It improves the speed of data retrieval. While applied index on that time its work like as per the below diagram.

 

index on necessary columns

For user-defined stored procedures avoid prefixes like “sp_”

As in SQL databases, the master database has some inbuild stored procedures which are starting with “sp_” so whenever we create a user-defined stored procedure at that time we can avoid prefixes like “sp_” because when we use that stored procedure in our code at that time SQL first finds from master database and it takes some extra time that’s why if we give another name instead of “sp_” then it will take less time.

Apply UNION ALL instead of UNION if possible

The major difference between UNION and UNION ALL is that UNION returns distinct records while UNION ALL returns all records including duplicates. While we apply UNION on that time function first apply sort and then find the distinct record and then return a result that’s why it takes more time to compare to UNION ALL. As if we require only distinct records at that time we can use UNION.

Example:-

  • If table Employee have following records
    • Ramesh
    • Mahesh
    • Sita
    • Nita
    • Naresh
  • If table Employee_new have the following records
    • Sita
    • Gita
    • Ramesh
  • While we apply UNION at that time queries like:
    • SELECT * FROM Employee
      UNION
      SELECT * FROM Employee_new
  • Result:-
    • Ramesh
    • Mahesh
    • Sita
    • Nita
    • Naresh
    • Gita
  • While we apply UNION ALL at that time queries like:
    • SELECT * FROM Employee
      UNION ALL
      SELECT * FROM EMployee_new
  • Result:-
    • Ramesh
    • Mahesh
    • Sita
    • Nita
    • Naresh
    • Sita
    • Gita
    • Ramesh

Avoid Negative search

As we know sometimes users are using negative search in where conditions like not equals (<>), not like, etc. but we need to avoid that type of search because if we give the exact search criteria on that time while query executing if that type of data is got then immediately query returns the result. Negative searches decrease the query execution speed that’s why we need to avoid that.

Avoid query in a loop

If sometimes we need to execute the same query multiple times like if we need to insert 10 records in any table at that time don’t use insert query in the loop instead of using bulk insert.

Example:-

For(Int i = 0;i <= 5; i++)
             {
             INSER INTO Table1(Id,Value) Values( i , ‘Value’ + i );
             } - - - Bad Practice
             
             INSERT INTO Table1(Id, Value) 
             Values(1,Value1),(2,Value2),(2,Value3),(4,Value4),(5,Value5) - - - Good Practice

Apply valid datatype on the column

As we know sometimes some new users do not know the actual use of datatype and they all apply varchar datatype for all columns but it’s not the right way, as per client requirements we need to identify first which type of data is required and based on that need to apply proper datatype.

Example:-

  1. In the Isdelete column, we need to set only boolean (true, false) value if the record is deleted or not.
  2. In the Creation Date column, we need to set the DateTime datatype.
  3. If the Department column is used as the foreign key in any table at that time we need to store that department’s id only not a name so we can set Integer datatype.

How do you find SQL developers for your project?

When checking out the SQL efficiency, it is essential to have a team of experienced individuals available. If the experienced team is not available, one will not be able to figure out whether things are going in the right direction. Well, the factors that you need to keep in mind includ

Knowledge of software development in general:

The primary factor that is important to look out for includes their knowledge of software development. If they are aware of basic SDLC, there is a point in hiring them. Some instances are there where it is essential that, along with SQL query, they also have good hands-on experience in the software development life cycle. If you feel like they need more knowledge, look for someone else. Make sure not to settle for less while hiring the developer.

Able to maintain database security:

Database security is a challenge to maintain. Several tools, tricks, and techniques are essential to adapt to the same. Ask the developer about the securities that they are using. If they cannot maintain database security, they are not the ones with whom you can connect long-term. For long-term collaboration, clarity must be available regarding the tools and methods they adopt for database security. As soon they figure out that this will work in this way, then only the developers can be finalized.

You can also inform them about the tools you consider for database security. This will help you know whether they can align themselves with the same. If there is anything that you find suspicious, drop the idea and look for someone else for the same. A clear discussion will help get the best services.

Able to work with SQL environment:

The candidate’s proficiency in working with the SQL (Structured Query Language) environment is important to know. SQL query is a programming language that helps developers to manage and manipulate databases. The SQL developer should be familiar with writing SQL queries to retrieve, insert, update, and delete data from databases. They should be comfortable navigating through different database management systems (DBMS) like MySQL, PostgreSQL, SQL Server, Oracle, etc. Look for candidates who have practical experience in handling complex queries, optimizing database performance, and understanding database schemas

Cost for the project:

The cost for the project is the financial aspect of hiring the SQL developer. It involves negotiating and determining the remuneration or contract rate for the services provided by the developer. When evaluating the cost, consider the developer’s skills, experience, and the complexity of the project. A highly skilled and experienced developer may demand higher compensation, but they might also deliver better results in less time. On the other hand, hiring a less experienced developer might save money initially, but it could lead to longer development times and potentially subpar outcomes.

Time required for delivery:

The estimated timeframe the SQL developer requires to complete the project successfully is also essential. Assess the candidate’s ability to set realistic timelines and deliver projects on time. Look for developers who have experience in project management, understand the scope of work, and can provide a detailed timeline for different project milestones. A reliable and punctual developer is crucial to ensure that the project meets its deadlines and doesn’t face unnecessary delays.

How are they handling deadlines:

The candidate’s approach to managing and meeting project deadlines is something that one cannot overlook. An excellent SQL query developer should demonstrate a track record of meeting project timelines and delivering results within the agreed-upon timeframes. They should have strong organizational and time management skills to handle multiple tasks efficiently. Additionally, the developer should be proactive in communicating any potential delays or roadblocks that might impact the project’s progress.

Understanding of latest SQL query updates:

As technology evolves, SQL query is subject to updates and enhancements. A proficient SQL developer should keep up-to-date with the latest SQL query updates, new features, and improvements in database management systems. This ensures they can leverage the most current and efficient techniques in their work. During the hiring process, inquire about the candidate’s awareness of recent SQL query advancements, and ask them how they stay informed about changes in the SQL landscape.

Able to work with a dedicated team:

Being able to work effectively in a dedicated team is crucial for successful project execution. A good SQL developer should have strong communication skills and the ability to collaborate with other team members, including project managers, other developers, and stakeholders. Teamwork is essential for problem-solving, sharing knowledge, and delivering a cohesive final product. During the hiring process, look for candidates who can demonstrate their experience working in team environments and handling team-based projects.

Conclusion

In conclusion, working with SQL is fun. A developer needs to be sure of all the tips and tricks that they can follow to make things work. Developers should thoroughly understand query optimization SQL servers techniques. If you are someone who is working with SQL or want to know more about it, this read is best to consider. For sure after keeping all these parameters in mind you can get the best outputs as needed!

FAQ

SQL query performance directly impacts the responsiveness and efficiency of your application. Faster queries mean reduced user wait times and improved user experience, making it crucial for any database-driven application.

Common factors include a need for proper indexing, inefficient query design, large data sets, poorly written queries, and suboptimal database configuration.

Yes, regularly updating statistics and indexes is vital. Outdated statistics can lead to poor query plans, while well-maintained indexes improve query execution speed and overall database performance.

Yes, denormalization can enhance query performance in some cases. By reducing JOINs and data retrieval complexity, denormalization can speed up queries. However, it may lead to data integrity and maintenance challenges, so it should be carefully implemented.

In SQL, multiple tables can be combined using JOIN statements to retrieve data from related tables based on common columns, enabling complex queries and data analytics.