Performance Tuning In Stored Procedure – This article covers some important techniques for setting up SQL queries. Query tuning is a very broad topic, but some important techniques never change for query tuning in SQL Server. This is a tough question, especially for those who are new to configuring SQL queries or thinking about getting started. Therefore, this article will be a good starting point for them. Other readers can also update their knowledge with this article. In the later parts of this article, we will mention these techniques that will help you in posing questions.

We should use asterisk (asterisk) only when we need to return all the columns in the table. However, this usage becomes a bad habit of programmers and they start writing their queries with “SELECT *” clause. At various times in my career as a database administrator, I have seen the “SELECT *” statement used to retrieve only one column in multi-column tables. Worse than this experience is that the developer is not aware of this problem. This usage method causes more network and I/O activity, so it negatively affects query performance due to more resource consumption. Now we will perform a very simple test to determine the performance difference between SELECT * statement and SELECT column_name1, column_name2, column_nameN. Let’s say that in a web application we need to display only two columns, but we have used an asterisk in our query.

Performance Tuning In Stored Procedure

SQL Server Management Studio (SSMS) provides a very useful tool to help you analyze and compare the performance of executed queries. The name of this tool is Customer Statistics, and we will enable this option before running the next two queries.

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As we can clearly see, there is a stark difference between the received network measurements of these two select statements in the Network Statistics section. At the same time, the comparison result of measuring the time statistics of the “SELECT *” statement does not change. It shows worse performance than “Select column_name1, column_name2, column_nameN”. Based on this information, we can conclude: “As much as possible, we should not use asterisks in SELECT clauses.

A scalar value function takes some parameters and returns a single value after some calculations. The main reason that scalar-valued functions have a negative impact on performance is that indexes cannot be used in this usage. When we analyze the query execution plan below, we see the index scan operator because the SUBSTRING function is used in the WHERE clause.

The index scan operator reads all index pages to find the correct entries. However, this operator consumes more I/O and takes more time. Whenever possible, we should avoid the index scan operator whenever we see it in our execution plans.

On the other hand, especially for this question, we can improve their performance with a small touch. Now we modify this query as follows so that the query optimizer decides to use a different operator.

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The Index Finder operator reads only qualified rows because this operator effectively uses indexes to retrieve the selected rows. At the same time, it shows good performance compared to the index scan operator.

Tip: Scalar-valued functions are executed for each row in the result set, so we must take the row number of the result set into account when using them. If you try to use them for queries that return a large number of rows, they can hurt the performance of the queries. However, Microsoft has broken this traditional chain with SQL Server 2019 and implemented some performance improvements in the query optimizer for scalar-valued functions, and if any query contains a scalar-valued function, it will provide more accurate execution plans. created For more information about this improvement, you can see the following article:

Covering indexes include all referenced columns in a query, so they improve the selectivity of the index and if any query uses that index, it provides more efficient data access. Before creating a covered index, we need to determine the cost-benefit analysis, because each new index directly affects the performance of the supplement. We will now analyze the execution plan for the following query.

As we have learned, the index scan operation does not show good performance when executing a query. To solve this problem, we create the following index. The main feature of this index is that it covers all the columns in the query either by the index key or the included columns.

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The query execution plan started using the index search operator, and this operator shows better performance than the index scan operator.

UNION ALL and UNION operators are used to combine two or more result sets to select one. However, the main difference between these two operators is that the UNION operator removes duplicate rows from the result set. In terms of matching queries, the UNION ALL operator performs better than the UNION operator. As a result, we must use the UNION ALL operator in select statements if we do not want duplicate rows in the result set. When we compare the execution plans for the following questions, we see a significant difference between these two execution plans. First we compare implementation plans.

When we analyze the comparison of execution plans, we can see that the Sort operator adds overhead to a select statement that uses the UNION operator. As a final word about these two operators, if we do not consider duplicate entries, we should use the UNION ALL operator to combine the result sets.

The implementation plan gives us a visual representation of the stages of request processing. When we analyze the execution plan, we can clearly understand the query roadmap, and this is also an important starting point for query tuning. Estimated and actual execution plans are two types of execution plans that we can use to analyze questions. During the generation of the calculated execution plan, the query is not executed, but is generated by the query optimizer. However, it lacks driving time measurement and warnings.

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On the other hand, the implementation plan itself contains more reliable information and measurements on this issue. Actual execution plans provide an advantage for customizing query performance.

Another approach could be to use a combination of execution plans for queries with longer execution times. First, we can check the tentative implementation plan and then re-analyze the actual implementation plan.

Tip: You cannot create a calculated execution plan if the query contains a temporary table. An error occurs when we try to create it. The following query returns an error when trying to create a calculated execution plan.

In this article, we have learned the important techniques for setting up SQL queries. Performance tuning is a complex and difficult task, but we can learn this concept from easy to difficult, and this article can be a good starting point to start. The following topics are also important to improve our search capabilities; so you can check out the articles below for the next step in your learning.

Sql Server Stored Procedure Recompile Options

Esat Erkec is a SQL Server expert who started his career as a software developer 8+ years ago. He is a SQL Server Microsoft Certified Solutions Expert.

The main part of his activity is focused on SQL Server database management and development. His current interests are Database Administration and Business Intelligence. You can find him on LinkedIn.

Stored procedures in SQL Server are prepared T-SQL codes that can be executed repeatedly by database users to perform data manipulation commands and data definition commands. We can list the following four features as advantages of stored procedures:

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The main benefit of stored procedures is that they are able to reuse compiled and cached query plans. At the first execution of a stored procedure, its execution plan is stored in the query plan cache, and this query plan is used in subsequent executions of the procedure. However, some factors can cause cached stored procedure query plans to be recompiled, and this process is called stored procedure recompilation. Recompiling a stored procedure has some advantages and disadvantages. Thus, after the index is rebuilt or the statistics are updated, the stored procedure query plan can be recomposed, and this new plan is usually more efficient. On the other hand, excessively high recompilation operations can increase CPU overhead and negatively affect the performance of the database engine.

In this article, we will use the Adventureworks sample database, and we will also use a sample stored procedure. We can create this SQL Server stored procedure instance through the following query.

Monitoring stored procedure recompilation in SQL Server

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