SQL performance optimization techniques

SQL performance optimization is the process of improving the performance of a database system. There are several techniques that can be used to optimize the performance of SQL queries. Here are some common ones:

• Indexing: Creating an index on columns that are frequently used in the WHERE clause of a query can significantly improve the performance of the query. For example, if you have a large table named employees and you frequently search for employees based on their employee_id, you can create an index on the employee_id column as follows:

• Normalization: Normalizing the data in the database can improve the performance of queries by reducing data redundancy and eliminating data anomalies. For example, if you have a table named employees that stores information about employees and their departments, you can split the data into two tables: employees and departments. This way, you can avoid storing duplicate data for departments and improve the performance of queries that retrieve information about employees and their departments.

• Avoid using wildcard characters: Using wildcard characters, such as %, in the LIKE operator can slow down the performance of a query. You should avoid using wildcard characters in the WHERE clause of a query whenever possible.

• Avoid using subqueries: Subqueries can be slow and impact the performance of a query. You should avoid using subqueries whenever possible and instead use join operations to retrieve data from multiple tables.

• Use appropriate data types: Using the appropriate data type for columns can improve the performance of queries. For example, if you have a column named age that stores the age of employees, you should use the INT data type instead of the VARCHAR data type.

• Use aggregate functions judiciously: Aggregate functions, such as SUM, AVG, and COUNT, can be slow and impact the performance of a query. You should use aggregate functions judiciously and only when necessary.

Here's an example of how you can optimize a query using the techniques described above:

In the original query, the LIKE operator is used with a wildcard character, which can slow down the performance of the query. In the optimized query, the LIKE operator is replaced with the = operator, which is faster.