Correlated subqueries

Correlated subqueries in SQL are nested queries where the inner query references a column from the outer query. These subqueries are evaluated for each row processed by the outer query.

Consider a table named Employees with columns EmployeeID, EmployeeName, and Salary. We want to retrieve all employees whose salary is greater than the average salary of their department.

SELECT EmployeeID, EmployeeName, Salary FROM Employees e1 WHERE Salary > ( SELECT AVG(Salary) FROM Employees e2 WHERE e1.DepartmentID = e2.DepartmentID );

In this example, the subquery (SELECT AVG(Salary) FROM Employees e2 WHERE e1.DepartmentID = e2.DepartmentID) is correlated because it references the DepartmentID column from the outer query (e1). For each row processed by the outer query, the subquery calculates the average salary of the corresponding department. The outer query then retrieves the EmployeeID, EmployeeName, and Salary where the salary is greater than the average salary of the department. This query returns employees whose salary exceeds the average salary of their department.

Comments

Performance Optimization

Performance optimization in SQL is crucial for ensuring that your database queries run efficiently, especially as the size and complexity of your data grow. Here are several strategies and techniques to optimize SQL performance: Indexing Create Indexes : Primary Key and Unique Indexes : These are automatically indexed. Ensure that your tables have primary keys and unique constraints where applicable. Foreign Keys : Index foreign key columns to speed up join operations. Composite Indexes : Use these when queries filter on multiple columns. The order of columns in the index should match the order in the query conditions. Avoid Over-Indexing: Too many indexes can slow down write operations (INSERT, UPDATE, DELETE). Only index columns that are frequently used in WHERE clauses, JOIN conditions, and as sorting keys. Query Optimization Use SELECT Statements Efficiently : SELECT Only Necessary Columns : Avoid using SELECT * ; specify only ...

DAX UPPER Function

The DAX UPPER function in Power BI is used to convert all characters in a text string to uppercase. This function is useful for standardizing text data, ensuring consistency in text values, and performing case-insensitive comparisons. Syntax: UPPER(<text>) <text>: The text string that you want to convert to uppercase. Purpose: The UPPER function helps ensure that text data is consistently formatted in uppercase. This can be essential for tasks like data cleaning, preparing text for comparisons, and ensuring uniformity in text-based fields. E xample: Suppose you have a table named "Customers" with a column "Name" that contains names in mixed case. You want to create a new column that shows all names in uppercase. UppercaseName = UPPER(Customers[Name]) Example Scenario: Assume you have the following "Customers" table: You can use the UPPER function as follows: Using the UPPER function, you can convert all names to uppercase: UppercaseName = ...

TechUplift: Elevating Your Expertise in Every Click

Unlock the potential of data with SQL Fundamental: Master querying, managing, and manipulating databases effortlessly. Empower your database mastery with PL/SQL: Unleash the full potential of Oracle databases through advanced programming and optimization. Unlock the Potential of Programming for Innovation and Efficiency. Transform raw data into actionable insights effortlessly. Empower Your Data Strategy with Power Dataware: Unleash the Potential of Data for Strategic Insights and Decision Making.

DataMindSphere

Search This Blog