The relation scheme given below is used to store information about the employees of a company, where empId is the key and deptId indicates the department to which the employee is assigned. Each employee is assigned to exactly one department. $\text{emp}(\underline{\text{empId}}, \text{name}, \text{gender}, \text{salary}, \text{deptId})$ Consider the following SQL query:select deptId, count(*) from emp where gender = "female" and salary > (select avg(salary) from emp) group by deptId;The above query gives, for each department in the company, the number of female employees whose salary is greater than the average salary of

To understand what the query computes, let us analyze its components step-by-step:

1. Subquery Analysis: The subquery is: select avg(salary) from emp This is an uncorrelated subquery without any WHERE clause or GROUP BY clause. Therefore, it computes the overall average salary of all employees in the entire company.

2. Outer Query Filtering (WHERE clause):where gender = "female" and salary > (select avg(salary) from emp) This filters rows from emp to retain only female employees whose salary exceeds the company-wide average salary computed by the subquery.

3. Grouping and Aggregation (GROUP BY and SELECT):group by deptId and select deptId, count(*) The qualifying female employee tuples are grouped by deptId, and count(*) counts the number of such employees in each department.

Hence, the query outputs, for each department, the number of female employees whose salary is greater than the average salary of employees in the company.

Therefore, option (B) is correct.