Exercise 20.2 Consider the following BCNF relational schema for a portion of a university...

Exercise 20.2 Consider the following BCNF relational schema for a portion of a university database (type information is not relevant to this question and is omitted):

Prof(ssno, pname, office, age, sex, specialty, dept_did)
Dept(did, dname, budget, num_majors, chair_ssno)

Suppose you know that the following queries are the five most common queries in the workload for this university and that all five are roughly equivalent in frequency and importance:

• List the names, ages, and offices of professors of a user-specified sex (male or female) who have a user-specified research specialty (e.g., recursive query processing). Assume that the university has a diverse set of faculty members, making it very uncommon for more than a few professors to have the same research specialty.
• List all the department information for departments with professors in a user-specified age range.
• List the department id, department name, and chairperson name for departments with a user-specified number of majors.
• List the lowest budget for a department in the university.
• List all the information about professors who are department chairpersons.

These queries occur much more frequently than updates, so you should build whatever indexes you need to speed up these queries. However, you should not build any unnecessary indexes, as updates will occur (and would be slowed down by unnecessary indexes). Given this information, design a physical schema for the university database that will give good performance for the expected workload. In particular, decide which attributes should be indexed and whether each index should be a clustered index or an unclustered index. Assume that both B+ trees and hashed indexes are supported by the DBMS and that both single- and multiple-attribute index search keys are permitted.

1. Specify your physical design by identifying the attributes you recommend indexing on, indicating whether each index should be clustered or unclustered and whether it should be a B+ tree or a hashed index.
2. Assume that this workload is to be tuned with an automatic index tuning wizard. Outline the main steps in the algorithm and the set of candidate configurations considered.
3. Redesign the physical schema, assuming that the set of important queries is changed to be the following:
   • List the number of different specialties covered by professors in each department, by department.
   • Find the department with the fewest majors.
   • Find the youngest professor who is a department chairperson.