Consider the following relational schema as part of a university database: Prof(ssn, pname, office, age, sex, specialty, dept_did) Dept(did, dname, budget, num_majors, chair_ssn) Assume the following queries are the most common queries in the workload for this university and they are almost equivalent in frequency and importance: 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. Specify the table and attributes you recommend indexing on. Note: If you can search with an index-only plan you should create a composite search key. Please define more than one index if it is necessary. 1. Find the maximum age of professors in each department. 2. List all the department information for departments with professors in a specified age range. 3. Find the name of professors who have a specified research specialty. 4. List names of the departments with the budget more than 100K. 5. List all the information about professors who are chairpersons of specified department ids.
Consider the following relational schema as part of a university database: Prof(ssn, pname, office, age, sex, specialty, dept_did) Dept(did, dname, budget, num_majors, chair_ssn) Assume the following queries are the most common queries in the workload for this university and they are almost equivalent in frequency and importance: 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. Specify the table and attributes you recommend indexing on. Note: If you can search with an index-only plan you should create a composite search key. Please define more than one index if it is necessary. 1. Find the maximum age of professors in each department. 2. List all the department information for departments with professors in a specified age range. 3. Find the name of professors who have a specified research specialty. 4. List names of the departments with the budget more than 100K. 5. List all the information about professors who are chairpersons of specified department ids.
Database System Concepts
7th Edition
ISBN:9780078022159
Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan
Chapter1: Introduction
Section: Chapter Questions
Problem 1PE
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Transcribed Image Text:Consider the following relational schema as part of a university database:
Prof(ssn, pname, office, age, sex, specialty, dept_did)
Dept(did, dname, budget, num_majors, chair_ssn)
Assume the following queries are the most common queries in the workload for this university
and they are almost equivalent in frequency and importance:
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. Specify the table and attributes you
recommend indexing on.
Note: If you can search with an index-only plan you should create a composite search key. Please define
more than one index if it is necessary.
1. Find the maximum age of professors in each department.
2.
List all the department information for departments with professors in a specified age range.
3. Find the name of professors who have a specified research specialty.
4.
List names of the departments with the budget more than 100K.
5. List all the information about professors who are chairpersons of specified department ids.
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VIEWStep 2: maximum age of professors in each department.
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VIEWStep 4: name of professors who have a specified research specialty.
VIEWStep 5: names of the departments with the budget more than 100K.
VIEWStep 6: List all the information about professors who are chairpersons of specified department ids.
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