©Silberschatz, Korth and Sudarshan2.1Database System Concepts Huiswerk Lees delen 3.2, 3.3 van hoofdstuk 3. opgaven voor hoofdstuk 2: modelleeropgave 5 opgaven voor hoofdstuk 3: maak de queries voor de vragen uit 3.5 in relationele algebra; maak de queries 1-6 voor de bierdrinkerdatabase in tuppel calculus EN in relationele algebra.

©Silberschatz, Korth and Sudarshan2.2Database System Concepts Silberschats 3.5 a employee (person-name, street, city) works (person-name, company-name, salary) company (company-name, city) manages (person-name, manager_name) Find the names of all employees who work for FBC { t |  w  works ( t[person-name] =w[person-name] Λ w[company-name]=“FBC” )}

©Silberschatz, Korth and Sudarshan2.3Database System Concepts Silberschats 3.5 b employee (person-name, street, city) works (person-name, company-name, salary) company (company-name, city) manages (person-name, manager_name) Find the names and the cities of residence of all employees who work for FBC { t |  e  employee (t[person-name] = e[person-name] Λ t[city] = e[city] Λ  w  works ( w[person-name] =e[person-name] Λ w[company-name]=“FBC”))}

©Silberschatz, Korth and Sudarshan2.4Database System Concepts Silberschats 3.5 c employee (person-name, street, city) works (person-name, company-name, salary) company (company-name, city) manages (person-name, manager_name) Find the names, street address, and the cities of residence of all employees who work for First Bank Corporation and earn more that $10000 per annum. { t |  e  employee (t[person-name] = e[person-name] Λ t[city] = e[city] Λ t[street] = e[street] Λ  w  works ( w[person-name] =e[person-name] Λ w[company-name]=“FBC” Λ w[salary] >10000))} { t | t  employee Λ  w  works ( w[person-name] =t[person-name] Λ w[company-name]=“FBC” Λ w[salary] >10000))}

©Silberschatz, Korth and Sudarshan2.5Database System Concepts Silberschats 3.5 d employee (person-name, street, city) works (person-name, company-name, salary) company (company-name, city) manages (person-name, manager_name) Find the names of all employees who live in the same city as the company for which they work. { t |  w  works ( t[person-name] =w[person-name] Λ  c  company ( c[company-name=w[company-name] Λ  e  employee ( e[person-name] = w[person-name] Λ e[city] = c[city] )))}

©Silberschatz, Korth and Sudarshan2.6Database System Concepts Silberschats 3.5 e employee (person-name, street, city) works (person-name, company-name, salary) company (company-name, city) manages (person-name, manager_name) Find the names of all employees who live in the same city and on the same street as do their managers. { t |  e  employee (t[person-name] = e[person-name] Λ  m  manages ( m[person-name] = e[person-name] Λ  em  employee (em[person-name] = m[person-name] Λ e[city] = em[city] Λ e[street] = em[street] )))}

©Silberschatz, Korth and Sudarshan2.7Database System Concepts Silberschats 3.5 f employee (person-name, street, city) works (person-name, company-name, salary) company (company-name, city) manages (person-name, manager_name) Find the names of all employees in this database who do not work for FBC. single company assumption { t |  w  works (t[person-name]=w[person-name] Λ [company-name]≠“FBC”)} Multiple company assumption { t |  w  works (t[person-name]=w[person-name] Λ  w1  works (w[person-name] = w1[person-name]  w1[company-name]≠“FBC”))} Which assumption holds according to the definition of the database?

©Silberschatz, Korth and Sudarshan2.8Database System Concepts Silberschats 3.5 g employee (person-name, street, city) works (person-name, company-name, salary) company (company-name, city) manages (person-name, manager_name) Find the names of all employees who earn more than every employee of SBC. { t |  w  works (t[person-name]=w[person-name] Λ  w1  works (w1[company-name] = “SBC”  w[salary] > w1[salary] ))}

©Silberschatz, Korth and Sudarshan2.9Database System Concepts Silberschats 3.5 h employee (person-name, street, city) works (person-name, company-name, salary) company (company-name, city) manages (person-name, manager_name) Assume the companies may be located in several cities. Find all companies located in every city in which SBC is located. { t |  c  company (t[company-name]=c[company-name] Λ  c1  company (c1[company-name] = “SBC”   c2  company (c2[company-name]=c[company-name] Λ c2[city] = c1[city] )))}

©Silberschatz, Korth and Sudarshan2.10Database System Concepts Reduction of an E-R Schema to Tables Primary keys allow entity sets and relationship sets to be expressed uniformly as tables which represent the contents of the database. A database which conforms to an E-R diagram can be represented by a collection of tables. For each entity set and relationship set there is a unique table which is assigned the name of the corresponding entity set or relationship set. Each table has a number of columns (generally corresponding to attributes), which have unique names. Converting an E-R diagram to a table format is the basis for deriving a relational database design from an E-R diagram.

©Silberschatz, Korth and Sudarshan2.11Database System Concepts Representing Entity Sets as Tables A strong entity set reduces to a table with the same attributes.

©Silberschatz, Korth and Sudarshan2.12Database System Concepts Composite and Multivalued Attributes Composite attributes are flattened out by creating a separate attribute for each component attribute  E.g. given entity set customer with composite attribute name with component attributes first-name and last-name the table corresponding to the entity set has two attributes name.first-name and name.last-name A multivalued attribute M of an entity E is represented by a separate table EM  Table EM has attributes corresponding to the primary key of E and an attribute corresponding to multivalued attribute M  E.g. Multivalued attribute dependent-names of employee is represented by a table employee-dependent-names( employee-id, dname)  Each value of the multivalued attribute maps to a separate row of the table EM  E.g., an employee entity with primary key John and dependents Johnson and Johndotir maps to two rows: (John, Johnson) and (John, Johndotir)

©Silberschatz, Korth and Sudarshan2.13Database System Concepts Representing Weak Entity Sets A weak entity set becomes a table that includes a column for the primary key of the identifying strong entity set

©Silberschatz, Korth and Sudarshan2.14Database System Concepts Representing Relationship Sets as Tables A many-to-many relationship set is represented as a table with columns for the primary keys of the two participating entity sets, and any descriptive attributes of the relationship set. E.g.: table for relationship set borrower

©Silberschatz, Korth and Sudarshan2.15Database System Concepts Redundancy of Tables Many-to-one and one-to-many relationship sets that are total on the many-side can be represented by adding an extra attribute to the many side, containing the primary key of the one side E.g.: Instead of creating a table for relationship account- branch, add an attribute branch to the entity set account

©Silberschatz, Korth and Sudarshan2.16Database System Concepts Redundancy of Tables (Cont.) For one-to-one relationship sets, either side can be chosen to act as the “many” side  That is, extra attribute can be added to either of the tables corresponding to the two entity sets If participation is partial on the many side, replacing a table by an extra attribute in the relation corresponding to the “many” side could result in null values The table corresponding to a relationship set linking a weak entity set to its identifying strong entity set is redundant.  E.g. The payment table already contains the information that would appear in the loan-payment table (i.e., the columns loan-number and payment-number).

©Silberschatz, Korth and Sudarshan2.17Database System Concepts Representing Specialization as Tables Method 1:  Form a table for the higher level entity  Form a table for each lower level entity set, include primary key of higher level entity set and local attributes table table attributes personname, street, city customername, credit-rating employeename, salary  Drawback: getting information about, e.g., employee requires accessing two tables

©Silberschatz, Korth and Sudarshan2.18Database System Concepts Representing Specialization as Tables (Cont.) Method 2:  Form a table for each entity set with all local and inherited attributes table table attributes personname, street, city customername, street, city, credit-rating employee name, street, city, salary  If specialization is total, table for generalized entity (person) not required to store information  Can be defined as a “view” relation containing union of specialization tables  But explicit table may still be needed for foreign key constraints  Drawback: street and city may be stored redundantly for persons who are both customers and employees

©Silberschatz, Korth and Sudarshan2.19Database System Concepts Relations Corresponding to Aggregation To represent aggregation, create a table containing primary key of the aggregated relationship, the primary key of the associated entity set Any descriptive attributes

©Silberschatz, Korth and Sudarshan2.20Database System Concepts Relations Corresponding to Aggregation (Cont.) E.g. to represent aggregation manages between relationship works-on and entity set manager, create a table manages(employee-id, branch-name, title, manager-name) Table works-on is redundant provided we are willing to store null values for attribute manager-name in table manages

Example

©Silberschatz, Korth and Sudarshan2.22Database System Concepts Vertaal naar het relationeel model