1. The Entity-Relationship Model
Relational Thinking
Demo some ER drawing tools, see wikipedia.
To demo SQL server on CSIL: log in, choose Cypress (not SQL-Lite). Choose SQL Server login.
Look up user name, password from helpdesk, something like s_oschulte.
Chapter 1: Introduction to Database Systems
Chapter 2: The Entity-Relationship Model
Chapter 3: The Relational Model
Chapter 4 (Part A): Relational Algebra
Chapter 4 (Part B): Relational Calculus
Chapter 5: SQL: Queries, Programming, Triggers
Chapter 6: Query-by-Example (QBE)
Chapter 7: Storing Data: Disks and Files
Chapter 8: File Organizations and Indexing
Chapter 9: Tree-Structured Indexing
Chapter 10: Hash-Based Indexing
Chapter 11: External Sorting
Chapter 12 (Part A): Evaluation of Relational Operators
Chapter 12 (Part B): Evaluation of Relational Operators: Other Techniques
Chapter 13: Introduction to Query Optimization
Chapter 14: A Typical Relational Optimizer
Chapter 15: Schema Refinement and Normal Forms
Chapter 16 (Part A): Physical Database Design
Chapter 16 (Part B): Database Tuning
Chapter 17: Security
Chapter 18: Transaction Management Overview
Chapter 19: Concurrency Control
Chapter 20: Crash Recovery
Chapter 21: Parallel and Distributed Databases
Chapter 22: Internet Databases
Chapter 23: Decision Support
Chapter 24: Data Mining
Chapter 25: Object-Database Systems
Chapter 26: Spatial Data Management
Chapter 27: Deductive Databases
Chapter 28: Additional Topics 1

2. Overview Relational Model Entity-Relationship Diagrams. Motivation.
Definition.
Entity-Relationship Diagrams.
Key Constraints.
Participation Constraints.
Weak Entities.
ISA Hierarchy.

3. Relational Databases: History
1970s: Computers are spreading. Many organizations use them to store their data.
Ad hoc formats
hard to build general data management systems.
lots of duplicated effort.
The Standardization Dilemma:
Too restrictive: doesn’t fit users’ needs.
Too loose: back to ad-hoc solutions.

4. The Relational Format Codd (IBM Research 1970)
The fundamental question: What kinds of information do users need to represent?
Answered by 1st-order predicate logic! (Russell, Tarski).
The world consists of
Individuals/entities.
Relationships/links among them.

5. Database design

6. Gathering Specifications
The slides for this text are organized into chapters. This lecture covers Chapter 5.
Chapter 1: Introduction to Database Systems
Chapter 2: The Entity-Relationship Model
Chapter 3: The Relational Model
Chapter 4 (Part A): Relational Algebra
Chapter 4 (Part B): Relational Calculus
Chapter 5: SQL: Queries, Programming, Triggers
Chapter 6: Query-by-Example (QBE)
Chapter 7: Storing Data: Disks and Files
Chapter 8: File Organizations and Indexing
Chapter 9: Tree-Structured Indexing
Chapter 10: Hash-Based Indexing
Chapter 11: External Sorting
Chapter 12 (Part A): Evaluation of Relational Operators
Chapter 12 (Part B): Evaluation of Relational Operators: Other Techniques
Chapter 13: Introduction to Query Optimization
Chapter 14: A Typical Relational Optimizer
Chapter 15: Schema Refinement and Normal Forms
Chapter 16 (Part A): Physical Database Design
Chapter 16 (Part B): Database Tuning
Chapter 17: Security
Chapter 18: Transaction Management Overview
Chapter 19: Concurrency Control
Chapter 20: Crash Recovery
Chapter 21: Parallel and Distributed Databases
Chapter 22: Internet Databases
Chapter 23: Decision Support
Chapter 24: Data Mining
Chapter 25: Object-Database Systems
Chapter 26: Spatial Data Management
Chapter 27: Deductive Databases
Chapter 28: Additional Topics

7. Overview of Database Development
Requirements Analysis / Ideas
High-Level/Conceptual Database Design
Conceptual/Relational Database Schema
Dilbert on software requirements
Physical Database Design
 Similar to software development 2

8. Overview of Database Design
Conceptual design: (ER Model is used at this stage.)
What are the entities and relationships in the enterprise?
What information about these entities and relationships should we store in the database?
What are the integrity constraints or business rules that hold?
An ER Model can be represented pictorially (ER diagrams).
Can map an ER diagram into a relational schema.
Can also Unified Modelling Language (UML).
Pictorial Versions of 1st-order logic. 2

9. Entity-Relationship Models

10. Employees
ssn
name
lot
Entities
Entity: Real-world object distinguishable from other objects. An entity is described using a set of attributes.
Entity Set: A collection of similar entities. E.g., all employees.
All entities in an entity set have the same set of attributes. (Exception: ISA hierarchies, later.)
Each entity set has a key.
Each attribute has a domain.
A key can be a (minimal) set of attributes.
An entity set is like a class, an entity is like an instance. 3

11. Example: Entities ssn name lot 1000 Atishoo 1 2000 Maite 2 .... Cecile
violates attribute key constraint
Employees
ssn
name
lot

12. Relationships s
Users
Receiver
Sender id
lot
dname
budget
did
since
name
Works_In
Departments
Employees
ssn
Relationship: Association among two or more entities. E.g., Attishoo works in Pharmacy department.
Relationship Set: Collection of similar relationships.
An n-ary relationship set R relates n entity sets E1 ... En; each relationship in R involves entities e1, ..., en.
Same entity set could participate in different relationship sets, or in different “roles” in same set.
Consider showing Tarki’s workld demo. 4

13. Example: Relationshipss
Users
Receiver
Sender id
Relationships
....
lot
dname
budget
did
since
name
Works_In
Departments
Employees
ssn
Relationships
Attribute Values
<Attishoo, Pharmacy>
2000
<Cecile, Reception>
2010
....
2011
disallowed

14. Relation Math

15. Cartesian or Cross-Products
A tuple <a1,a2,…,an> is just a list with n elements in order.
A binary tuple <a,b> is called an ordered pair.
Given two sets A,B, we can form a new set A x B containing all ordered pairs <a,b> such that a is a member of A, b is a member of B.
In set notation: A x B = {<a,b> | a in A, b in B}.
Example: {1,2,3} x {x,y} = {<1,x>,<1,y>,<2,x>,<2,y>,<3,x>,<3,y>}

16. Exercise
Let A = {1,2,3}, B = {x,y}.
Compute B x A.
Compute A x A.

17. N-fold cross products
Given n sets A1, A2, …, An, the cross product A1 x A2 x A3 …x An is a new set defined by A1 x A2 x A3 …x An = {<a1, a2, a3, …, an>: a1 in A1, a2 in A2, …, an in An}.
Example: {1,2,3} x {x,y} x {1,2,3} has as members <1,x,1> and <1,y,3>.

18. Exercise Let A = {1,2,3}, B = {x,y}. Compute B x A x B.
Compute B x B x B.
If a set C has n members, how many are there in C x C? How many in C x C x C? In general, how many in C x C x …x C where we take k cross-products?
SQL implements these in one line.

19. The Cross Product Let E1, E2, E3 be three entity sets.
A relationship among E1, E2, E3 is a tuple in E1 x E2 x E3.
A relationship set is a set of relationships. So if R is a relationship set among E1, E2, E3, then R is a subset of E1 x E2 x E3.
Relationship set = subset of cross product.

20. Relationships
A relationship defines a relationship set given entity sets.
Informally, the relationship specifies which entities are related.
entityset 1
entityset 2
Students
Courses
Relationship
Enrolled
Relationship Set
enrolled (student,course)
subset
subset
entityset 1 x entityset 2
Students x Course

21. ER Diagrams and Relation Constraints

22. Relation Types
since
lot
name
ssn
dname
did
budget
Manages
Consider Works_In: An employee can work in many departments; a dept can have many employees.
In contrast, each dept has at most one manager, according to the key constraint on Manages.
Employees
Departments
Examples: 1-1 -> Dep, Manager
1-many -> Dep, Employees
Many-1 -> Employees, Dep Many-Many -> Customers, Items.
Who can come up with another example?
1-to-1
1-to Many
Many-to-1
Many-to-Many 6

23. ER Exercise 1
A university database contains information about professors (identified by SSN) and courses (identified by courseid). Professors teach courses; each of the following situations concerns the Teaches relationship. For each diagram, draw an ER diagram that describes it (assuming no further constraints hold).
Professors can teach the same course in several semesters, and only the most recent such offering needs to be recorded.
Professors can teach the same course in several semesters, and each offering must be recorded.

24. Participation Constraints
Must every department have a manager?
If so, this is a participation constraint: the participation of Departments in Manages is said to be total (vs. partial).
Every did value in Departments must appear in a tuple of the Manages relation.
since
since
name
name
dname
dname
ssn
lot
did
did
budget
budget
Employees
Manages
Departments
Works_In
since 8

25. Example: Participation Constraint
Manages
Relationship
since
<1000,100>
2000
<2000,200>
2001
participation constraint requires entry for did 300
Departments
did
dname
budget
100 CS 1M
200
Biology
10M
300
Engineering
100M

26. ER Exercise ctd.
Same scenario as before, where we need only the current semester. Draw E-R diagrams for the following constraints.
3. Every professor must teach some course.
4. Every professor teaches exactly one course.
5. Every professor teaches exactly one course, and every course must be taught by some professor.
Prepare solutions. in ex 2.2.

27. Weak Entities
A weak entity can be identified uniquely only by considering the primary key of another (owner) entity.
Owner entity set and weak entity set must participate in a one-to-many relationship set (one owner, many weak entities).
Weak entity set must have total participation in this identifying relationship set.
login
name
filename
Assignment
Students
sid
Submits
grade
submit time
Nice example: each student submits an assignment file, called solutions.pdf. This is a partial ID, works only in conjunction with student ID. 10

28. Example: Weak Entities
Filename
StudentID
assign1.pdf
1000
2000
....

29. ISA (is a) Hierarchies As in C++, or Java, attributes are inherited.
name
ISA (is a) Hierarchies
ssn
lot
Employees
As in C++, or Java, attributes are inherited.
If we declare A ISA B, every A entity is also considered to be a B entity.
hourly_wages
hours_worked
ISA
contractid
Hourly_Emps
Contract_Emps
Overlap constraints: Can Joe be an Hourly_Emps as well as a Contract_Emps entity? (Overlap Allowed/disallowed)
Covering constraints: Does every Employees entity also have to be an Hourly_Emps or a Contract_Emps entity? (Covering Yes/no)
Reasons for using ISA:
To add descriptive attributes specific to a subclass.
To identify entities that participate in a relationship.
Examples: hourly wages are specific to hourly employees
“motor vehicles” participates in “licenses” relationship; see also managers in slide “entity vs. relationship”.
What would you expect for overlap/covering constraints? 12

30. Reading Review Question
A ternary relationship
has three attributes
connects three entity sets
contains a key constraint.

31. Designing ER Diagrams
show Mondial ER diagaam: things can get complicated, better fix schema before moving data. See monial-abh.pdf for tabular schema.
Also: example from soccer from premier league. Example: entities = {match, players, teams}. Relationships: Plays(Team,Match), Home(Team, Match), PlaysIn(Player,Team), PlaysIn(Player,Match).

32. Conceptual Design Using the ER Model
Design choices:
Should a concept be modeled as an entity or an attribute? (e.g., address)
Should a concept be modeled as an entity or a relationship? (e.g., address)
Identifying relationships: Binary or ternary?
These are common for relational databases. 3

33. Entity vs. Attribute
Should address be an attribute of Employees or an entity (connected to Employees by a relationship)?
Depends upon the use we want to make of address information:
If we have several addresses per employee, address must be an entity. (Why?)
If the structure (city, street, etc.) is important, e.g., we want to retrieve employees in a given city, address must be modeled as an entity (since attribute values are atomic).
On atomic values: that’s the top of the object-oriented iceberg.
several addresses: (since attributes cannot be set-valued)

34. Entity vs. Attribute (Contd.)
from to
name
Employees
ssn
lot
dname
Works_In4 does not allow an employee to work in a department for two or more periods.
Similar to the problem of wanting to record several addresses for an employee: We want to record several values of the descriptive attributes for each instance of this relationship. Accomplished by introducing new entity set, Duration.
did
budget
Works_In4
Departments
dname
budget
did
name
Departments
ssn
lot
Employees
Works_In5
Duration
from to
General point: reify space and time points. 5

35. Duration Example Relationships <Attishoo, Pharmacy, 2000-2001>
dname
budget
did
name
Departments
ssn
lot
Employees
Works_In5
Duration
from to
Relationships
<Attishoo, Pharmacy, >
<Cecile, Reception, >
....
<Cecile, Reception, >

36. Entity vs. Relationship
First ER diagram OK if a manager gets a separate discretionary budget for each dept.
What if a manager gets a discretionary budget that covers all managed depts?
Redundancy: dbudget stored for each dept managed by manager.
Misleading: Suggests dbudget associated with department-mgr combination.
Manages2
name
dname
budget
did
Employees
Departments
ssn
lot
dbudget
since
Departments
dname
budget
did
Manages2
Employees
name
ssn
lot
since
Managers
dbudget
ISA
what are the differences between the two E-R diagrams? (Before showing the text.)
This fixes the
problem! 6

37. Binary vs. Ternary Relationships
age
pname
Dependents
Covers
name
ssn
lot
Employees
Policies
policyid
cost
Bad design
If each policy is owned by just 1 employee, and each dependent is tied to the covering policy, first diagram is inaccurate.
Beneficiary
age
pname
Dependents
policyid
cost
Policies
Purchaser
name
Employees
ssn
lot
Better design
what are the differences between the two E-R diagrams? (Before showing the text.)
For each dependent, exactly one policy of which the dependent is the beneficiary.
For each policy, there is exactly one employee who purchases it. 7

38. Binary vs. Ternary Example
Covers
Ternary Relationships <Employee,Policy,Dependent>
<Maite,100E,Adriana>
<Oliver,100E,Adriana>
<Juan,200A,Adriana>
Beneficiary
Purchases
Binary Relationships <Policy,Dependent>
<100E,Adriana>
<200A,Adriana>
Binary Relationships <Employee,Policy>
<Maite,100E>
<Oliver,100E>
<Juan,200A>

39. Binary vs. Ternary Relationships (Contd.)
Previous example: two binary relationships were better than one ternary relationship.
An example in the other direction: a ternary relation Contracts relates entity sets Parts, Departments and Suppliers, and has descriptive attribute qty.
No combination of binary relationships is an adequate substitute.
Need to be able to accommodate any triple -> no constraints to exploit in modelling. :
S “can-supply” P, D “needs” P, and D “deals-with” S does not imply that D has agreed to buy P from S.
How do we record qty? 9

40. Summary

41. Conceptual Design Conceptual design follows requirements analysis,
Provides a high-level description of data to be stored.
ER model popular for conceptual design
Expressive constructs.
Close to the way users think about their domains.
Basic constructs: entities, relationships, and attributes.
Some additional constructs: weak entities, ISA hierarchies.
There are many variations on ER model. 11

42. Constraints in the ER Model
Several kinds of integrity constraints can be expressed in the ER model.
key constraints.
participation constraints.
overlap/covering constraints for ISA hierarchies.
Some constraints (notably, functional dependencies) cannot be expressed in the ER model. (e.g., z = x + y)
Constraints play an important role in determining the best database design for an enterprise. 12

43. Common Design Choices ER design is subjective. Common choices include:
There are often many ways to model a given scenario
Analyzing alternatives can be tricky, especially for a large enterprise.
Common choices include:
Entity vs. attribute.
entity vs. relationship
binary or n-ary relationship
ISA hierarchies.
Resulting relational schema should be analyzed and refined further.
FD = functional dependency. Normalization: automatically simplify schema. These are not part of our course. 13