1 database systems ( 資料庫系統 ) september 24, 2014 lecture #2

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Database Systems( 資料庫系統 )

September 24, 2014Lecture #2

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Course Administration• http://www.csie.ntu.edu.tw/~winston/courses/dms/• HW #1 will be on the course homepage now

– It is due on Oct 8.• Next week reading:

– R&G Chapters 3 & 4.1~4.2

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TA Updates• TAs

– 謝朋儒 , Room 505, Monday 1:10~2:10 pm, email: r02944011@ntu.edu.tw

– 張人尹 , Room 506, Tuesday 1:10~2:10 pm, email: b99902105@gmail.com

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Possible Layered Architecture to DMS

Query Optimizationand Execution

Relational Operators

Files and Access Methods

Buffer Management

Disk Space Management

These layersmust considerconcurrencycontrol andcrash recovery

ApplicationsQueries (SQL)

SELECT S.nameFROM Students SWHERE S.sid = 123456

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Chapter 2Introduction to Database

Design

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Scenario

• Say if you are hired by iBeer Retailer as a computer consultant.

• iBeer wants you to design its database system. • How to design it?

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Database Design

• Step 1: Requirements Analysis– What application (e.g., queries, updates, ..) needs from the

database?– What data to store in the database?– What operations are most frequent and subject to performance

req.

• Step 2: Conceptual Database Design– Data to be stored and the constraints– Come up with the design: Entity-Relation (ER) model – Sketch the design using pictures called entity-relationship

diagrams.

• Step 3: Logical Database Design– Implement the design: relational data model– Easy to map ER diagrams into the relational data model (CH 3).

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Requirement Analysis• Requirement analysis:

– The Beer retailer wants to keep track of

• Beers on shelves • Beer manufacturers: [name & address]

• Conceptual database design– ER diagram

• Logical database design:– Relational model

Beer names

台灣啤酒

青島啤酒

台灣生啤酒

Beers ManfsManfBy

name name addr

Manufacturer’s names

Manufacturer’s addresses

台灣菸酒公賣局

台北市南昌路一段 4 號

青島啤酒廠 ??

Beer names Manufacturer's names

台灣啤酒 台灣菸酒公賣局 台灣生啤酒 台灣菸酒公賣局

青島啤酒 青島啤酒廠

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ER Model: Entity

• Proposed by Peter Chen (BS NTU EE ‘68) in 1976. • Entity: A real-world object distinguishable from other

objects (e.g., Joe). • An entity is described by a set of attributes.

– Each attribute has a domain of possible values (.e.g., 20-char. strings)

• Entity Set: a collection of similar entities (rectangle)• Each entity in an entity set is uniquely identified by a

key attribute.

Employees

ssnname

(Joe, Alice, ..)

(123: integer)

(‘Joe’: string)

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ER Model: Relationship

• Relationship: Association among two or more entities– Joe works in finance department.– A relationship must be uniquely identified by the participating entities,

without reference to the descriptive attributes. For example the pair <ssn, did>

• A relationship can have descriptive attributes.– Joe has worked in finance department since 5/2001.

• Relationship Set: Collection of similar relationships.

dname

budgetdid

sincename

Works_In DepartmentsEmployees

ssn

(5/2001)

(finance dept)(Joe)

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ER Model: Relationship (An Instance)

dname

budgetdid

sincename

Works_In DepartmentsEmployees

ssn

Joe

Alice

Mary

Peter

Finance

AccountingResearch

Legal

3/3/932/2/923/1/922/1/921/1/92Many-to-Many

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Ternary Relationship

dname

budgetdid

sincename

Works_In DepartmentsEmployees

ssn

capacityLocationsaddress

(Joe) (finance dept)

(Taipei)

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Roles in Relationship

Reports_To

name

Employees

supervisor

ssn

subordinate

(Roles)

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Key Constraints• Describe at most once (entity) relationship

– Manages relationship: each department has at most one manager (okay to have none).

– One department can appear at most once in Manages relationship set, also called one-to-many relation.

dname

budgetdidsincename

ssn

Employees DepartmentsManages

Joe

Alice

Mary

Peter

Finance

AccountingResearch

Legal

3/3/932/2/923/1/92

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More Key Constraints

1-to-1 1-to-Many Many-to-Many

Women Give Birth Babies

Married WomenMen Befriends WomenMen

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Participation Constraints

• Describe all (entity) participation relationship– Must every department have a manager?

• If yes, this is a participation constraint– All Departments entities must participate in the Manages

relationship set (total participation).

lotname dname

budgetdid

sincename dname

budgetdid

since

Manages

since

DepartmentsEmployees

ssn

Works_In

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Weak Entities• A weak entity can be identified uniquely only by

considering the key of another (owner) entity.– Pname = partial key (of the weak entity set, i.e.,

“Dependents”)– 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.

name

agepname

DependentsEmployees

ssn

Policy

cost

(Alicia) (2)

(Hao)

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ISA (`is a’) Hierarchies

• As in C++ and OO languages, attributes are inherited from superclass.

• A ISA B, every A entity is also considered to be a B entity. • Why using ISA?

• Add descriptive attributes specific (make sense) to a subclass.• Identify entities that make sense to a relationship (policy).

subclass entities

superclass entity

Contract_Emps

namessn

Employees

hourly_wagesISA

Hourly_Emps

contractid

hours_worked

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ISA (`is a’) Constraints

• Overlap constraints: Can Joe be an Hourly_Emps as well as a Contract_Emps entity? (Allowed/disallowed)

• Covering constraints: Does every Employees entity also have to be an Hourly_Emps or a Contract_Emps entity? (Yes/no)

Contract_Emps

namessn

Employees

hourly_wagesISA

Hourly_Emps

contractid

hours_worked

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Aggregation

• Create relationship set from relationship sets.

• Aggregation: relationship set turns into an entity set– So that they can

participate in (other) relationships.

budgetdidpid

started_on

pbudgetdname

until

DepartmentsProjects Sponsors

Employees

Monitors

namessn

since

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Design Guideline

1. Avoid redundancy.2. Don’t use an entity set when an

attribute will do.3. Limit the use of weak entity sets.

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Avoiding Redundancy

• Redundancy occurs when we say the same thing in two different ways.

• Redundancy is bad– wastes space – encourages inconsistency.

• The two instances of the same fact may become inconsistent if we change one and forget to change the other instance.

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Redundancy Example

Beers ManfsManfBy

name

This design states the manufacturer of a beer twice: as an attribute and as a related entity.

name

manf

addr

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Fix Redundancy

Beers ManfsManfBy

name

This design gives the address of each manufacturer exactly once.

name addr

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Example: Bad

Beers

name

This design repeats the manufacturer’s address once for each beer.Why is it bad?

•Manf updates its address.•Loses the address if there are temporarily no beers for a manufacturer.

manf manfAddr

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Exercise 2.2 (R-G Book)A university database contains information about

professors (identified by social security number) and courses (identified by courseid). Professors teach courses; each of the following situations concerns the Teaches relationship set. For each situation, draw an ER diagram that describes it.

• Professors can teach the same course in several semesters, and each offering must be recorded.

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• Professors can teach the same course in several semesters, and only the most recent such offering needs to be recorded.

• Every professor must teach some courses

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• Every professor teaches exactly one course (no more, no less)

• Every professor teaches exactly one course (no more, no less), and every course must be taught by some professor

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Exercise 2.3 (R-G Book)

• Professors have an SSN, a name, an age, a rank, and a research specialty.• Projects have a project number, a sponsor name (e.g., NSF), a starting

date, an ending date, and a budget.

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• Graduate students have an SSN, a name, an age, and a degree program• Each project is managed by exactly one professor (known as PI)• Each project is worked in by one or more professors (known as Co-PIs)• Each project is worked on by one or more graduate students (known as RAs)

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• When graduate students work on a project, a professor must supervise their work on the project. Graduate students can work on multiple projects, in which case they will have a potentially different supervisor for each one

• Departments have a department number, a department name, and a main office.• Department has a professor (known as Chairman) who runs the department.

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• Professors work in one or more departments, and for each department that they work in, a time percentage is associated with their job

• Graduate students have one major department in which they are working on their degree.

• Each graduate student must have another, more senior graduate student as an advisor.

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Summary

• ER model is popular for conceptual design– Sketch the design of a database informally using pictures

• Basic constructs in ER model: – entities, relationships, and attributes (of entities and

relationships).

• Some additional constructs: – weak entities, ISA hierarchies, and aggregation.

• Several kinds of integrity constraints:– key constraints, participation constraints, and

overlap/covering constraints for ISA hierarchies.

• Design guideline in ER model

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Entity Sets Versus Attributes

• Modeling a concept with a new entity set should satisfy at least one of the following conditions:

– It is more than the name of something; it has at least one nonkey attribute.

or– It is the “many” in a many-one or many-

many relationship.

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Example: Okay

Beers ManfsManfBy

name

•Manfs deserves to be an entity set because of the nonkey attribute addr.•Beers deserves to be an entity set because it is the “many” of the many-one relationship ManfBy.

name addr

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Example: Beers Entity not Needed

Beers ManfsManfBy

name

•Beers can be an attribute rather than an entity.

name addr

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Example: Okay

Beers

name

There is no need to make the manufacturer an entity set, because we record nothing about manufacturers besides their name.

manf

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Example: Bad

Beers ManfsManfBy

name

Since the manufacturer is nothing but a name, and is not at the “many” end of any relationship, it should not be an entity set.

name

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Don’t Overuse Weak Entity Sets

• Beginning database designers often doubt that anything could be a key by itself.– They make all entity sets weak, supported by all

other entity sets to which they are linked.

• In reality, we usually create unique ID’s for entity sets.– Examples include social-security numbers,

automobile VIN’s etc.

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When Do We Need Weak Entity Sets?

• The usual reason is that there is no global authority capable of creating unique ID’s.

• Example: it is unlikely that there could be an agreement to assign unique player numbers across all football teams in the world.