Database Systems Entity-Relationship (ER) Modeling

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1 Database Systems Entity-Relationship (ER) Modeling
Gergely Lukács Pázmány Péter Catholic University Faculty of Information Technology Budapest, Hungary

2 Overview Entity-Relationship (ER) Model
Converting ER-Model to relational Schema Extended ER (EER) Model SQL Developer, Data Modeler

3 Data model Collection of concepts – e.g., data types, relationships, constrains – that can be used to describe the structure of a database Types of data models Conceptual data model: high-level concepts, close to users' understanding of the problem; e.g., (E)ER model, UML (Unified Modeling Language) Implementation/Logical data model: concepts understandable for users, but also considering DBMS; e.g., relational model, objectrelational model (s. later, useful e.g., for geographic data, XML), hierarchical model, network model (historical) Physical data model: low level concepts that describe the data’s physical storage details

4 Modeling A database can be modeled as: a collection of entities,
relationship among entities. An entity is an object that exists and is distinguishable from other objects. Example: specific person, company, event, plant Entities have attributes Example: people have names and addresses An entity set is a set of entities of the same type that share the same properties. Example: set of all persons, companies, trees, holidays 4

5 Entity Sets instructor and student
instructor_ID instructor_name student-ID student_name 5

6 Relationship Sets A relationship is an association among several entities Example: (Peltier) advisor (Einstein) student entity relationship instructor entity A relationship set is a mathematical relation among n  2 entities, each taken from entity sets {(e1, e2, … en) | e1  E1, e2  E2, …, en  En} where (e1, e2, …, en) is a relationship Example: (44553,22222)  advisor 6

7 Relationship Set advisor
7

8 Attributes of Relationship Sets
An attribute can also be property of a relationship set. Depending on the ER-notation For instance, the advisor relationship set between entity sets instructor and student may have the attribute date which tracks when the student started being associated with the advisor 8

9 Degree of a Relationship Set
Binary relationship involves two entity sets (degree two). most relationship sets in a database system are binary. Relationships between more than two entity sets are rare Example: students work on research projects under the guidance of an instructor. relationship proj_guide is a ternary relationship between instructor, student, and project Often replaced by entity-sets and binary relationship sets 9

10 Attributes Simple and composite attributes.
An entity is represented by a set of attributes, that is descriptive properties possessed by all members of an entity set. Example: instructor = (ID, name, street, city, salary ) course= (course_id, title, credits) Domain – the set of permitted values for each attribute Attribute types: Single-valued and multivalued attributes Example: multivalued attribute: phone_numbers Derived attributes Can be computed from other attributes Example: age, given date_of_birth Simple and composite attributes. 10

11 Composite Attributes 11

12 Relationship Cardinality
Express the number of entities to which another entity can be associated via a relationship set. Cardinalities for binary relationship sets: One to one One to many Many to one Many to many + Optional left and/or right 12

13 Relationship Cardinality
One to one (One to zero or one) One to many Note: Some elements in A and B may not be mapped to any elements in the other set 13

14 Mapping Cardinalities
Many to one Many to many (Many to zero or many) Note: Some elements in A and B may not be mapped to any elements in the other set 14

15 Primary Key of an Entity Set
Minimal set of uniquely identifying attributes 15

16 E-R Diagrams Rectangles represent entity sets.
Diamonds represent relationship sets. Attributes listed inside entity rectangle Underline indicates primary key attributes 16

17 Entity With Composite, Multivalued, and Derived Attributes
17

18 Relationship Sets with Attributes
18

19 Roles Entity sets of a relationship need not be distinct
Each occurrence of an entity set plays a “role” in the relationship The labels “course_id” and “prereq_id” are called roles. 19

20 Cardinality Constraints
Notation for cardinality constraints One: directed line:  Many: undirected line: — 20

21 One-to-One Relationship
one-to-one relationship between an instructor and a student an instructor is associated with at most one student via advisor and a student is associated with at most one instructor via advisor 21

22 One-to-Many Relationship
one-to-many relationship between an instructor and a student an instructor is associated with several (including 0) students via advisor a student is associated with at most one instructor via advisor 22

23 Many-to-Many Relationship
An instructor is associated with several (possibly 0) students via advisor A student is associated with several (possibly 0) instructors via advisor 23

24 Participation of an Entity Set in a Relationship Set
Total participation (indicated by double line): every entity in the entity set participates in at least one relationship in the relationship set E.g., participation of section in sec_course is total every section must have an associated course Partial participation: some entities may not participate in any relationship in the relationship set Example: participation of instructor in advisor is partial 24

25 E-R Diagram with a Ternary Relationship
Complications… Can be replaced with a new entity set + binary relationships 25

26 Weak Entity Sets An entity set that does not have a primary key is referred to as a weak entity set. The existence of a weak entity set depends on the existence of a identifying entity set It must relate to the identifying entity set via a total, one-to-many relationship set from the identifying to the weak entity set Identifying relationship depicted using a double diamond The discriminator (or partial key) of a weak entity set is the set of attributes that distinguishes among all the entities of a weak entity set. The primary key of a weak entity set is formed by the primary key of the strong entity set on which the weak entity set is existence dependent, plus the weak entity set’s discriminator. 26

27 Weak Entity Sets (Cont.)
We underline the discriminator of a weak entity set with a dashed line. We put the identifying relationship of a weak entity in a double diamond. Primary key for section – (course_id, sec_id, semester, year) 27

28 E-R Diagram for a University Enterprise
28

29 Converting ER-Model to relational SCHEMA

30 Reduction to Relation Schemas
Entity sets and relationship sets can be expressed uniformly as relation schemas that represent the contents of the database. A database which conforms to an E-R diagram can be represented by a collection of schemas. For each entity set and relationship set there is a unique schema that is assigned the name of the corresponding entity set or relationship set. Each schema has a number of columns (generally corresponding to attributes), which have unique names. 30

31 Representing Entity Sets With Simple Attributes
A strong entity set reduces to a schema with the same attributes student(ID, name, tot_cred) A weak entity set becomes a table that includes a column for the primary key of the identifying strong entity set section ( course_id, sec_id, sem, year ) In practice, most often surrogate keys are chosen. Also, the key of the relation of the weak entity set often doesn’t contain the key of the strong entity set (foreign key with cascade option useful, though) 31

32 Representing Relationship Sets
Many-to-one and one-to-many relationship sets can be represented by adding an extra attribute to the “many” side, containing the primary key of the “one” side Optionality – (NOT) NULL Additional atributes of the relationship – additional attributes beside the foreign key Example: inst_dept: add an attribute dept_name to the schema arising from entity set instructor 32

33 Representing Relationship Sets (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 33

34 Representing Relationship Sets cont.
A many-to-many relationship set is represented as a schema with attributes for the primary keys of the two participating entity sets, and any descriptive attributes of the relationship set. Example: schema for relationship set advisor advisor = (s_id, i_id) 34

35 Composite and Multivalued Attributes
Composite attributes are flattened out by creating a separate attribute for each component attribute Example: given entity set instructor with composite attribute name with component attributes first_name and last_name the schema corresponding to the entity set has two attributes name_first_name and name_last_name Prefix omitted if there is no ambiguity Ignoring multivalued attributes, extended instructor schema is instructor(ID, first_name, middle_initial, last_name, street_number, street_name, apt_number, city, state, zip_code, date_of_birth) 35

36 Composite and Multivalued Attributes
A multivalued attribute M of an entity E is represented by a separate schema EM Schema EM has attributes corresponding to the primary key of E and an attribute corresponding to multivalued attribute M Example: Multivalued attribute phone_number of instructor is represented by a schema: inst_phone= ( ID, phone_number) Each value of the multivalued attribute maps to a separate tuple of the relation on schema EM For example, an instructor entity with primary key and phone numbers and maps to two tuples: (22222, ) and (22222, ) 36

37 Design Issues Use of entity sets vs. relationship sets Possible guideline is to designate a relationship set to describe an action that occurs between entities 37

38 Design Issues Binary versus n-ary relationship sets
It is possible to replace any nonbinary (n-ary, for n > 2) relationship set by a number of distinct binary relationship sets. Many design tools do not support n-ary (n>2) relationships. n-ary relationship set may show more clearly that several entities participate in a single relationship (depends on personal preferences) 38

39 Extended ER Features

40 Inheritence Specialisation: Top-down design process; we designate subgroupings within an entity set that are distinctive from other entities in the set. These subgroupings become lower-level entity sets that have attributes or participate in relationships that do not apply to the higher-level entity set. Depicted by a triangle component (E.g., instructor “is a” person). Generalisation: A bottom-up design process – combine a number of entity sets that share the same features into a higher-level entity set. Attribute inheritance – a lower-level entity set inherits all the attributes and relationship participation of the higher-level entity set to which it is linked. 40

41 Alternative names IS-A relationship superclass - subclass relationship
41

42 Inheritence Example 42

43 Representing Inheritence in Relational Model: Method 1
Table per Concrete Class/Table for Each Entity Form a relation (table) for the higher-level entity set, common attributes + type (discriminator) Form a relation (table) for each lower-level entity set, include primary key of higher-level entity set and local attributes relation attribute person ID, type, name, street, city student ID, tot_cred employee ID, salary + simple query for higher-level entity set + understandable relational schema (attributes clearly distinquishible + easy modification of schema - join required (expensive) 43

44 Representing Inheritence in Relational Model: Method 2
Table per Subclass/Table per Child Form a relation (table) for each entity set with all local and inherited attributes relation attributes student ID, name, street, city, tot_cred employee ID, name, street, city, salary + no join for single subclass querying Set operation (union) for superclass Superclass not subclass? Overlapping subclasses? (both student and employee) Redundant attributes Foreign keys? 44

45 Representing Inheritence in Relational Model: Method 3
Table per Class Hierarchy/Single Table Form a single relation (table) with all local and inherited attributes + type (or discriminator) attribute schema attributes person ID, type, name, street, city, tot_cred , salary + no joins required + no unions required Schema hard to understand Wasting of space 45

46 Alternative notations

47 Summary of Symbols Used in E-R Notation
47

48 Symbols Used in E-R Notation (Cont.)
48

49 Alternative ER Notations
Chen, IDE1FX, … 49

50 Cardinality Constraints
Alternative notations Crow's Foot notation Cardinalities by numbers and * 50

51 Alternative ER Notations
51

52 UML UML: Unified Modeling Language
UML has many components to graphically model different aspects of an entire software system UML Class Diagrams correspond to E-R Diagram, but several differences. 52

53 ER vs. UML Class Diagrams
*Note reversal of position in cardinality constraint depiction 53

54 UML Class Diagrams (Cont.)
Binary relationship sets are represented in UML by just drawing a line connecting the entity sets. The relationship set name is written adjacent to the line. The role played by an entity set in a relationship set may also be specified by writing the role name on the line, adjacent to the entity set. The relationship set name may alternatively be written in a box, along with attributes of the relationship set, and the box is connected, using a dotted line, to the line depicting the relationship set. 54

55 Schema design – practical issues
1 55

56 E-R Design Decisions The use of an attribute or an entity set to represent an object. Whether a real-world concept is best expressed by an entity set or a relationship set. The use of specialization/generalization – contributes to modularity in the design. The use of a ternary relationship versus a pair of binary relationships. The use of a strong or weak entity set. 56

57 Natural key vs surrogate key
Natural key: attribute(s) with meaning E.g. social security number + attribute exists already + readable for humans - maintenance (changing requirements, foreign keys!!) Surrogate key: key with no (business) meaning incremental keys Universally unique identifiers (UUIDs) 42a4e e a5d5c51b + maintenance (changing requirements) + uniform (common strategy for all tables) + performance (compact data type) + compatible (many software systems, e.g., object-relational mappers) Strategy? (surrogate, eventually natural key for lookup tables ?)

58 Naming conventions Names of entities/tables, attributes, primary and foreign keys Abbreviations (20-30) (Oracle names: max 30 characters) Attribute groups Order of attributes and attribute groups Key lookup tables, association tables Color conventions for diagrams

59 Oracle SQL Developer: Data Modeler
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60 Oracle SQL Developer: Data Modeler
Logical model (~ER model)

61 Information engineering notation
relationships – lines only Information engineering notation only binary relationships IsA (inheritance) Simple, single-valued attributes only relationships without attributes n:m relationship optional identifying relationship (~ weak entity)

62 Barker notation

63 Bachman notation

64 Relational model

65 n:m relationship association table (1:m relationship foreign key)
names converted (naming rules) Fwd engineering strategy: single table

66 Forward engineering strategy: one table per child

67 Forward engineering strategy: table for each entity

68 Design rules

69 DDL generation

70 Reverse engineering

71 FK: ON DELETE CASCADE FK: ON DELETE SET NULL UNIQUE KEY

72 Készítse el az alábbi leírás alapján egy adatbázis logikai modelljét (az ER diagram megfelelője az Oracle SQL Developer, Data Modeler-ében; ennek az eszköznek a lehetőségeit és az "Information Engineering" notációját használja). (40%) Második lépésben, a logikai modell alapján, készítse el a relációs modellt is (az SQL developer notációját használva, grafikusan ábrázolva). A recepteknél szereplő ISA kapcsolatot (öröklődést) közös egy táblával fordítsa le ("Single table ") Pontosan jelölje az elsődleges és a külső kulcsokat (tábla, attribútum) (45%) Mutassa be külön diagramon (ill. diagramrészleten), a másik két "forward engineering strategy" ("Table for each entity " ill. "Table per Child") alkalmazását. (15%). Minden részfeladatnál írjon magyarázatot, ha pl. a követelményeket pontosítani kellett, kompromisszumos megoldást kellett választani vagy más miatt nem egyértelmű a megoldás.

73 Receptgyűjtemény főzéshez (Háttér: Community Supported Agriculture, CSA)
A recepteket jellemzi a nevük, a nehézségi fokuk, az elkészítési idő és az adagok száma. Kétféle recept van: amelyik elkészítési módja szöveges formában és amelyiké hangfájl formában érhető el. Az előbbit a fentieken túl egy szöveges leírás, az utóbbit pedig a hangfájl neve, hossza és a felvételt készítő személy neve jellemzi. A szöveges formában elérhető receptekhez tartoznak elkészítési lépések is: ezeket a munkafolyamat leírása és a lépéshez szükséges idő jellemzi. Ezen felül a lépéseknek van egy sorszáma is (értelemszerűen receptenként). A mértékegységeket jellemzi a nevük és egy szöveges leírás. A lehetséges nyersanyagokat jellemzi a nevük és a típusuk. (A „lehetséges” szó hangsúlyos: a receptektől függetlenül is beszélhetünk nyersanyagokról.) Egy recepthez többféle hozzávalóra is szükség lehet. A hozzávalók megadásánál a nyersanyag mellett a mennyiséget, a mennyiség mértékegységét valamint egy megjegyzést kell ill. lehet megadni. A szövegesen megadott receptek lépéseihez is hozzá vannak rendelve a hozzávalók mennyiséggel ill. mértékegységgel. Különféle receptkategóriák léteznek (pl. leves, főétel,…). Ezeket jellemzi a nevük és egy leírás. A kategóriák hierarchiát képeznek. Egy recept pontosan egy kategóriába tartozik. Különféle egészségügyi kockázatok vannak. Ezeket jellemzi a nevük és egy szöveges leírás. Egy recept többféle egészségügyi kockázat esetén is ellenjavallt lehet, és egy egészségügyi kockázat esetén több recept is ellenjavalt lehet. Az adatbázisban szereplő valamennyi entitástípushoz egy mesterségesen képzett, jelentés nélküli azonosító tartozik.

74 Receptgyűjtemény főzéshez (Háttér: Community Supported Agriculture, CSA)
A recepteket jellemzi a nevük, a nehézségi fokuk, az elkészítési idő és az adagok száma. Kétféle recept van: amelyik elkészítési módja szöveges formában és amelyiké hangfájl formában érhető el. Az előbbit a fentieken túl egy szöveges leírás, az utóbbit pedig a hangfájl neve, hossza és a felvételt készítő személy neve jellemzi. A szöveges formában elérhető receptekhez tartoznak elkészítési lépések is: ezeket a munkafolyamat leírása és a lépéshez szükséges idő jellemzi. Ezen felül a lépéseknek van egy sorszáma is (értelemszerűen receptenként). A mértékegységeket jellemzi a nevük és egy szöveges leírás. A lehetséges nyersanyagokat jellemzi a nevük és a típusuk. (A „lehetséges” szó hangsúlyos: a receptektől függetlenül is beszélhetünk nyersanyagokról.)

75 Egy recepthez többféle hozzávalóra is szükség lehet
Egy recepthez többféle hozzávalóra is szükség lehet. A hozzávalók megadásánál a nyersanyag mellett a mennyiséget, a mennyiség mértékegységét valamint egy megjegyzést kell ill. lehet megadni. A szövegesen megadott receptek lépéseihez is hozzá vannak rendelve a hozzávalók mennyiséggel ill. mértékegységgel. Különféle receptkategóriák léteznek (pl. leves, főétel,…). Ezeket jellemzi a nevük és egy leírás. A kategóriák hierarchiát képeznek. Egy recept pontosan egy kategóriába tartozik. Különféle egészségügyi kockázatok vannak. Ezeket jellemzi a nevük és egy szöveges leírás. Egy recept többféle egészségügyi kockázat esetén is ellenjavallt lehet, és egy egészségügyi kockázat esetén több recept is ellenjavalt lehet. Az adatbázisban szereplő valamennyi entitástípushoz egy mesterségesen képzett, jelentés nélküli azonosító tartozik.