1. ©Silberschatz, Korth and Sudarshan2.1Database System Concepts 在 E-R 圖中的符號

2. ©Silberschatz, Korth and Sudarshan2.2Database System Concepts 在 E-R 圖中的符號

3. ©Silberschatz, Korth and Sudarshan2.3Database System Concepts 另一種 E-R 符號

4. ©Silberschatz, Korth and Sudarshan2.4Database System Concepts UML UML: 統一模型語言 UML 是針對軟體系統中不同元件的規格所提出的一個標準 UML 類別圖類似與 E-R 圖, 在這個章節的後面我們會描述類別圖的 幾個特性, 以及他們是如何和 E-R 圖建立關係

5. ©Silberschatz, Korth and Sudarshan2.5Database System Concepts實體集合與屬

6. ©Silberschatz, Korth and Sudarshan2.6Database System Concepts UML Class Diagrams (Contd.) Entity sets are shown as boxes, and attributes are shown within the box, rather than as separate ellipses in E-R diagrams. 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. Non-binary relationships drawn using diamonds, just as in ER diagrams

7. ©Silberschatz, Korth and Sudarshan2.7Database System Concepts 使用 UML 類別圖符號的說明 *Note reversal of position in cardinality constraint depiction *Generalization can use merged or separate arrows independent of disjoint/overlapping overlapping disjoint

8. ©Silberschatz, Korth and Sudarshan2.8Database System Concepts UML Class Diagrams (Contd.) 基數條件限制跟在 E-R 圖中所弋表恴思相同, 是以 l..h 的形式呈現, 其中 l 和 h 分別代表一個實體可以參與關係的最小量以及最大量. 注意 : 條件限制的位置正好和在 E-R 圖中的條件限制位置完全反向. 在 E2 邊的條件是 0..*, 而 E1 邊的條件是 0..1, 所代表的意思是每一個 E2 的 實體最多只可以參與一個關係, 而每一個 E1 實體則可以參與很多個關係 ; 換句話說, 從 E2 到 E1 的關係是多對一關係. 個別的數值可以寫在邊 ; 上在邊上的數值 1 所代表的涵意指的是 1..1, 而 * 代表的是 0..*.

9. ©Silberschatz, Korth and Sudarshan2.9Database 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.

10. ©Silberschatz, Korth and Sudarshan2.10Database System Concepts Representing Entity Sets as Tables A strong entity set reduces to a table with the same attributes.

11. ©Silberschatz, Korth and Sudarshan2.11Database 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)

12. ©Silberschatz, Korth and Sudarshan2.12Database 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

13. ©Silberschatz, Korth and Sudarshan2.13Database 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

14. ©Silberschatz, Korth and Sudarshan2.14Database 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

15. ©Silberschatz, Korth and Sudarshan2.15Database 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).

16. ©Silberschatz, Korth and Sudarshan2.16Database 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

17. ©Silberschatz, Korth and Sudarshan2.17Database 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

18. ©Silberschatz, Korth and Sudarshan2.18Database 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

19. ©Silberschatz, Korth and Sudarshan2.19Database 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

20. End of Chapter 2

21. ©Silberschatz, Korth and Sudarshan2.21Database System Concepts 習題 2.10 的 E-R 圖

22. ©Silberschatz, Korth and Sudarshan2.22Database System Concepts 習題 2.15 的 E-R 圖

23. ©Silberschatz, Korth and Sudarshan2.23Database System Concepts 習題 2.22 的 E-R 圖

24. ©Silberschatz, Korth and Sudarshan2.24Database System Concepts 習題 2.10 的 E-R 圖

25. ©Silberschatz, Korth and Sudarshan2.25Database System Concepts Existence Dependencies If the existence of entity x depends on the existence of entity y, then x is said to be existence dependent on y.  y is a dominant entity (in example below, loan)  x is a subordinate entity (in example below, payment) loan-payment payment loan If a loan entity is deleted, then all its associated payment entities must be deleted also.