The Relational Database Model – some relations you might want to avoid!!!

2 Our HERO!!!

3 Logical vs. Physical Relational Database Designer focuses on logical representation rather than physical Use of table advantageous Structural and data independence Related records stored in independent tables Logical simplicity Allows for more effective design strategies

4 Logical View of Data Entities and Attributes Entity is a person, place, event, or thing about which data is collected Attributes are characteristics of the entity Tables Holds related entities or entity set Also called relations Comprised of rows and columns

5 Table Characteristics Two-dimensional structure with rows and columns Rows (tuples) represent single entity Columns represent attributes Row/column intersection represents single value Tables must have an attribute to uniquely identify each row Column values all have same data format Each column has range of values called attribute domain Order of the rows and columns is immaterial to the DBMS

6 Keys One or more attributes that determine other attributes Key attribute Composite key Full functional dependence Entity integrity Uniqueness No ‘null’ value in key

7 Keys SuperkeyUniquely identifies each entity Candidate keyMinimal superkey Primary keyCandidate key to uniquely identify all other attributes in a given row – used to uniquely identify each record Secondary keyUsed only for data retrieval Foreign keyValues must match primary key in another table

8 Example Tables Figure 2.1

9 Comparison Operators … A and B - Intersect A OR B –UNION: all of A (including yellow, gray and purple) all of B (including aqua, and purple and gray) C and B

10 Simple Relational Database Figure 2.2

11 Integrity Rules Entity integrity Ensures all entities are unique Each entity has unique key Referential integrity Foreign key must have null value or match primary key values Makes it impossible to delete row whose primary key has mandatory matching foreign key values in another table

12 Relationships within Relational Database Relationship classifications 1:1 1:M M:N E-R Model ERD Maps E-R model Chen Crow’s Feet

13 ERD Symbols Rectangles represent entities “1” side of relationship Number 1 in Chen Model Bar crossing line in Crow’s Feet Model “ Many” relationships –Letter “M” and “N” in Chen Model –Three pronged “Crow’s foot” in Crow’s Feet Model

14 Define Relationship Determine relationship using this terminology: (i.e. relationship between student and dorm rooms) 1 of A is related to X (1 or many) of B i.e. 1 student is assigned to 1 dorm room 1 of B is related to X (1 or many) of A i.e. 1 dorm room is assigned to many students The decision will be as follows: 1:1 1 of A is related to 1 of B 1 of B is related to 1 of A 1:M 1 of A is related to many of B 1 of B is related to 1 of A M:N 1 of A is related to many of B 1 of B is related to many of A

15 Relationship Resolution 1 to 1 (1:1) Assumed that the entity is just another attribute for that table. Add entity as another attribute to existing table

16 Relationship Resolution 1 to Many (1:M) The primary key of the one side is duplicated as the foreign key on the many side. RULE!!!! foreign key ALWAYS goes on Many side. Names of the primary key and the foreign key do not need to match - only the data type needs to be the same. Of course, the values of the data stored in the field must match as well or there can not be a join.

17 Relationship Resolution M:N 1.Resolve the M:N relationship into two 1:M relationships Create an associative entity (AKA composite entity or bridge entity) with primary keys (PK) of two entities as foreign keys (FK) Associative entity is many side of both 1:M relationships. FK ALWAYS goes on many side of relationship -> Associative entity ALWAYS many side of the relationship 2.If combination of 2 FKs unique, can use as PK of the associative entity. In this case, since PK be composed of 2 PKs, called composite key. 3.If combination of 2 FKs NOT unique, leave 2 FKs in associative entity. Create new PK for associative entity.

18 Comparison of Modeling Techniques 1:1 relationship Chen Infinity Crow’s Feet Car Steering Wheel 11 Car Steering Wheel 11 Car Steering Wheel 11

19 Comparison of Modeling Techniques 1:M relationship Chen Infinity Crow’s Feet Car Tire 1 ∞ Car Tire 1 Car Tire 1M

20 Example 1:M Relationship Figure 2.20

21 Comparison of Modeling Techniques M:N relationship (yes it seems it should be M:M but…) Chen Infinity Crow’s Feet Class Student ∞ Class Student Class Student M ∞ N

22 Example M:N Relationship Figure 2.24

23 Data Redundancy Revisited Foreign keys can reduce redundancy Some redundancy is desirable Called controlled redundancy Speed Information requirements

24 Points to location Makes retrieval of data faster Indexes Figure 2.31