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Chapter 2

Chapter 2. The Relational Database Model Database Systems: Design, Implementation, and Management, Fifth Edition, Rob and Coronel. In this chapter, you will learn: . That the relational database model takes a logical view of data

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Chapter 2

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  1. Chapter 2 The Relational Database Model Database Systems: Design, Implementation, and Management, Fifth Edition, Rob and Coronel

  2. In this chapter, you will learn: • That the relational database model takes a logical view of data • That the relational database model’s basic components are entities and their attributes, and relationships among entities • How entities and their attributes are organized into tables • About relational database operators, the data dictionary, and the system catalog • How data redundancy is handled in the relational database model • Why indexing is important Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  3. Logical View of Data • 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 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  4. Logical View of Data (con’t.) • 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 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  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 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  6. Table Characteristics (con’t.) • 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 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  7. Keys • One or more attributes that determine other attributes • Key attribute • Composite key • Full functional dependence • Entity integrity • Uniqueness • No ‘null’ value in key Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  8. Example Tables Figure 2.1 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  9. Simple Relational Database Figure 2.2 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  10. Keys (con’t.) • Superkey • Uniquely identifies each entity • Candidate key • Minimal superkey • Primary key • Candidate key to uniquely identify all other attributes in a given row • Secondary key • Used only for data retrieval • Foreign key • Values must match primary key in another table Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  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 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  12. Relational Database Operators • Relational algebra determines table manipulations • Key operators • SELECT • PROJECT • JOIN • Other operators • INTERSECT • UNION • DIFFERENCE • PRODUCT • DIVIDE Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  13. Union Combines all rows Figure 2.5 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  14. Intersect Yields rows that appear in both tables Figure 2.6 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  15. Difference Yields rows not found in other tables Figure 2.7 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  16. Product Yields all possible pairs from two tables Figure 2.8 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  17. Select Yields a subset of rows based on specified criterion Figure 2.9 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  18. Project Yields all values for selected attributes Figure 2.10 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  19. Join Information from two or more tables is combined Figure 2.11 Figure 2.14 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  20. Natural Join Process • Links tables by selecting rows with common values in common attribute(s) • Three-stage process • Product creates one table • Select yields appropriate rows • Project yields single copy of each attribute to eliminate duplicate columns Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  21. Other Joins • EquiJOIN • Links tables based on equality condition that compares specified columns of tables • Does not eliminate duplicate columns • Join criteria must be explicitly defined • Theta JOIN • EquiJOIN that compares specified columns of each table using operator other than equality one • Outer JOIN • Matched pairs are retained • Unmatched values in other tables left null • Right and left Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  22. Divide Requires user of single-column table and two-column table Figure 2.17 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  23. Data Dictionary and System Catalog • Data dictionary • Provides detailed account of all tables found within database • Metadata • Attribute names and characteristics • System catalog • Detailed data dictionary • System-created database • Stores database characteristics and contents • Tables can be queried just like any other tables • Automatically produces database documentation Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  24. Relationships within Relational Database • Relationship classifications • 1:1 • 1:M • M:N • E-R Model • ERD Maps E-R model • Chen • Crow’s Feet Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  25. ERD Symbols • Rectangles represent entities • Diamonds represent the relationship(s) between the 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 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  26. Example 1:M Relationship Figure 2.18 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  27. Example 1:M Relationship Figure 2.20 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  28. Example M:N Relationship Figure 2.23 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  29. Example M:N Relationship Figure 2.24 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  30. Converting M:N Relationship to Two 1:M Relationships Figure 2.25 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  31. Converting M:N Relationship to Two 1:M Relationships (con’t.) Figure 2.26 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  32. Converting M:N Relationship to Two 1:M Relationships (con’t.) Figure 2.27 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  33. Converting M:N Relationship to Two 1:M Relationships (con’t.) Figure 2.28 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  34. Data Redundancy Revisited • Foreign keys can reduce redundancy • Some redundancy is desirable • Called controlled redundancy • Speed • Information requirements Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

  35. Indexes • Points to location • Makes retrieval of data faster Figure 2.31 Database Systems: Design, Implementation, & Management, 5th Edition, Rob & Coronel

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