Relational databases.pdf
- 1. Relational Databases The Logical view of data
- 2. 2 Objectives In this chapter, students will learn: • That the relational database model offers a logical view of data • About the relational model’s basic component: relations • That relations are logical constructs composed of rows (tuples) and columns (attributes) • That relations are implemented as tables in a relational DBMS
- 3. 3 Objectives (cont’d.) • 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
- 4. 4 A Logical View of Data • Relational model – View data logically rather than physically • Table – Structural and data independence – Resembles a file conceptually • Relational database model is easier to understand than hierarchical and network models
- 5. 5 Tables and Their Characteristics • Logical view of relational database is based on relation – Relation thought of as a table • Table: two-dimensional structure composed of rows and columns – Persistent representation of logical relation • Contains group of related entities (entity set)
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- 8. 8 Keys • Each row in a table must be uniquely identifiable • Key: one or more attributes that determine other attributes – Key’s role is based on determination • If you know the value of attribute A, you can determine the value of attribute B – Functional dependence • Attribute B is functionally dependent on A if all rows in table that agree in value for A also agree in value for B
- 9. Types of Keys • Superkey -A set of keys that can be used to uniquely identify any row or tuple in the table. • Candidate key -A minimal set of keys that can be used to identify a tuple in a table. -A superkey without unnecessary attributes. • Composite key -Is a key that consists of more than one attribute and can be used to uniquely identity a tuple in the table. 10
- 10. 10 Types of Keys • Alternate key -A candidate key that has not be chosen as the primary key. • Primary Key -Is any attribute that is used to uniquely identify a tuple or a row in a table. • Foreign key -is an attribute or column in a table that references the primary key of another table.
- 11. 11 Types of Keys (cont’d.) • Entity integrity – Each row (entity instance) in the table has its own unique identity and the PK doesn’t accept NULL values. • Nulls – No data entry – Not permitted in primary key – Should be avoided in other attributes
- 12. 12 Types of Keys (cont’d.) – Can represent: • An unknown attribute value • A known, but missing, attribute value • A “not applicable” condition – Can create problems when functions such as COUNT, AVERAGE, and SUM are used – Can create logical problems when relational tables are linked
- 13. 13 Types of Keys (cont’d.) • Controlled redundancy – Makes the relational database work – Tables within the database share common attributes • Enables tables to be linked together – Multiple occurrences of values not redundant when required to make the relationship work – Redundancy exists only when there is unnecessary duplication of attribute values
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- 15. 15 Types of Keys (cont’d.) • Foreign key (FK) – An attribute whose values match primary key values in the related table • Referential integrity – FK contains a value that refers to an existing valid tuple (row) in another relation • Secondary key – Key used strictly for data retrieval purposes
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- 17. 17 Integrity Rules • Many RDBMs enforce integrity rules automatically • Safer to ensure that application design conforms to entity and referential integrity rules • Designers use flags to avoid nulls – Flags indicate absence of some value
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- 20. 20 Relational Set Operators • Relational algebra – Defines theoretical way of manipulating table contents using relational operators – Use of relational algebra operators on existing relations produces new relations: • SELECT • PROJECT • JOIN • INTERSECT • UNION • DIFFERENCE • PRODUCT • DIVIDE
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- 25. 25 Relational Set Operators (cont’d.) • Natural join – Links tables by selecting rows with common values in common attributes (join columns) • Equijoin – Links tables on the basis of an equality condition that compares specified columns • Theta join – Any other comparison operator is used
- 26. 26 Relational Set Operators (cont’d.) • Inner join – Only returns matched records from the tables that are being joined • Outer join – Matched pairs are retained, and any unmatched values in other table are left null
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- 28. 28 Relational Set Operators (cont’d.) • Left outer join – Yields all of the rows in the CUSTOMER table – Including those that do not have a matching value in the AGENT table • Right outer join – Yields all of the rows in the AGENT table – Including those that do not have matching values in the CUSTOMER table
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- 30. 30 The Data Dictionary and System Catalog • Data dictionary – Provides detailed accounting of all tables found within the user/designer-created database – Contains (at least) all the attribute names and characteristics for each table in the system – Contains metadata: data about data • System catalog – Contains metadata – Detailed system data dictionary that describes all objects within the database
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- 32. 32 The Data Dictionary and System Catalog (cont’d.) • Homonym – Indicates the use of the same name to label different attributes • Synonym – Opposite of a homonym – Indicates the use of different names to describe the same attribute
- 33. 33 Relationships within the Relational Database • 1:M relationship – Relational modeling ideal – Should be the norm in any relational database design • 1:1 relationship – Should be rare in any relational database design
- 34. 34 Relationships within the Relational Database (cont’d.) • M:N relationships – Cannot be implemented as such in the relational model – M:N relationships can be changed into 1:M relationships
- 35. The 1:M Relationship • Relational database norm • Found in any database environment 35
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- 37. 37 The 1:1 Relationship • One entity related to only one other entity, and vice versa • Sometimes means that entity components were not defined properly • Could indicate that two entities actually belong in the same table • Certain conditions absolutely require their use
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- 39. 39 The M:N Relationship • Implemented by breaking it up to produce a set of 1:M relationships • Avoid problems inherent to M:N relationship by creating a composite entity – Includes as foreign keys the primary keys of tables to be linked
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- 45. 45 Data Redundancy Revisited • Data redundancy leads to data anomalies – Can destroy the effectiveness of the database • Foreign keys – Control data redundancies by using common attributes shared by tables – Crucial to exercising data redundancy control • Sometimes, data redundancy is necessary
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- 47. 47 Indexes • Orderly arrangement to logically access rows in a table • Index key – Index’s reference point – Points to data location identified by the key • Unique index – Index in which the index key can have only one pointer value (row) associated with it • Each index is associated with only one table
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- 49. 49 Codd’s Relational Database Rules • In 1985, Codd published a list of 12 rules to define a relational database system – Products marketed as “relational” that did not meet minimum relational standards • Even dominant database vendors do not fully support all 12 rules
- 50. 50 Summary • Tables are basic building blocks of a relational database • Keys are central to the use of relational tables • Keys define functional dependencies – Superkey – Candidate key – Primary key – Secondary key – Foreign key
- 51. 51 Summary (cont’d.) • Each table row must have a primary key that uniquely identifies all attributes • Tables are linked by common attributes • The relational model supports relational algebra functions – SELECT, PROJECT, JOIN, INTERSECT UNION, DIFFERENCE, PRODUCT, DIVIDE • Good design begins by identifying entities, attributes, and relationships – 1:1, 1:M, M:N