# Introduction to modeling

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1 Introduction to modeling Relational modelling Slides for this part are based on Chapters 11 from Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition (ISBN: ), published by Morgan Kaufmann Publishers. 1

2 Where are we? # Title Date 1 Introduction ORM modeling Relational modeling ER modeling OO modeling Process modeling Service modeling Exam

3 Relational model Data Model Set of concepts to describe the structure of a database Relational Model The database can be regarded as a collection of tables Key concepts: Relation: A mathematical concept that can be interpreted as a table of values Relational Database: A collection of relations null indicates that no value is stored in that position 3

4 Terminology Domain: An set of atomic values. Atomic means that items can not themselves be sets Attribute: A name of a role played by a domain (column name) If A is an attribute, we write dom(a) = D to express that A is a role played by the domain D Relational schema R(A1,A2,,An): A named set of attributes R = {A1,A2,,An} where R is the relation name n is the arity of the relationship Instance of a relational schema R(A1,A2,,An): A set {t1,t2,,tm} ("rows") where each t k is a n-tuple of values from the domain of A1,A2,,An Relation: A relational schema with an associated instance 4

5 Example Relation schema Relation name attribute Employee empnr salary tax instances Horizontal layout notation: the table name precedes a parenthesized list of column names, separated by commas: Employee (empnr, salary, tax ) Tuppel 5

6 Remarks Tuples order in relations is arbitrarily The order of values within a tuple is not arbitrary In one relations there cannot be two identical tuples A domain can be finite or infinite Two attributes in a relational schema can have the same domain, but not the same name 6

7 Uniqueness constraints on relational columns In horizontal layout, uniqueness constraints on relational columns are shown by underlining. Each unique column, or unique column combination, provides a candidate key for identifying rows in a table. A key is a minimal set of uniquely constrained attributes, i.e. if an attribute is removed from a compound key, the remaining attributes are not spanned by a uniqueness constraint. If there is only one candidate key, this is automatically the primary key, e.g. Employee (empnr, salary, tax) Material on this slide based on Ch 11.2 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 7

8 Uniqueness constraints on relational columns If more than one candidate key exists, one of these must be selected as the primary key. The others are then called alternate keys or secondary keys. Primary keys are doubly underlined if alternate keys exist, e.g. Employee (empnr, empname, deptcode, salary, tax) A column that does not allow null values is said to be mandatory (A column that does allow null values is said to be optional. Optional columns are enclosed in square brackets, e.g. Employee (empnr, salary, [tax]) Material on this slide based on Ch 11.2 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 8

9 Mapping ORM models Employee (.nr) has paid Salary (E U R:) Tax (E U R:) => Employee (empnr, salary, [tax]) ? Relational model often requires different facts about the same object to be stored in different tables Mandatory role constraints are captured by making their columns mandatory in their table, and running a subset constraint from other tables (if any) that contain facts about that object type Material on this slide based on Ch 11.2 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 9

10 Mapping ORM models has Salary (E U R:) Employee (empnr, salary, [tax]) Employee (.nr) paid works in Project (.Id) Tax (E U R:) => WorksIn (empnr, project) empnr in the WorksIn table is a foreign key 10

11 Integrity rules Entity integrity rule: primary keys contain no nulls (i.e., each column in a primary key is a mandatory column for its table). Referential integrity rule: each non-null value of a foreign key must match the value of some primary key Material on this slide based on Ch 11.2 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 11

12 Relational schema representations Relational schema in horizontal layout and some vertical layouts: Material on this slide based on Ch 11.2 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 12

13 Relational schema representations Relational schema in SQL: Material on this slide based on Ch 11.2 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 13

14 Relational Mapping Procedure Rmap Several different relational designs may be possible for a given conceptual schema But the resulting relational design should be correct, efficient, and clear A high priority is placed on simplifying the enforcement of constraints at update time Avoid redundancy, but this can lead to more tables in the design For efficiency, number of tables should be kept down to an acceptable limit Rmap procedure guarantees a redundancy-free relational design and includes strategies to restrict the number of tables Material on this slide based on Ch 11.3 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 14

15 Rmap basic rules Typically each row of a relational table stores one or more elementary facts Avoiding redundancy in tables: ensure that each fact type maps to only one table in such a way that its instances appear only once Material on this slide based on Ch 11.2 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 15

16 Rmap basic rules Two basic rules: 1. Each fact type with a compound, internal uniqueness constraint maps to a separate table by itself, keyed on the uniqueness constraint 2. Fact types with functional roles (i.e. roles that have a simple uniqueness constraint) attached to the same object type are grouped into the same table, keyed on the object type s identifier Material on this slide based on Ch 11.2 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 16

17 Rmap - Mapping 1:1 Associations When no additional functional roles: When additional functional roles: Material on this slide based on Ch 11.3 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 17

18 Rmap - Mapping 1:1 Associations Procedure: Material on this slide based on Ch 11.3 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 18

19 Rmap Mapping External Uniqueness Constraints Composite primary identifier, and functional fact type: Composite primary identifier and nonfunctional fact type: Material on this slide based on Ch 11.3 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 19

20 Rmap Mapping External Uniqueness Constraints Composite secondary identifier and functional fact type: External uniqueness constraint involving an m:n fact type: Material on this slide based on Ch 11.3 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 20

21 Rmap Mapping Objectified Associations Initially treat the objectified association as a black box (i.e. remove its identification scheme) Group fact types in the usual way Unpack the black box into its component attributes Material on this slide based on Ch 11.3 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 21

22 Rmap Mapping Subtypes Subtyping mapping: Absorption: absorb the subtypes back into the (top) supertype (giving qualified optional roles), group the fact types as usual, and then add the subtyping constraints as textual qualifications Separation: separate tables for facts with subtype specific functional roles Partition: may be used when the subtypes form a partition of their supertype Subtype constraints on functional roles map to qualified optionals: Nonfunctional fact type of subtypes map to separate tables: Material on this slide based on Ch 11.3 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 22

23 Basic Rmap procedure Material on this slide based on Ch 11.3 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition 23

24 Resources Chapter 11 in Halpin, T. & Morgan, T. 2008, Information Modeling and Relational Databases, Second Edition (ISBN: ), published by Morgan Kaufmann Publishers. 24

25 Next lecture # Title Date 1 Introduction ORM modeling Relational modeling ER modeling OO modeling Process modeling Service modeling Exam

26 Questions? 26

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