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The Relational Data Model

The Relational Data Model. TCU Database Systems Last update: September 2004 Reference: Elmasri 4 th edition, chapter 5. Introduction . Codd (1970) Theoretical (mathematical) foundation Concepts relation data structure integrity constraints Operations relational algebra and extensions.

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The Relational Data Model

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  1. The Relational Data Model TCU Database Systems Last update: September 2004 Reference: Elmasri 4th edition, chapter 5

  2. Introduction • Codd (1970) • Theoretical (mathematical) foundation • Concepts • relation data structure • integrity constraints • Operations • relational algebra and extensions

  3. Definitions • Figure 5.1 (informal definitions) • Domain D: a set of atomic (indivisible) values • {Names}, {valid GPA’s}, {valid grades} • must specify a data type {char(30)}, {[0.0,4.0]},{A,B,C,D,F} • dom(Ai)=data type

  4. Definition: Relation Schema • think of as template or a Prolog predicate • R(A1, A2,...,An) where • R = relation name • Ai=attribute • n = degree of relation R • example: PET(Name, Type, Breed, Birthdate, Weight)

  5. Definition: Relation • r(R): a relation r of the relation schema R(A1,A2,...,An) • set of n-tuples r={t1, t2,...,tm} • each n-tuple t is an ordered list, t=<v1,v2,...,vn>, where • vi is an element of dom(Ai) or null (unknown/D.N.E.) • More formally • a relation r(R) is a subset of the Cartesian product of the domains that define R • Max size (assuming finite domains):

  6. Definition: Relational DB Schema • Set of relation schemas AND integrity constraints • Figure 5.5 • A relational DB instance is a set of relation instances that satisfy the integrity constraints • Figure 5.6

  7. Characteristics of Relations • Row order (ordering of tuples) is insignificant • formally, but for performance it may be • Column order is insignificant • given a unique name or a fixed order • All values are atomic - can’t be subdivided • called the first normal form assumption • no composite attributes (e.g., address) • no multivalued attributes (e.g., car colors)

  8. Relational Model Constraints • Domain • Key • Entity Integrity • Referential Integrity • Others in section 5.2.5 and later in normalization • Generally no ability to declaratively specify • semantic integrity constraints (max hours all projects<56; salary<boss) • heuristics (folks usually weigh more than their age)

  9. Domain Constraint • attribute value is an atomic value from domain • Example domains (from Oracle) • number(l,d): l=length, d=decimal digits • char(size): fixed length • varchar(size): variable length char string • date • long: up to 2 GB • many allow subranges and enumerated data types

  10. Key Constraint • Each tuple in r is unique (a set) • superkey: any subset of attributes for which the values are unique in all valid DB states • key: a minimal superkey • candidate key: multiple keys may be possible • primary key: the candidate key selected • prefer integer key or key with fewest attributes • Figure 5.4

  11. Integrity Constraints • Entity Integrity • no primary key value can be null • Referential Integrity • foreign key • same domain as p.k. attribute of referenced schema • value equals an existing referenced attribute or is null (if not part of a p.k.) • Figures 5.6, 5.7

  12. Updates • DBMS must enforce integrity constraints • Insert • can violate all 4 I.C.’s • DBMS rejects or asks for correction • Delete • can only violate referential integrity • reject/cascade/modify referencing attribute value (null, default or another tuple value) • Modify • can violate all 4 if p.k. or f.k. • else domain constraint only examples pp 141-143

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