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System Concepts and Architecture

System Concepts and Architecture. Rose-Hulman Institute of Technology Curt Clifton. Data Model. A set of concepts to describe Database structure Basic operations on the data. Categories of Data Models. Conceptual Closest to users’ views Implementation

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System Concepts and Architecture

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  1. System Concepts and Architecture Rose-Hulman Institute of Technology Curt Clifton

  2. Data Model • A set of concepts to describe • Database structure • Basic operations on the data

  3. Categories of Data Models • Conceptual • Closest to users’ views • Implementation • Intermediate level for programmers • Physical • Actual hardware level

  4. Database Schema • A description of the database • Not the actual data in it • Tends to change seldom • Shown with a Schema Diagram

  5. Database State • Actual content at an instant in time • Every change results in a new state • DBMS tries to ensure only valid states occur

  6. Three-Schema Architecture • Goals: • Support program-data independence • Represent multiple views of data

  7. The Three Schemas • Internal schema • Describes storage with physical data model • Conceptual schema • Describes entire database structurewith conceptual or implementation data model • External schemas • Describe user viewstypically with same data model

  8. Data Independence • Two kinds: • Logical: change conceptual schema without changing external schemas • Physical: change internal schema without changing conceptual • Just update mappings

  9. Database System Architectures • Centralized • All processing on one machine • Mainframe + dumb terminals • Client-Server • Specialized server machines for each function • Smart client machines provide interfaces • Connected via some sort of network

  10. Two Tier Client-Server • Client runs UI and application programs • Uses API to connect directly to DBMS • Perhaps multiple DBMS

  11. Three Tier Client-Server • Intermediate layer • Application Server or Web Server • Advantages • Security • Scalability • Disadvantage • Complexity

  12. Entity-Relationship Model Rose-Hulman Institute of Technology Curt Clifton

  13. Entity-Relationship Model • Lets us sketch database designs • Sketches called ER Diagrams • Simple enough share with customers • Can convert sketches into implementations • Conversion is easy (with practice)

  14. Entity Sets • Entity: a “thing” that database tracks • Entity set: a collection of similar entities • Attribute: property of an entity • Simple values, like integers or strings • All entities in set have same properties(though different values)

  15. Entity Set Notation Attribute 2 Attribute 3 Attribute 1 Entity Set Name Entity set names areusually singular, i.e. “Employee”not “Employees”

  16. Relationships • Connect two (or more) entity sets • Notation: • Try to make verbs read left-to-right, top-to-bottom Verbs Entity Set 1 Entity Set 2

  17. Values • Entity set value: • The set of entities in it • Relationship value: • A set of pairs (or triples, …) withone element from each related entity set

  18. Multi-way Relationships • Connect more than two entity sets • Useful for more complex relationships

  19. Relationship Constraints • One-One: • Entity of first set can connect to just one entity in second set, and vice versa Verbs 1 Entity Set 1 Entity Set 2 1

  20. Relationship Constraints • One-Many: • Entity of first set can connect to just one entity in second set • Entity of second set can connect to many in first • Use N for arbitrary number greater than 1,or put specific number Verbs N Entity Set 1 Entity Set 2 1

  21. Relationship Constraints • Many-Many: • An entity of either set can connect to many entities in the other set • Use N and M for arbitrary number greater than 1,or put specific number (or omit) Verbs N Entity Set 1 Entity Set 2 M

  22. Relationship Constraints • Numbers on lines indicate maximums • Can also show that every entity must participate • Every entity of first set must be related to at least one entity of the second set Verbs M Entity Set 1 Entity Set 2 N

  23. Attributes on Relationships • Sometimes attribute is property of relationship instead of either entity Verbs Entity Set 1 Entity Set 2 Attribute

  24. Recursive Relationships • When an entity set is related to itself • Label edges with roles • Consider “Cousin Of” • Symmetrical • No clear role names Person wife husband Marries

  25. Subclasses • Subclass = fewer entities • Have more properties • Entity of subclass set is alsoin superclass set • Has all attributes of both sets SuperclassEntity Set isa SubclassEntity Set

  26. Keys • Let us tell entities apart • The key for an entity set is a subset of the attributes for that entity set, such that no two entities agree on all the attributes

  27. Showing Keys • Each entity must have a key • Shown by underlining names of key attributes • For subclass hierarchies: • Only the root entity set has a key • All entities in hierarchy use that key

  28. Weak Entity Sets • When even all the attributes aren’t enough for a key… • Use a many-one relationship to “borrow” an additional attribute for the key

  29. Example Weak Entity Set • Consider football players in a fantasy league • Is Name a key? • Is Number a key? • Need Number + Team Played On name number name Plays on Player Team 1

  30. Practice with E-R Diagrams • In groups of 2–3 work on HW Problem 3.21 • On back of handout

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