2 - 1 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] CIS 8040 – DBMS ConceptS Modeling and Basics Outline Data Models DBMS Basics ANSI/SPARC Architecture Data Independence Centralized/Distributed DBMS2 - 2 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] Data Models  Formal representation for describing  Entities -- An object, concept or an event about which the org. chooses to collect and store information about  Relationships -- Associations among data  Operations -- Activities involved  Integrity constraints -- Data integrity and business rules  Data model classification in a DB  Physical data model  Deals with physical storage and access  Conceptual data model  Deals with conceptual structure and access  Logical data models  One step away from products created based on these models DBMS - Basics Database schema (Definition):  Description of the structure of a database  Organization of application data in a database Database state:  Data values stored in a database at a specific point of time.  Changes over time (How?) Database languages  Data definition language (DDL) -- Defines the database schema  Data manipulation language (DML)  Creates, deletes, modifies, and retrieves data in application programs  Data query language (e.g. SQL) -- For users to retrieve data2 - 3 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] Data Dependence Search ( name-asked : char[30] ); s : Student-Record; . . . Begin open ( student-file ); while not end of file do begin read-a-record ( s ); if s.name = name-asked then begin print ( s ); stop; end; end; print ( "No such a student." ); End. John, 3/21/70, . . . Peter, 6/2/78, . . . Lisa, 8/11/73, . . . Tom, 9/21/70, . . . Linda, 11/2/71, . . . Bill, 6/2/76, . . . Data Dependence... Search ( name-asked : char[30] ); root-record : student-record; begin root-record := root record; Find-It (name-asked, root-record ); end. Find-It ( name-asked : char[30]; root : student-record ); begin if root = null then begin print ( "No such a student." ); stop; end; if root.name = name-asked then begin print( root ); stop; end else if root.name < name-asked then find-it ( name-asked, root.left ); else find-it ( name-asked, root.right ); end. John, . . . Lisa, . . . Peter, . . . Tom, . . . Linda, . . . Bill, . . .2 - 4 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] Data Independence WHY do we have to modify our program after the data structure is changed? Data Independence: The capability to change the lower level structure of data without having to change the application programs at the next higher level. ANSI/SPARC Architecture View ( User 1 ) View ( User 2 ) View ( User N )Internal LevelExternal LevelConceptual LevelInternal SchemalConceptual SchemaPhysical Data OrganizationMapping Mapping Mapping Student(SID, Name, Address) Instructor(Emp#, Name, Address, Rank, Dept)2 - 5 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] Three Schema Levels  Internal level (schema)  Describes the physical storage structure and access paths  Uses a physical data model  Conceptual level (schema)  Describes the logical structure and access paths of the whole database  Hides the physical storage structure and access paths from the user  Uses a conceptual data model  External level (schema)  Describes individual user views  An external view is a part of the DB  Typically uses a logical data model ANSI/SPARC Architecture... Data independence is achieved by inter-level mappings… Queries are translated between levels automatically Physical data independence  Refers to immunity of conceptual schema to changes in the internal schema.  Internal schema changes (e.g. using different file organizations, storage structures/devices).  Should not require change to conceptual or external schemas. Logical data independence  Refers to immunity of external schemas to changes in conceptual schema.  Conceptual schema changes (e.g. addition/removal of entities).  Should not require changes to external schema or rewrites of application programs2 - 6 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] Centralized DB Systems DatabaseDBMS Distributed DB Systems DatabaseData Manager Transaction Manager DatabaseData Manager Transaction Manager DatabaseData Manager Transaction Manager DBMS2 - 7 Copyright © 2012 Robinson College of Business, Georgia State University David S. McDonald Director of Emerging Technologies Tel: 404-413-7368; e-mail: [email protected] Client/Server DB Systems Server Internet Client DatabaseDBMS Internet Client Internet