vdocuments.mx_chapter-2-database-environment-thomas-connolly-carolyn-begg-database-system.ppt
- 1. Chapter 2 Database Environment Thomas Connolly, Carolyn Begg, Database System, A Practical Approach to Design Implementation and Management, 4th Edition, Addison Wesley Pg 33 ~ 62
- 2. Learning Outcomes • Three-Level ANSI-SPARC Architecture • Database Languages • Data Models • Functions of DBMS • Components of DBMS • Teleprocessing
- 3. Two-Level Approach • Standard Terminology & General Architecture of dadabase • Produced in 1971 by DBTG • Appointed by the CODASYL • System View(Schema) • User View (Sub schema)
- 4. ANSI/SPARC • ANSI – American National Standards Institute • SPARC – Standards Planning and Requirements Committee • 1975 – Proposed a framework for DBS
- 5. Three-Level ANSI-SPARC Architecture • External level (Database Users) – Provide a view of the database tailored to a user • Data gathering • Conceptual level (Database Designer) – Deals with the organization of data as a whole • Constraints and security • Entity-relationship diagram • Normalization • Mapping & Desired independence • Internal level (System Designer) – Deal with physical storage of data • Storage, index, compression, & encryption • File organization
- 7. Database Schemas • Database schema (intension) & database instance (extension) – External schemas (subschema) – Conceptual schema (database schema) – Internal schema
- 8. Mapping • Translate information from one level to the next – External/conceptual mapping – Conceptual/internal mapping • Provide data independence
- 9. Data Independence • Logical data independence – Conceptual level changed shouldn’t affect external levels • Physical data independence – Change to internal level shouldn’t affect conceptual level
- 11. Database Languages • Data Definition Language (DDL) – Structured Query Language (SQL) • Data Manipulation Language (DML) – Procedural DML – Non-procedural DML • Structured Query Language (SQL) • Query-by-Example (QBE) • Fourth-Generation Language – Form, report, graphics, & application generators
- 12. Data Models • Definition – Integrated concept for describing data, relationships and constraints • Types – Object-based data models – Record-based data models – Physical data models (internal structure, ordering, & paths)
- 13. Object-Based Data Models • Entity-relationship – Entity, attribute, relationship – Usage: documentation • Object-oriented – Object, class, subclass, inheritance, state (attributes), behavior (methods or actions), encapsulation, message, polymorphism – Usage: building software
- 14. Record-Based Data Models • Relational data model • Network model • Hierarchical Model
- 15. Relational Data Model • Terminology – Relations – Attributes – Tuples • Record relationship – One-to-many relationship • Usage – Ad hoc reporting
- 16. Network Model • CODASYL DBTG • Terminology – Data item & group item – Record type: owner, member – Set type: optional, mandatory, permanent • Record relationship – Many-to-many relationship – Link or pointer between set owner and set member • Usage – Large volume transaction processing
- 17. Hierarchical Model • IBM • Information Management Systems • Terminology – Tree, general tree, & subtree – Nodes, root node, parent node, and child node – Segment type ( root, parent, child) • Record relationship – One-to-many relationship – Link or pointer between parent node and child node – No many-to-many relationship • Usage – Large volume transaction processing
- 18. Functions of a DBMS • Data storage, retrieval and update • A user-accessible catalog • Transaction support • Concurrency control • Recovery • Authorization • Integrity • Data independence • Data communication • Other Utilities
- 19. Components of a DBMS • Query processor • Database manager • File manager • DML preprocessor • DDL compiler • Catalog manager
- 20. Components of Database Manager • Authorization control • Command processor • Integrity checker • Query optimizer • Transaction manager • Scheduler • Recovery manager • Buffer manager
- 21. Teleprocessing - I • Two-tier client-server architecture – Client: user interface, business and data processing logic – Database server: data validation and database access – Advantage • Accessing to distributed database • Increasing performance and consistency • Lowering server and communication cost • Supporting open systems architecture
- 22. Teleprocessing - II • Three-tier client-server architecture – Client: user interface – Application server: business and processing logic – Database server: data validation and database access – Advantage • Reducing client cost • Software distribution • Maintenance cost • Balancing load
- 23. Teleprocessing - III • Transaction processing (TP) monitor – Transaction manager between client and server – Advantage • Transaction routing • Distributed transaction for load balancing