Database Environment. Pearson Education 2009

Transcription

1 Chapter 2 Database Environment 1 Chapter 2 - Objectives Purpose of three-level database architecture. Contents of external, conceptual, and internal levels. Purpose of external/conceptual and conceptual/internal mappings. Meaning of logical and physical data independence. Distinction between DDL and DML. A classification of data models. 2

2 Chapter 2 - Objectives Purpose/importance of conceptual modeling. Typical functions and services a DBMS should provide. Function and importance of system catalog. Software components of a DBMS. Meaning of client server architecture and advantages of this type of architecture for a DBMS. Function and uses of Transaction Processing Monitors. 3 Objectives of Three-Level Architecture All users should be able to access same data. A user s view is immune to changes made in other views. Users should not need to know physical database storage details. 4

3 Objectives of Three-Level Architecture DBA should be able to change database storage structures without affecting the users views. Internal structure of database should be unaffected by changes to physical aspects of storage. DBA should be able to change conceptual structure of database without affecting all users. 5 ANSI-SPARC Three-Level Architecture 6

4 ANSI-SPARC Three-Level Architecture External Level Users view of the database. Describes that part of database that is relevant to a particular user. Conceptual Level Community view of the database. Describes what data is stored in database and relationships among the data. 7 ANSI-SPARC Three-Level Architecture Internal Level Physical representation of the database on the computer. Describes how the data is stored in the database. 8

5 Differences between Three Levels of ANSI- SPARC Architecture 9 Data Independence 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 programs. 10

6 Data Independence 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. 11 Data Independence and the ANSI-SPARC Three-Level Architecture 12

7 Database Languages Data Definition Language (DDL) Allows the DBA or user to describe and name entities, attributes, and relationships required for the application plus any associated integrity and security constraints. 13 Database Languages Data Manipulation Language (DML) Provides basic data manipulation operations on data held in the database. Procedural DML allows user to tell system exactly how to manipulate data. Non-Procedural DML allows user to state what data is needed rather than how it is to be retrieved. Fourth Generation Languages (4GLs) 14

8 Data Model Integrated collection of concepts for describing data, relationships between data, and constraints on the data in an organization. Data Model comprises: a structural part; a manipulative part; possibly a set of integrity rules. 15 Data Model Purpose To represent data in an understandable way. Categories of data models include: Object-based Record-based Physical. 16

9 Data Models Object-Based Data Models Entity-Relationship Semantic Functional Object-Oriented. Record-Based Data Models Relational Data Model Network Data Model Hierarchical Data Model. Physical Data Models 17 Relational Data Model 18

10 Network Data Model 19 Hierarchical Data Model 20

11 Conceptual Modeling Conceptual schema is the core of a system supporting all user views. Should be complete and accurate representation of an organization s data requirements. Conceptual modeling is process of developing a model of information use that is independent of implementation details. Result is a conceptual data model. 21 Enterprise Data Model First step in database development Specifies scope and general content Overall picture of organizational data at high level of abstraction Entity-relationship diagram Descriptions of entity types Relationships between entities Business rules 22

12 Figure 2-1 Segment from enterprise data model Enterprise data model describes the highlevel entities in an organization and the relationship between these entities 23 Information Engineering A data-oriented methodology to create and maintain information systems Top-down planning a a generic IS planning methodology for obtaining a broad understanding of the IS needed by the entire organization Four steps to Top-Down planning: Planning Analysis Design Implementation 24

13 25 Identify Strategic Planning Factors (Table 2-2) 2 2) Organization goals what we hope to accomplish Critical success factors what MUST work in order for us to survive Problem areas weaknesses we now have 26

14 Identify Corporate Planning Objects (Table 2-3) 2 Organizational units departments Organizational locations Business functions groups of business processes Entity types the the things we are trying to model for the database Information systems application programs 27 Develop Enterprise Model Functional decomposition Iterative process breaking system description into finer and finer detail Enterprise data model Planning matrixes Describe interrelationships between planning objects 28

15 29 Planning Matrixes Describe relationships between planning objects in the organization Types of matrixes: Location-to to-function Unit-to to-function IS-to to-data entity Supporting function-to to-data entity IS-to to-business objective 30

16 Example Business Function-to to-data Entity Matrix (Fig. 2-3) 2 31 Two Approaches to Database and IS Development SDLC System Development Life Cycle Detailed, well-planned development process Time-consuming, but comprehensive Long development cycle Prototyping Rapid application development (RAD) Cursory attempt at conceptual data modeling Define database during development of initial prototype Repeat implementation and maintenance activities with new prototype versions 32

17 Systems Development Life Cycle (see also Figures 2.4, 2.5) Planning Analysis Logical Design Physical Design Implementation Maintenance 33 Systems Development Life Cycle (see also Figures 2.4, 2.5) (cont.) Planning Analysis Purpose preliminary understanding Deliverable request for study Logical Design Physical Design Database activity enterprise modeling and early conceptual data modeling Implementation Maintenance 34

18 Systems Development Life Cycle (see also Figures 2.4, 2.5) (cont.) Planning Analysis Purpose thorough requirements analysis and structuring Deliverable functional system specifications Logical Design Physical Design Database activity thorough and integrated conceptual data modeling Implementation Maintenance 35 Planning Systems Development Life Cycle (see also Figures 2.4, 2.5) (cont.) Analysis Purpose information requirements elicitation and structure Deliverable detailed design specifications Logical Design Physical Design Database activity logical database design (transactions, forms, displays, views, data integrity and security) Implementation Maintenance 36

19 Systems Development Life Cycle (see also Figures 2.4, 2.5) (cont.) Planning Analysis Logical Design Purpose develop technology and organizational specifications Deliverable program/data structures, technology purchases, organization redesigns Physical Design Database activity physical database design (define database to DBMS, physical data organization, database processing programs) Implementation Maintenance 37 Planning Systems Development Life Cycle (see also Figures 2.4, 2.5) (cont.) Analysis Logical Design Purpose programming, testing, training, installation, documenting Deliverable operational programs, documentation, training materials Database activity database implementation, including coded programs, documentation, installation and conversion Physical Design Implementation Maintenance 38

20 Systems Development Life Cycle (see also Figures 2.4, 2.5) (cont.) Planning Analysis Purpose monitor, repair, enhance Deliverable periodic audits Logical Design Database activity database maintenance, performance analysis and tuning, error corrections Physical Design Implementation Maintenance 39 Prototyping Database Methodology (Figure 2.6) 40

21 Prototyping Database Methodology (Figure 2.6) (cont.) 41 Prototyping Database Methodology (Figure 2.6) (cont.) 42

22 Prototyping Database Methodology (Figure 2.6) (cont.) 43 Prototyping Database Methodology (Figure 2.6) (cont.) 44

23 CASE Computer-Aided Software Engineering (CASE) software tools providing automated support for systems development Three database features: Data modeling drawing drawing entity-relationship diagrams Code generation SQL code for table creation Repositories knowledge base of enterprise information 45 Packaged Data Models Model components that can be purchased, customized, and assembled into full-scale data models Advantages Reduced development time Higher model quality and reliability Two types: Universal data models Industry-specific specific data models 46

24 Managing Projects Project a a planned undertaking of related activities to reach an objective that has a beginning and an end Involves use of review points for: Validation of satisfactory progress Step back from detail to overall view Renew commitment of stakeholders Incremental commitment review of systems development project after each development phase with rejustification after each phase 47 Managing Projects: People Involved Business analysts Systems analysts Database analysts and data modelers Users Programmers Database architects Data administrators Project managers Other technical experts 48

25 Database Schema External Schema User Views Subsets of Conceptual Schema Can be determined from business-function/data entity matrices DBA determines schema for different users Conceptual Schema E-R R models covered in Chapters 3 and 4 Internal Schema Logical structures covered covered in Chapter 5 Physical structures covered covered in Chapter 6 49 Figure 2-7 Three-schema architecture Different people have different views of the database these are the external schema The internal schema is the underlying design and implementation 50

26 51 52

27 Pine Valley Furniture Segment of project data model (Figure 2-11) 53 Figure 2-12 Four relations (Pine Valley Furniture) 54

28 Figure 2-12 Four relations (Pine Valley Furniture) (cont.) 55 Functions of a DBMS Data Storage, Retrieval, and Update. A User-Accessible Catalog. Transaction Support. Concurrency Control Services. Recovery Services. 56

29 Functions of a DBMS Authorization Services. Support for Data Communication. Integrity Services. Services to Promote Data Independence. Utility Services. 57 System Catalog Repository of information (metadata) describing the data in the database. One of the fundamental components of DBMS. Typically stores: names, types, and sizes of data items; constraints on the data; names of authorized users; data items accessible by a user and the type of access; usage statistics. 58

30 Components of a DBMS 59 Components of Database Manager (DM) 60

31 Multi-User DBMS Architectures Teleprocessing File-server Client-server 61 Teleprocessing Traditional architecture. Single mainframe with a number of terminals attached. Trend is now towards downsizing. 62

32 File-Server File-server is connected to several workstations across a network. Database resides on file-server. DBMS and applications run on each workstation. Disadvantages include: Significant network traffic. Copy of DBMS on each workstation. Concurrency, recovery and integrity control more complex. 63 File-Server Architecture 64

33 Traditional Two-Tier Client-Server Client (tier 1) manages user interface and runs applications. Server (tier 2) holds database and DBMS. Advantages include: wider access to existing databases; increased performance; possible reduction in hardware costs; reduction in communication costs; increased consistency. 65 Traditional Two-Tier Client-Server 66

34 Traditional Two-Tier Client-Server 67 Three-Tier Client-Server Client side presented two problems preventing true scalability: Fat client, requiring considerable resources on client s computer to run effectively. Significant client side administration overhead. By 1995, three layers proposed, each potentially running on a different platform. 68

35 Three-Tier Client-Server Advantages: Thin client, requiring less expensive hardware. Application maintenance centralized. Easier to modify or replace one tier without affecting others. Separating business logic from database functions makes it easier to implement load balancing. Maps quite naturally to Web environment. 69 Three-Tier Client-Server 70

36 Transaction Processing Monitors Program that controls data transfer between clients and servers in order to provide a consistent environment, particularly for Online Transaction Processing (OLTP). 71 TPM as middle tier of 3-tier client-server 72