Databases and Database Management Systems (Based on Chapters 1-2) 1

Databases and Database Management Systems (Based on Chapters 1-2) 1

DBMS concepts and architecture ER model Relational Databases Relational Algebra Query Languages (SQL) Storage and Indexing (optional) Database Design : Normalization and Functional Dependencies Transaction Processing Concurrency Control and Recovery Emerging Trends in Database Technology – Web Data management, XML, Web mining, 2

Text Required: Elmasri, R. and Navathe S., Fundamentals of Database Systems, 3rd Edition, Addison-Wesley, 2000. ISBN – 0-8053-1755-1 ORACLE Reference: ORACLE 8: The Complete Reference, by George Koch & Kevin Loney, Osborne McGraw-Hill, Inc., 1998. 3

1. Basic Definitions Database: A collection of related data. Data: Known facts that can be recorded and have an implicit meaning. Mini-world: Some part of the real world about which data is stored in a database. For example, consider student names, student grades and transcripts at a university. 4

Database Management System (DBMS): A software package/ system to facilitate the creation and maintenance of a computerized database. It defines (data types, structures, constraints) construct (storing data on some storage medium controlled by DBMS) manipulate (querying, update, report generation) databases for various applications. Database System: The DBMS software together with the data itself. Sometimes, the applications are also included. 5

2. Example of a Database (Conceptual Data Model) Mini-world for the example: Part of a UNIVERSITY environment. Some mini-world entities (Data elements): - STUDENTs - COURSEs - SECTIONs (of COURSEs) - (academic) DEPARTMENTs - INSTRUCTORs Some mini-world relationships: - SECTIONs are of specific COURSEs - STUDENTs take SECTIONs - COURSEs have prerequisite COURSEs - INSTRUCTORs teach SECTIONs - COURSEs are offered by DEPARTMENTs - STUDENTs major in DEPARTMENTs 6

Figure 1.1: A simplified database system environment, illustrating the concepts and terminology discussed in Section 1.1 7

Figure 1.2: An example of a database that stores student records and their grades. 8

File Processing and DBMS File Systems : – Store data over long periods of time – Store large amount of data However : – No guarantee that data is not lost if not backed up – No support to query languages – No efficient access to data items unless the location is known – Application depends on the data definitions (structures) – Change to data definition will affect the application programs – Single view of the data – Separate files for each application – Limited control to multiple accesses 9 - Data viewed as physically stored

3. Main Characteristics of Database Technology - Self-contained nature of a database system: A DBMS catalog stores the description (structure, type, storage format of each entities) of the database. The description is called meta-data). This allows the DBMS software to work with different databases. - Insulation between programs and data: Called program-data independence. Allows changing data storage structures and operations without having to change the DBMS access programs. - Data Abstraction: A data model is used to hide storage details and present the users with a conceptual view of the database; does not include how data is stored and how the operations are implemented. - 10

Support of multiple views of the data: Each user may see a different view of the database, which describes only the data of interest to that user. Sharing of Data and Multiple users 11

Figure 1.3: Internal storage format for a STUDENT RECORD 12

Figure 1.4:Two views derived from the example database shown in Figure 1.2 (a) The student transcript view. (b) The course prerequisite view. 13

DBA – Database Administrator - Responsible for authorizing access to the database, coordinating, monitoring its use, acquiring hardware, software needed. Database designers - Responsible for identifying the data to be stored, storage structure to represent and store data. This is done by a team of professionals in consultation with users, and applications needed. 14

4. Additional Benefits of Database Technology - Controlling redundancy in data storage and in development and maintenance efforts. Sharing of data among multiple users. Restricting unauthorized access to data. Providing multiple interfaces to different classes of users. Representing complex relationships among data. Enforcing integrity constraints on the database. Providing backup and recovery services. Potential for enforcing standards. Flexibility to change data structures. Reduced application development time. Availability of up-to-date information. Economies of scale. 15

Figure 1.5: The redundant storage of Data items. (a) Controlled Redundancy: Including StudentName and CourseNumber in the grade report file. (b) Uncontrolled redundancy: A GRADE REPORT record that is inconsistent with the STUDENT records in Figure 1.2, because the Name of student number 17 is Smith, not Brown. 16

5 When not to use a DBMS Main inhibitors (costs) of using a DBMS: - High initial investment and possible need for additional hardware. - Overhead for providing generality, security, recovery, integrity, and concurrency control. When a DBMS may be unnecessary: - If the database and applications are simple, well defined, and not expected to change. - If there are stringent real-time requirements that may not be met because of DBMS overhead. - If access to data by multiple users is not required. When no DBMS may suffice: - If the database system is not able to handle the complexity of data because of modeling limitations - If the database users need special operations not supported by the DBMS. 17

6. Data Models Data Model: A set of concepts to describe the structure (data types, relationships) of a database, and certain constraints that the database should obey. Data Model Operations: Operations for specifying database retrievals and updates by referring to the concepts of the data model. 18

Categories of data models: - Conceptual (high-level, semantic) data models: Provide concepts that are close to the way many users perceive data. (Also called entity-based or object-based data models.) Physical (low-level, internal) data models: Provide concepts that describe details of how data is stored in the computer. - Implementation (record-oriented) data models: Provide concepts that fall between the above two, balancing user views with some computer storage details. 19

6A. HISTORY OF DATA MODELS Relational Model: proposed in 1970 by E.F. Codd (IBM), first commercial system in 1981-82. Now in several commercial products (ORACLE, SYBASE, INFORMIX, INGRES). Network Model: the first one to be implemented by Honeywell in 1964-65 (IDS System). Adopted heavily due to the support by CODASYL (CODASYL DBTG report of 1971). Later implemented in a large variety of systems - IDMS (Cullinet - now CA), DMS 1100 (Unisys), IMAGE (H.P.), VAX -DBMS (Digital). Hierarchical Data Model : implemented in a joint effort by IBM and North American Rockwell around 1965. Resulted in the IMS family of systems. The most popular model. Other system based on this model: System 2k (SAS inc.) 20

Object-oriented Data Model(s) : several models have been proposed for implementing in a database system. One set comprises models of persistent O-O Programming Languages such as C (e.g., in OBJECTSTORE or VERSANT), and Smalltalk (e.g., in GEMSTONE). Additionally, systems like O2, ORION (at MCC - then ITASCA), IRIS (at H.P.- used in Open OODB). Object-Relational Models : Most Recent Trend. Exemplified in ILLUSTRA and UNiSQL systems. 21

Figure 2.1: Schema diagram for the database of Figure 1.2 22

7. Schemas versus Instances Database Schema: The description of a database. Includes descriptions of the database structure and the constraints that should hold on the database. Schema Diagram: A diagrammatic display of (some aspects of) a database Schema. Database Instance: The actual data stored in a database at a particular moment in time . Also called database state (or occurrence). The database schema changes very infrequently . The database state changes every time the database is updated . Schema is also called intension, whereas state is called extension. 23

8. Three-Schema Architecture Proposed to support DBMS characteristics of: Program-data independence. Support of multiple views of the data. Defines DBMS schemas at three levels : Internal schema at the internal level to describe data storage structures and access paths. Typically uses a physical data model. Conceptual schema at the conceptual level to describe the structure and constraints for the whole database. Uses a conceptual or an implementation data model. 24

External schemas at the external level to describe the various user views. Usually uses the same data model as the conceptual level. Mappings among schema levels are also needed. Programs refer to an external schema, and are mapped by the DBMS to the internal schema for execution. 25

Figure 2.2: Illustrating the three-schema architecture 26

9 Data Independence Logical Data Independence: The capacity to change the conceptual schema without having to change the external schemas and their application programs. Physical Data Independence: The capacity to change the internal schema without having to change the conceptual schema. When a schema at a lower level is changed, only the mappings between this schema and higher-level schemas need to be changed in a DBMS that fully supports data independence. The higherlevel schemas themselves are unchanged. Hence, the application programs need not be changed since they refer to the external schemas. 27

10. DBMS Languages Data Definition Language (DDL): Used by the DBA and database designers to specify the conceptual schema of a database. In many DBMSs, the DDL is also used to define internal and external schemas (views). In some DBMSs, separate storage definition language (SDL) and view definition language (VDL) are used to define internal and external schemas. Data Manipulation Language (DML): Used to specify database retrievals and updates. -DML commands (data sublanguage) can be embedded in a general-purpose programming language (host language), such as COBOL, PL/1 or PASCAL. - Alternatively, stand-alone DML commands can be applied directly (query language). 28

High Level or non-Procedural DML – Describes what data to be retrieved rather than how to retrieve. - Process many records at a time - SQL Low Level or Procedural DML – It needs constructs for both, what to retrieve and what to retrieve - Uses looping etc. like programming languages Only access one record at a time 29

11. DBMS Interfaces -Stand-alone query language interfaces. Programmer interfaces for embedding DML in programming languages: - Pre-compiler Approach - Procedure (Subroutine) Call Approach User-friendly interfaces: - Menu-based - Graphics-based (Point and Click, Drag and Drop etc.) - Forms-based - Natural language - Combinations of the above - Speech as Input (?) and Output - Web Browser as an interface - 30

Parametric interfaces using function keys. Report generation languages. Interfaces for the DBA: - Creating accounts, granting authorizations - Setting system parameters - Changing schemas or access path 31

Figure 2.3: Typical component modules of a DBMS. Dotted lines show accesses that are under the control of the stored data manager. 32

13. Database System Utilities To perform certain functions such as: Loading data stored in files into a database. Backing up the database periodically on tape. Reorganizing database file structures. Report generation utilities. Performance monitoring utilities. Other functions, such as sorting , user monitoring , data compression , etc. Data dictionary / repository: Used to store schema descriptions and other information such as design decisions, application program descriptions, user information, usage standards, etc. Active data dictionary is accessed by DBMS software and users/DBA. 33 - Passive data dictionary is accessed by users/DBA only.

14. Classification of DBMSs Based on the data model used: Traditional: Relational, Network, Hierarchical. Emerging: Object-oriented, Object-relational. Other classifications: Single-user (typically used with micro- computers) vs. multi-user (most DBMSs). Centralized (uses a single computer with one database) vs. distributed (uses multiple computers, multiple databases) Distributed Database Systems have now come to be known as client server based database systems because they do not support a totally distributed environment, but rather a set of database servers supporting a set of clients. 34