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Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe CHAPTER 2 Database System Concepts and Architecture Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 1- 2 Data Models Data Model: A set of concept...

Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe CHAPTER 2 Database System Concepts and Architecture Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 1- 2 Data Models Data Model: A set of concepts to describe the structure of a database, the operations for manipulating these structures, and certain constraints that the database should obey. Data Model Structure and Constraints: Constructs are used to define the database structure Constructs typically include elements (and their data types) as well as groups of elements (e.g. entity, record, table), and relationships among such groups. Constraints specify some restrictions on valid data; these constraints must be enforced at all times Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 3 Data Models (continued) Data Model Operations: These operations are used for specifying database retrievals and updates by referring to the constructs of the data model. Operations on the data model may include basic model operations (e.g. generic insert, delete, update) and user-defined operations (e.g. compute_student_gpa, update_inventory) Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 4 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 (representational) data models: Provide concepts that fall between the above two, used by many commercial DBMS implementations (e.g. relational data models). It represents data by using record structures Self-Describing Data Models: Combine the description of data with the data values. Examples include XML, key-value stores and some NOSQL systems. Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 5 Schemas versus Instances Database Schema: The description of a database. Includes descriptions of the database structure, data types, and the constraints on the database. Schema Diagram: An illustrative display of (most aspects of) a database schema. Schema Construct: A component of the schema or an object within the schema, e.g., STUDENT, COURSE. Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 6 Schemas versus Instances Database State: The actual data stored in a database at a particular moment in time. This includes the collection of all the data in the database. Also called database instance (or occurrence or snapshot). Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 7 Database Schema vs. Database State Database State: Refers to the content of a database at a moment in time. Initial Database State: Refers to the database state when it is initially loaded into the system. Valid State: A state that satisfies the structure and constraints of the database. Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 8 Database Schema vs. Database State (continued) Distinction The database schema changes very infrequently*. The database state changes every time the database is updated. Schema is also called intension. State is also called extension. Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 9 Example of a Database Schema Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 10 Example of a database state Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 11 Three-Schema Architecture Proposed to support DBMS characteristics of: Program-data independence. Support of multiple views of the data. Not explicitly used in commercial DBMS products, but has been useful in explaining database system organization Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 12 Three-Schema Architecture Defines DBMS schemas at three levels: Internal schema at the internal level to describe physical storage structures and access paths (e.g indexes). Typically uses a physical data model. Conceptual schema at the conceptual level to describe the structure and constraints for the whole database for a community of users. Uses a conceptual or an implementation data model. External schemas at the external level to describe the various user views. Usually uses the same data model as the conceptual schema. Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 13 The three-schema architecture Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 14 DATABASE LANGUAGES AND INTERFACES Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 15 DBMS Languages Data Definition Language (DDL) Data Manipulation Language (DML) Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 16 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. SDL is typically realized via DBMS commands provided to the DBA and database designers Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 17 DBMS Languages 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, C, C++, or Java. A library of functions can also be provided to access the DBMS from a programming language Alternatively, stand-alone DML commands can be applied directly (called a query language). Copyright © 2016 Ramez Elmasri and Shamkant B. Navathe Slide 2- 18

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