Chapter02
- 2. Chapter 2 Database System Concepts and Architecture
- 3. Outline Data Models and Their Categories History of Data Models Schemas, Instances, and States Three-Schema Architecture Data Independence DBMS Languages and Interfaces Database System Utilities and Tools Centralized and Client-Server Architectures Classification of DBMSs
- 4. 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
- 5. 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)
- 6. 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. These are usually specified in an ad-hoc manner through DBMS design and administration manuals Implementation (representational) data models: Provide concepts that fall between the above two, used by many commercial DBMS implementations (e.g. relational data models used in many commercial systems).
- 7. 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.
- 8. 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). The term instance is also applied to individual database components, e.g. record instance, table instance, entity instance
- 9. 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.
- 10. 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 .
- 11. Example of a Database Schema
- 12. Example of a database state
- 13. 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
- 14. 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.
- 16. Three-Schema Architecture Mappings among schema levels are needed to transform requests and data. Programs refer to an external schema, and are mapped by the DBMS to the internal schema for execution. Data extracted from the internal DBMS level is reformatted to match the user’s external view (e.g. formatting the results of an SQL query for display in a Web page)
- 17. Data Independence Logical Data Independence: The capacity to change the conceptual schema without having to change the external schemas and their associated application programs. Physical Data Independence: The capacity to change the internal schema without having to change the conceptual schema. For example, the internal schema may be changed when certain file structures are reorganized or new indexes are created to improve database performance
- 18. Data Independence (continued) 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 higher-level schemas themselves are unchanged . Hence, the application programs need not be changed since they refer to the external schemas.
- 19. DBMS Languages Data Definition Language (DDL) Data Manipulation Language (DML) High-Level or Non-procedural Languages: These include the relational language SQL May be used in a standalone way or may be embedded in a programming language Low Level or Procedural Languages: These must be embedded in a programming language
- 20. 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
- 21. 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 ).
- 22. Types of DML High Level or Non-procedural Language: For example, the SQL relational language Are “set”-oriented and specify what data to retrieve rather than how to retrieve it. Also called declarative languages. Low Level or Procedural Language: Retrieve data one record-at-a-time; Constructs such as looping are needed to retrieve multiple records, along with positioning pointers.
- 23. DBMS Interfaces Stand-alone query language interfaces Example: Entering SQL queries at the DBMS interactive SQL interface (e.g. SQL*Plus in ORACLE) Programmer interfaces for embedding DML in programming languages User-friendly interfaces Menu-based, forms-based, graphics-based, etc.
- 24. DBMS Programming Language Interfaces Programmer interfaces for embedding DML in a programming languages: Embedded Approach : e.g embedded SQL (for C, C++, etc.), SQLJ (for Java) Procedure Call Approach : e.g. JDBC for Java, ODBC for other programming languages Database Programming Language Approach : e.g. ORACLE has PL/SQL, a programming language based on SQL; language incorporates SQL and its data types as integral components
- 25. User-Friendly DBMS Interfaces Menu-based, popular for browsing on the web Forms-based, designed for naïve users Graphics-based (Point and Click, Drag and Drop, etc.) Natural language: requests in written English Combinations of the above: For example, both menus and forms used extensively in Web database interfaces
- 26. Other DBMS Interfaces Speech as Input and Output Web Browser as an interface Parametric interfaces, e.g., bank tellers using function keys. Interfaces for the DBA: Creating user accounts, granting authorizations Setting system parameters Changing schemas or access paths
- 27. Database System Utilities To perform certain functions such as: Loading data stored in files into a database. Includes data conversion tools. 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.
- 28. Other Tools 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. Passive data dictionary is accessed by users/DBA only.
- 29. Other Tools Application Development Environments and CASE (computer-aided software engineering) tools: Examples: PowerBuilder (Sybase) JBuilder (Borland) JDeveloper 10G (Oracle)
- 30. Typical DBMS Component Modules
- 31. Centralized and Client-Server DBMS Architectures Centralized DBMS: Combines everything into single system including- DBMS software, hardware, application programs, and user interface processing software. User can still connect through a remote terminal – however, all processing is done at centralized site.
- 32. A Physical Centralized Architecture
- 33. Basic 2-tier Client-Server Architectures Specialized Servers with Specialized functions Print server File server DBMS server Web server Email server Clients can access the specialized servers as needed
- 34. Logical two-tier client server architecture
- 35. Clients Provide appropriate interfaces through a client software module to access and utilize the various server resources. Clients may be diskless machines or PCs or Workstations with disks with only the client software installed. Connected to the servers via some form of a network. (LAN: local area network, wireless network, etc.)
- 36. DBMS Server Provides database query and transaction services to the clients Relational DBMS servers are often called SQL servers, query servers, or transaction servers Applications running on clients utilize an Application Program Interface ( API ) to access server databases via standard interface such as: ODBC: Open Database Connectivity standard JDBC: for Java programming access Client and server must install appropriate client module and server module software for ODBC or JDBC See Chapter 9
- 37. Two Tier Client-Server Architecture A client program may connect to several DBMSs, sometimes called the data sources. In general, data sources can be files or other non-DBMS software that manages data. Other variations of clients are possible: e.g., in some object DBMSs, more functionality is transferred to clients including data dictionary functions, optimization and recovery across multiple servers, etc.
- 38. Three Tier Client-Server Architecture Common for Web applications Intermediate Layer called Application Server or Web Server: Stores the web connectivity software and the business logic part of the application used to access the corresponding data from the database server Acts like a conduit for sending partially processed data between the database server and the client. Three-tier Architecture Can Enhance Security: Database server only accessible via middle tier Clients cannot directly access database server
- 40. 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 personal computers) vs. multi-user (most DBMSs). Centralized (uses a single computer with one database) vs. distributed (uses multiple computers, multiple databases)
- 41. Variations of Distributed DBMSs (DDBMSs) Homogeneous DDBMS Heterogeneous DDBMS Federated or Multidatabase Systems 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.
- 42. Cost considerations for DBMSs Cost Range: from free open-source systems to configurations costing millions of dollars Examples of free relational DBMSs: MySQL, PostgreSQL, others Commercial DBMS offer additional specialized modules, e.g. time-series module, spatial data module, document module, XML module These offer additional specialized functionality when purchased separately Sometimes called cartridges (e.g., in Oracle) or blades Different licensing options: site license, maximum number of concurrent users (seat license), single user, etc.
- 43. History of Data Models Network Model Hierarchical Model Relational Model Object-oriented Data Models Object-Relational Models
- 44. History of Data Models Network Model: The first network DBMS was implemented by Honeywell in 1964-65 (IDS System). Adopted heavily due to the support by CODASYL (Conference on Data Systems Languages) (CODASYL - DBTG report of 1971). Later implemented in a large variety of systems - IDMS (Cullinet - now Computer Associates), DMS 1100 (Unisys), IMAGE (H.P. (Hewlett-Packard)), VAX -DBMS (Digital Equipment Corp., next COMPAQ, now H.P.).
- 45. Example of Network Model Schema
- 46. Network Model Advantages: Network Model is able to model complex relationships and represents semantics of add/delete on the relationships. Can handle most situations for modeling using record types and relationship types. Language is navigational; uses constructs like FIND, FIND member, FIND owner, FIND NEXT within set, GET, etc. Programmers can do optimal navigation through the database.
- 47. Network Model Disadvantages: Navigational and procedural nature of processing Database contains a complex array of pointers that thread through a set of records. Little scope for automated “query optimization”
- 48. History of Data Models Hierarchical Data Model: Initially implemented in a joint effort by IBM and North American Rockwell around 1965. Resulted in the IMS family of systems. IBM’s IMS product had (and still has) a very large customer base worldwide Hierarchical model was formalized based on the IMS system Other systems based on this model: System 2k (SAS inc.)
- 49. Hierarchical Model Advantages: Simple to construct and operate Corresponds to a number of natural hierarchically organized domains, e.g., organization (“org”) chart Language is simple: Uses constructs like GET, GET UNIQUE, GET NEXT, GET NEXT WITHIN PARENT, etc. Disadvantages: Navigational and procedural nature of processing Database is visualized as a linear arrangement of records Little scope for "query optimization"
- 50. 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 (e.g. DB2, ORACLE, MS SQL Server, SYBASE, INFORMIX). Several free open source implementations, e.g. MySQL, PostgreSQL Currently most dominant for developing database applications. SQL relational standards: SQL-89 (SQL1), SQL-92 (SQL2), SQL-99, SQL3, … Chapters 5 through 11 describe this model in detail
- 51. History of Data Models Object-oriented Data Models: 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 Database Standard: ODMG-93, ODMG-version 2.0, ODMG-version 3.0. Chapters 20 and 21 describe this model.
- 52. History of Data Models Object-Relational Models: Most Recent Trend. Started with Informix Universal Server. Relational systems incorporate concepts from object databases leading to object-relational. Exemplified in the latest versions of Oracle-10i, DB2, and SQL Server and other DBMSs. Standards included in SQL-99 and expected to be enhanced in future SQL standards. Chapter 22 describes this model.
- 53. Summary Data Models and Their Categories History of Data Models Schemas, Instances, and States Three-Schema Architecture Data Independence DBMS Languages and Interfaces Database System Utilities and Tools Centralized and Client-Server Architectures Classification of DBMSs