Database system concepts


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Database system concepts

  1. 1. DATABASE Basic Terminologies
  2. 2. Basic Database Terminology • Database – A collection (or list) of information. A database is comprised of one or more lists (called tables) of data organized by columns, rows, and cells. • Tables – The view that displays the data base as a combinations of rows (records) and columns (fields). The cells contain the bits and pieces of data for each record in each field. The first row of a table is reserved for the field names.
  3. 3. Basic Database Terminology • Field names – Identify the different categories in a database. The top row is reserved for field names. Examples of field names are First name, last name, address, city, state, zip, phone number. • Field – Categories in a database. Fields are displayed in columns. For Example, in a database, the zip field contains all the zip codes from each of the records. These are the bits and pieces of data.
  4. 4. Basic Database Terminology • Records – Related information that is separated by columns or fields. A name and address are considered one record in the database. A second Name and address are a different record. • Cells - The intersection of columns and rows that contain the data for each record • Data – All of the records of information in a database including the field names. Data + Field Names = Records All Records = a Database.
  5. 5. Basic Database Terminology • Objects – Enables you to find, view, display, and print data differently, based on your needs. The most commonly used objects are tables, queries, forms and reports.  Tables show all records in a spreadsheet format  Queries allow you to ask questions of the one or more tables and show only the information you ask for  Forms display one record at a time  Reports give and organize why of presenting information.
  6. 6. Instance and Schema Database Instance The term instance is typically used to describe a complete database environment, including the RDBMS software, table structure, stored procedures and other functionality. It is most commonly used when administrators describe multiple instances of the same database. Also Known As: environment
  7. 7. Instance and Schema Examples: An organization with an employees database might have three different instances: production (used to contain live data), pre-production (used to test new functionality prior to release into production) and development (used by database developers to create new functionality).
  8. 8. Instance and Schema SCHEMA A relation schema can be thought of as the basic information describing a table or relation. This includes a set of column names, the data types associated with each column, and the name associated with the entire table.
  9. 9. Instance and Schema For example, a relation schema for the relation called Students could be expressed using the following representation: Students(sid: string, name: string, login:string, age: integer, gpa: real) There are five fields or columns, with names and types as shown above.
  10. 10. Database System Concepts and Architecture
  11. 11. Data Models A collection of concepts that can be used to describe the structure of a database (data types, relationships, and constraints) basic operations (retrieval and updates) specify the dynamic aspect or behavior of a database application( user-defined operations )
  12. 12. Categories of Data Models • High-level or conceptual data models (common users) • low-level or physical data models (describe the details of how data is stored ) • in between, representational (or implementation) data models can serve both categories above
  13. 13. Conceptual Data Model • Use concepts such as – Entities:a real-world object or concept (DEPT) (COURSE) – Attributes:property of interest that further describes an entity (dept no, name, telephone, etc) – Relationships:interaction among the entities (DEPT) provides (COURSE)
  14. 14. Physical Data Model • Describes how data is stored in the computer. • It represents info such as – record formats – record orderings – access path: make search more efficient
  15. 15. Representational Data Model • Used in traditional commercial DMBS • they include – Relational Data model – Network model – Hierarchical model
  16. 16. Schemas • Is the description of the database (not database itself) – Specified during database design – Not expected to change frequently – A displayed schema is called a schema diagram (Fig 2.1) • Each object in the schema-such as STUDENT or COURSE-is a schema construct. • Schema diagram represents only some aspects of a schema (name of record type, data element and some type of constraint)
  17. 17. Instances and Database State • The data in the database at a particular moment in time is called a database state or snapshot or current set of occurrences or instances in the database • When we define a new database we have database state is empty state (schema specified only in DBMS) • The initial state when the database is first populated • Then At any point in time, the database has a current state • schema evolution: when we need to change the schema
  18. 18. The Three-Schema Architecture • Importance of using DB approach – insulation of programs and data – support of multiple user views – use of a catalog to store the database description (schema). • The aim is to separate the user application and physical DB • schema can be defined into three levels: – The internal level has an internal schema – describes the physical storage structure of the database. – uses a physical data model
  19. 19. The Three-Schema Architecture – The conceptual level has a conceptual schema describing the structure of the whole database for a community of users. – It hides the details of physical storage structures and concentrates on describing entities, data types, relationships, user operations, and constraints. – A high-level data model or an implementation data model can be used at this level. – The external or view level includes a number of external schemas or user views describing the part of the db that a particular user group is interested in and hides the rest of the db from that user group. – A high-level data model or an implementation data model can be used at this level.
  20. 20. Data Independence • Is the capacity to change the schema at one level of a database system without having to change the schema at the next higher level. • Logical data independence: capacity to change the conceptual schema without having to change external schemas or application programs. • Physical data independence: capacity to change the internal schema without having to change the conceptual (or external) schemas
  21. 21. DBMS Languages • Data Definition Language DDL: Language to specify conceptual and internal schemas for the database and any mappings between the two. • Storage definition language SDL: used when clear distinction between conceptual and internal schema. • view definition language VDL: specify user views and their mappings to the conceptual schema. • data manipulation language DML:retrieval, insertion, deletion, and modification of the data
  22. 22. DBMS Languages ….. • SQL relational database language: represents a combination of DDL, VDL, and DML, as well as statements for constraint specification and schema evolution • There are two main types of DMLs: – A high-level or nonprocedural DML : specify complex DB operations. Example SQL(set-at-a-time) – A low-level or procedural DML: retrieve individual records or objects from DB and process each separately (record-at-atime).
  23. 23. DBMS Interfaces • Menu-Based Interfaces for Browsing – menus leads to formulation of a request • Forms-Based Interfaces – display a form for each user (insert, select) – designed for naïve users. • Graphical User Interfaces (GUI) – display schema as diagram. – Utilize both menu and forms.
  24. 24. DBMS Interfaces • Natural Language Interfaces – Accept requests in native language and attempt to understand them. – Refers to words in the schema and (standard words) to interpret the request. • Interfaces for Parametric Users (eg tellers) – goal is to min the number of keystroks required. (use of function) keys • Interfaces for the DBA – creating accounts, system privileges, changing schema, etc.
  25. 25. The Database System Environment • DBMS Component Modules (fig 2.3) – – – – – – – – db & DBMS stored in disk controlled by OS. Stored data manager control access to DBMS SDM puts data in buffers in main memory DDL compiler process schema definitions and store it in meta data. Run-time-data-proc handles DB accesses @runtime receive update or retrieve and solve them on the DB Query-Compiler: handles high level queries: parse, analyze and interpret uses DB access code. Precompiler extract DML commands from app program
  26. 26. Database System Utilities • Loading: load existing files into the DB • Backup: creates backup copy of the DB • File reorganization: reorganize files for better performance • Performance monitoring: monitor DB usage and provide statistics to DBA
  27. 27. Tools, Application Environments & Communications Facilities • Case: design phase • data (information) repository: store catalog info, design decisions, usage, app program description, user information • Application Developer: e.g. power builder. Help in development of DB design, GUI, query, update etc. • Comm Software: allow users remotely to access the DB
  28. 28. Classification of DBManagement Systems • Data model: – relational, object, object-relational, hierarchical, network, and other. • Number of users supported by the system. – Single-user systems and Multiuser systems • Number of sites over which the database is distributed. – centralized, distributed DBMS (DDBMS) ,Homogeneous DDBMSs ,federated DBMS (develop software to access several autonomous preexisting databases stored under heterogeneous DBMSs. )
  29. 29. Classification of DBManagement Systems ….. • Cost of the DBMS: 10K-100K. Single 100-3K • General-purpose vs Special-purpose (When performance is a primary consideration. – Example: on-line transaction processing (OLTP) systems, which must support a large number of concurrent transactions without imposing excessive delays. )