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Beginning Of DBMS (data base)
- 2. What is DBMS • Database – Is a collection of related Data. – By data, we mean known facts that can be recorded and that have implicit meaning. For example, consider the names, telephone numbers, and addresses of the people you know. • Database Management System (DBMS) – Collection of programs that enables users to create and maintain a database. – DBMS contains information about a particular enterprise – Set of programs to access the data – An environment that is both convenient and efficient to use.
- 3. Database System Applications – Banking: all transactions – Airlines and Hotel: reservations, schedules – Universities: registration, grades – Sales: customers, products, purchases. – Online retailers: order tracking, customized recommendations – Manufacturing: production, inventory, orders, supply chain – Human resources: employee records, salaries, tax deductions
- 4. • IBM DB2 • Microsoft SQL Server • Oracle • MySQL • MariaDB • PostgreSQL • SQLite • Microsoft Access • SAP HANA • Dbase • FoxPro • LibreOffice Base • FireMaker Pro • InterSystems Cache
- 5. The Evolution of a Database Sql server 1.0 1987 (with sybase) sql server 4.2 for window NT 1992 (with sybase) sql server 6.0 june 1995 Exclusively sql server 6.5 april 1996 sql server 7.0 december 1998 Sphnix sql server 2000 august 2000 shiloh sql server 2005 Yukon (oracle killer) sql server 2008 august 2008 sql server 2012 2012 denali
- 6. • Informix 11.7 May 26, 2012 "Panther" • Oracle 12c Standard edition , Enterprise Edition • Oracle 11g Release 2 • Oracle 11g Express Edition
- 7. • what is DBA – The function of managing and maintaining database management systems (DBMS) • Responsibility of DBA ? – Installation , Configuring, and upgrading – Maintain Backup & recovery – Grant and Revoke Access Permissions. – Maintenance & performance monitoring.
- 9. Drawbacks of File Management System / Purpose of Database Systems – Data redundancy and inconsistency • Multiple file formats, duplication of information in different files – Difficulty in accessing data • Need to write a new program to carry out each new task – Data isolation — multiple files and formats – Integrity problems • Integrity constraints (e.g. account balance > 0) • Hard to add new constraints or change existing ones
- 10. – Atomicity of updates • Failures may leave database in an inconsistent state with partial updates carried out • Example: Transfer of funds from one account to another should either complete or not happen at all – Concurrent access by multiple users • Concurrent accessed needed for performance • Uncontrolled concurrent accesses can lead to inconsistencies – Example: Two people reading a balance and updating it at the same time – Security problems • Hard to provide user access to some, but not all, data
- 11. Advantages of DBMS • Controlling Redundancy • Restricting Unauthorized Access • Centralized Control • Backup and Recovery • Enforcing Integrity Constraints • Providing Multiple User Interface • Shared Data • Representing Complex Relationship among Data
- 12. Disadvantages of DBMS • Number of problems are associated with centralized data. • Cost of hardware and software • Complexity of Backup and Recovery mechanism.
- 13. DBMS Architecture • Two Level Architecture – Client / Server Architecture. – A standard called Open Database Connectivity (ODBC) provides an application programming interface (API), which allows client-side programs to call the DBMS, as long as both client and server machines have the necessary software installed. • Three level Architecture – The goal is to separate user applications and physical database – A major purpose of database system is to provide users with an abstract view of the data
- 14. • In a basic client/server DBMS architecture, two types of modules. – A client module • user workstation or personal computer. user interface and application programs. – A server module • Data storage, access, search, and other functions. query server or transaction server
- 15. Three-Tier and n-Tier Architectures for Web Applications This intermediate layer or middle tier is called the application server or the Web server,
- 16. Three level Schema Architecture
- 18. Data Abstraction • Hiding details of data organization and storage. • different users can perceive data at their preferred level of detail.
- 20. Mapping • Process of transforming the request and result between different level is called as mapping. – External / conceptual mapping : – Conceptual / Internal mapping
- 21. Data Independence • We can define two types of data independence – Logical data independence is the capacity to change the conceptual schema without having to change external schemas or application programs – Physical data independence is the capacity to change the internal schema without having to change the conceptual schema.
- 23. Database State or Snapshot • Actual data in the database may change frequently • The data in the database at a particular moment in time is called a database state or snapshot • Also called the current set of occurrences or instances in the database
- 24. Database Schema vs. Database State • The distinction is very important • When we define a database, we specify its database schema only to the DBMS – Database state is the empty state (w/ no data) – Initial state: when the database is first populated or loaded with initial data – Current State: State at any point in time. Every time an update operation is applied to the database, database state changes
- 25. • Valid State: A state that satisfies the structure and the constraints specified in the schema The DBMS is partly responsible for ensuring that every state of the database is a valid state • The schema is sometimes called the intension, and a database state is called an extension of the schema
- 26. Data Models, Schemas, and Instances • Data model—a collection of concepts that can be used to describe the structure of a database. • By structure of a database we mean the data types, relationships, and constraints that apply to the data. – High-level or conceptual data models : users perceive data. Use concept such as entities, attributes, and relationships. – low-level or physical data models: details of how data is stored.
- 27. • An entity represents a real-world object or concept. – such as an employee or a project • An attribute represents some property of interest – employee’s name or salary. • A relationship among two or more entities represents an association among the entities. – works-on relationship between an employee and a project. • Scheme : The description and overall design of a database is called the database schema. • Instance : The collection of information stored in the database at a particular moment is called an instance.
- 30. DBMS Component Modules • The top part of the figure refers to the various users of the database environment and their interfaces. • The lower part shows the internals of the DBMS responsible for storage of data and processing of transactions. • Access to the disk is controlled primarily by the operating system (OS), which schedules disk read/write. • Reducing disk read/write improves performance considerably. • Many DBMSs have their own buffer management module to schedule disk read/write, • A higher-level stored data manager module of the DBMS controls access to DBMS information.
- 31. Different Users • DBA staff: who define, monitor and Control the whole Database access and performance. • Casual users / Sophisticated User: who work with interactive interfaces to formulate queries. • Application programmers : who create programs using some host programming languages. • Parametric users/ Naive user/ Web user : who do data entry work by supplying parameters to predefined transactions.
- 32. • Storage Data Manager : minimize the movement of data between the disk and main memory. – Buffer manager : Fetch data from disk storage into main memory. And decide what data to cache in main memory. – File manager: Manage the allocation of space on disk storage and data structure used to represent info. – Authorization and integrity Manager: test for satisfaction of integrity constraints, and authority of user to access the data. – Transaction Manager: ensure that the database remain in consistent state.
- 33. • The DDL compiler processes schema definitions and stores descriptions of the schemas (meta-data) in the DBMS catalog. • The catalog includes information such as the names and sizes of files, names and data types of data items, storage details of each file, mapping information among schemas, and constraints. • query optimizer is concerned with the rearrangement and possible reordering of operations, elimination of redundancies, and use of correct algorithms and indexes during execution. • Application programmers write programs in host languages such as Java, C, or C++. • The Precompiler extracts DML commands from an application program written in a host programming language. • These commands are sent to the DML compiler for compilation into object code for database access. • The rest of the program is sent to the host language compiler. • The object codes for the DML commands and the rest of the program are linked, forming a canned transaction • Canned transactions are executed repeatedly by parametric users, who simply supply the parameters to the transactions. Each execution is considered to be a separate transaction. An example is a bank withdrawal transaction where the account number and the amount may be supplied as parameters.
- 34. • Runtime database processor executes – (1) the privileged commands, (2) the executable query plans, and (3) the canned transactions with runtime parameters. It works with the system catalog and also works with the stored data manager. – The runtime database processor handles other aspects of data transfer, such as management of buffers in the main memory.
- 35. Database Languages • To perform operations on schema and data. • DDL : data definition language. Deal with structure of the database. • DML : data manipulation language. • DCL : data control language. Control access to database.
- 36. Categories of data models • Relational Model • ER Model • Object based model • Semi structured data model
- 37. Representational or implementation data models • Entity-Relationship Model • Relational data model • Network data model. • Hierarchical data models. • Object-Oriented data model.
- 38. Logical structure (schema) of a database can be expressed graphically by an E-R diagram • Rectangles- which represent entity sets • Ellipses- which represent attributes • Diamonds- which represent relationships among entity sets • Lines- which link attributes to entity sets and entity sets to relationships.