Introduction to Database Management System

Introduction To Database Management System CSE– SE– Database Management System Prachi Shahane Assistant Professor Dept. of Computer Engineering, SIES Graduate School of Technology...

Introduction To Database Management System CSE– SE– Database Management System Prachi Shahane Assistant Professor Dept. of Computer Engineering, SIES Graduate School of Technology 1 Prachi Shahane CSC403-Database Management System Credit-3 Course Objectives: 1 Develop entity relationship data model and its mapping to relational model 2 Learn relational algebra and Formulate SQL queries 3 Apply normalization techniques to normalize the database 4 Understand concept of transaction, concurrency control and recovery techniques. Course Outcomes: 1 Recognize the need of database management system 2 Design ER and EER diagram for real life applications 3 Construct relational model and write relational algebra queries. 4 Formulate SQL queries 5 Apply the concept of normalization to relational database design. 6 Describe the concept of transaction, concurrency and recovery. 2 Prachi Shahane Module 1 Introduction Database Concepts 1 Introduction, Characteristics of databases, File system v/s Database system, Data abstraction and data Independence, DBMS system architecture, Database Administrator 3 Prachi Shahane  4 Prachi Shahane  Database Management System (DBMS) DBMS contains information about a particular enterprise Collection of interrelated data Set of programs to access the data An environment that is both convenient and efficient to use Database Applications: Banking: transactions Airlines: 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 Databases can be very large. Databases touch all aspects of ourPrachi lives Shahane University Database Example Prachi Shahane Drawbacks of using file systems to store data 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) become “buried” in program code rather than being stated explicitly Hard to add new constraints or change existing ones Prachi Shahane Drawbacks of using file systems to store data (Cont.) 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 access needed for performance Uncontrolled concurrent accesses can lead to inconsistencies Example: Two people reading a balance (say 100) and updating it by withdrawing money (say 50 each) at the same time Security problems Hard to provide user access to some, but not all, data Database systems offer solutions to all the above problems Prachi Shahane Data Models A collection of tools for describing Data Data relationships Data semantics Data constraints Relational model Entity-Relationship data model (mainly for database design) Object-based data models (Object-oriented and Object-relational) Semistructured data model (XML) Other older models: Network model Hierarchical model Prachi Shahane Relational Model Relational model (Chapter 2) Example of tabular data in the relational model Columns Rows Prachi Shahane A Sample Relational Database Prachi Shahane Data Definition Language (DDL) Specification notation for defining the database schema Example: create table instructor ( ID char(5), name varchar(20), dept_name varchar(20), salary numeric(8,2)) DDL compiler generates a set of table templates stored in a data dictionary Data dictionary contains metadata (i.e., data about data) Database schema Integrity constraints Primary key (ID uniquely identifies instructors) Referential integrity (references constraint in SQL) e.g. dept_name value in any instructor tuple must appear in department relation Authorization Prachi Shahane SQL SQL: widely used non-procedural language Example: Find the name of the instructor with ID 22222 select name from instructor where instructor.ID = ‘22222’ Example: Find the ID and building of instructors in the Physics dept. select instructor.ID, department.building from instructor, department where instructor.dept_name = department.dept_name and department.dept_name = ‘Physics’ Application programs generally access databases through one of Language extensions to allow embedded SQL Application program interface (e.g., ODBC/JDBC) which allow SQL queries to be sent to a database Chapters 3, 4 and 5 Prachi Shahane Database Design? Is there any problem with this design? Prachi Shahane Design Approaches Prachi Shahane The Entity-Relationship Model What happened to dept_name of instructor and student? Prachi Shahane Storage Management Prachi Shahane  Query Processing 1. Parsing and translation 2. Optimization 3. Evaluation Prachi Shahane Transaction Management What if the system fails? What if more than one user is concurrently updating the same data? A transaction is a collection of operations that performs a single logical function in a database application Transaction-management component ensures that the database remains in a consistent (correct) state despite system failures (e.g., power failures and operating system crashes) and transaction failures. Concurrency-control manager controls the interaction among the concurrent transactions, to ensure the consistency of the database. Prachi Shahane Database System Internals Prachi Shahane Database Architecture The architecture of a database systems is greatly influenced by the underlying computer system on which the database is running: Centralized Client-server Parallel (multi-processor) Distributed Prachi Shahane History of Database Systems Prachi Shahane History (cont.) 1980s: Research relational prototypes evolve into commercial systems SQL becomes industrial standard Parallel and distributed database systems Object-oriented database systems 1990s: Large decision support and data-mining applications Large multi-terabyte data warehouses Emergence of Web commerce Early 2000s: XML and XQuery standards Automated database administration Later 2000s: Giant data storage systems Google BigTable, Yahoo PNuts, Amazon,.. Prachi Shahane Thank You! ([email protected]) 33 Prachi Shahane