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Chapter 1 Introduction

Chapter 1 Introduction. Yonsei University 1 st Semester, 2013 Sanghyun Park. Database Management System (DBMS). Collection of interrelated data Set of programs to access the data DBMS contains information about a particular enterprise

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Chapter 1 Introduction

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  1. Chapter 1Introduction Yonsei University 1st Semester, 2013 Sanghyun Park

  2. Database Management System (DBMS) • Collection of interrelated data • Set of programs to access the data • DBMS contains information about a particular enterprise • DBMS provides an environment that is both convenient and efficient to use • Databases touch all aspects of our lives

  3. Purpose of Database System • In the early days, database applications were built on top of file systems • Drawbacks of using file systems to store data: • Data redundancy and inconsistency • Difficulty in accessing data • Integrity problems • Atomicity of updates • Concurrent access by multiple users • Security problems • DBMS offers solutions to all the above problems

  4. View of Data • An architecture for a database system

  5. Data Models • A collection of tools for describing • Data • Data relationships • Data semantics • Data constraints • Entity-Relationship model • Relational model • Other models: • Object-oriented model, semi-structured data models • Older models: network model and hierarchical model

  6. Entity-Relationship Data Model

  7. Relational Model

  8. Data Definition Language (DDL) • Language for defining the database structure create table instructor (ID char(5),name varchar(20), dept_name varchar(20), salary numeric(8,2) ) • Execution of the above DDL statement creates the instructor table • In addition, it updates a special set of tables called the data dictionary

  9. Data Manipulation Language (DML) • Language for accessing and manipulating the data organized by the appropriate data model • Procedural DMLs require a user to specify what data are needed and how to get those data • Declarative (or Nonprocedural) DMLs require a user to specify what data are needed without specifying how to get those data • It is common to use the terms query language and data manipulation language synonymously • SQL is the most widely used query language

  10. Database Access From Applications • Application programs are programs that are used to interact with the database • Application programs are usually written in a host language, such as Cobol, C, C++, or Java • Application programs generally access databases through one of: • Language extensions to allow embedded SQL • Application program interface (e.g., ODBC/JDBC) which allows SQL queries to be sent to a database

  11. Application Architecture • Two-tier architecture: E.g. client programs using ODBC/JDBC to communicate with a database • Three-tier architecture: E.g. web-based applications

  12. Overall Database System Structure

  13. Storage Management • Storage manager is a program module that provides the interface between the low-level data stored in the database and the application programs and queries submitted to the system • Issues • Storage access • File organization • Indexing and hashing

  14. Query Processing • Parsing and translation • Optimization • Evaluation

  15. 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 and transaction failures • Concurrency-control manager controls the interaction among the concurrent transactions, to ensure the consistency of the database

  16. History of Database Systems (1/2) • Late 1960s and 1970s • Network and hierarchical data models in widespread use • Ted Codd defines the relational data model(Win the ACM Turing Award for this work)(IBM Research begins System R prototype)(UC Berkeley begins Ingres prototype) • 1980s • Research relational prototypes evolve into commercial systems(SQL becomes industrial standard) • Parallel and distributed database systems • Object-oriented database systems

  17. History of Database Systems (2/2) • 1990s • Large decision support and data-mining applications • Large multi-terabyte data warehouses • Emergence of Web commerce • 2000s • XML and XQuery standards • Automated database administration

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