Faculty of Computer and Information Communication Solution-based Database System Concepts 4th ED Chapter 1. Introduction Faculty of Computer and Information Communication 2019-05-01 Silberschartz-Korth-Byun

Solution-based Course This lecture is run with some solution-based subjects adapted to each chapter. The solution includes some topics needed in real business applications. Through this lecture, students can get an indirect experience. The courseware writing is supported by NURI of ministry of education. 2019-05-01 Silberschartz-Korth-Byun

Silberschartz-Korth-Byun Contents Purpose of Database Systems View of Data Data Models Data Definition Language Data Manipulation Language Transaction Management Storage Management Database Administrator Database Users Overall System Structure 2019-05-01 Silberschartz-Korth-Byun

Database Management System (DBMS) Collection of interrelated data + a set of programs to access them Database contains information relevant to an enterprise The primary goal of a DBMS is to provide a way to store and retrieve database information that is both convenient and efficient. Database system are designed to manage large bodies of information. Management of data involves both: defining structures for storage of information providing mechanisms for the manipulation of information ensuring the safety despite system crashes or attempts at unauthorized access. 2019-05-01 Silberschartz-Korth-Byun

Silberschartz-Korth-Byun DBMS (cont.) Database Applications: Banking: Customer Information, accounts, loans, banking trans. Airlines: reservations, schedule information in a geographically distributed manner Universities: student information, course registration, grades Credit and transaction, Telecommunication, Finance Sales: customers, products, purchases Manufacturing: production, inventory, orders, supply chain Human resources: employee records, salaries, tax deductions Databases touch all aspects of our lives 2019-05-01 Silberschartz-Korth-Byun

Purpose of Database System Major drawbacks of file processing system: 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 different formats Integrity problems Integrity constraints (e.g. account balance > 0) become part of program code Hard to add new constraints or change existing ones 2019-05-01 Silberschartz-Korth-Byun

Purpose of Database Systems (Cont.) Drawbacks of using file systems (cont.) Atomicity of updates Failures may leave database in an inconsistent state with partial updates carried out E.g. 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 E.g. two people reading a balance and updating it at the same time Security problems Database systems offer solutions to all the above problems 2019-05-01 Silberschartz-Korth-Byun

Silberschartz-Korth-Byun Levels of Abstraction Physical level describes how a record (e.g., customer) is stored. Logical level: describes data stored in database, and the relationships among the data. Record type of Pascal-like high-level language: type customer = record name : string; street : string; city : integer; end; View level: application programs hide details of data types. Views can also hide information (e.g., salary) for security purposes. 2019-05-01 Silberschartz-Korth-Byun

Silberschartz-Korth-Byun Data hierarchy? Physical unit bit < nibble < byte Logical Unit field < record < file < DB 2019-05-01 Silberschartz-Korth-Byun

View of Data An architecture for a database system 2019-05-01 Silberschartz-Korth-Byun

Silberschartz-Korth-Byun Instances and Schemas Similar to types and variables in programming languages Databases change over time as information is inserted and deleted Schema – the logical structure of the database e.g., the database consists of information about a set of customers and accounts and the relationship between them) Analogous to type information of a variable in a program Physical schema: database design at the physical level Logical schema: database design at the logical level Instance – the actual content of the database at a particular moment: Analogous to the value of a variable 2019-05-01 Silberschartz-Korth-Byun

Instances and Schemas (cont.) Physical Data Independence – the ability to modify the physical schema without changing the logical schema Applications depend on the logical schema In general, the interfaces between the various levels and components should be well defined so that changes in some parts do not seriously influence others. 2019-05-01 Silberschartz-Korth-Byun

Silberschartz-Korth-Byun Data Models Underlying the structure of a database A collection of tools for describing data data relationships,data semantics,data constraints Entity-Relationship model a perception of a real world: a collection of basic objects, entities and relationship among them Relational model a collection of tables to represent both data and the relationships among the data Other models: object-oriented model,semi-structured data models( XML ), network model and hierarchical model 2019-05-01 Silberschartz-Korth-Byun

Entity-Relationship Model -Example of schema in the entity-relationship model Rectangles, which represent entity sets Ellipses, which represents attributes Diamonds, which represent relationship among entity sets Lines, which link attributes to entity sets and entity sets to relationship 2019-05-01 Silberschartz-Korth-Byun

Entity Relationship Model (Cont.) E-R model of real world Entities (objects) E.g. customers, accounts, bank branch Relationships between entities E.g. Account A-101 is held by customer Johnson Relationship set depositor associates customers with accounts Widely used for database design Database design in E-R model usually converted to design in the relational model (coming up next) which is used for storage and processing 2019-05-01 Silberschartz-Korth-Byun

Silberschartz-Korth-Byun Relational Model Example of tabular data in the relational model. Attributes customer- name customer- street customer- city account- number Customer-id 192-83-7465 019-28-3746 321-12-3123 Johnson Smith Jones Alma North Main Palo Alto Rye Harrison A-101 A-215 A-201 A-217 -each table has multiple columns, which has a unique name. 2019-05-01 Silberschartz-Korth-Byun

A Sample Relational Database 2019-05-01 Silberschartz-Korth-Byun

Silberschartz-Korth-Byun Data Language DDL(data definition language) Specification notation for defining the database schema create table account ( account-number char(10), balance integer) DDL compiler generates a set of tables stored in a data dictionary Data dictionary contains metadata Data about data. database schema Data storage and definition language language in which the storage structure and access methods used by the database system are specified Usually an extension of the data definition language 2019-05-01 Silberschartz-Korth-Byun

Data Manipulation Language (DML) Language for accessing and manipulating the data organized by the appropriate data model DML also known as query language Two classes of languages Procedural – user specifies what data is required and how to get those data Nonprocedural – user specifies what data is required without specifying how to get those data SQL is the most widely used nonprocedural query language 2019-05-01 Silberschartz-Korth-Byun

SQL(Structure Query Language) SQL: widely used non-procedural language E.g. find the name of the customer with customer-id 192-83-7465 select customer.customer-name from customer where customer.customer-id = ‘192-83-7465’ E.g. find the balances of all accounts held by the customer with customer-id 192-83-7465 select account.balance from depositor, account where depositor.customer-id = ‘192-83-7465’ and depositor.account-number = account.account-number 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 2019-05-01 Silberschartz-Korth-Byun

Silberschartz-Korth-Byun Database Users Users are differentiated by the way they expect to interact with the system Naive users – invoke one of the permanent application programs that have been written previously E.g. bank tellers involve a program called transfer. Application programmers – interact with system through DML calls Sophisticated users – interact with the system without writing programs and form requests in a database query language Specialized users – write specialized database applications that do not fit into the traditional data processing framework eg) CAD, KB, expert systems 2019-05-01 Silberschartz-Korth-Byun

Database Administrator Coordinates all the activities of the database system; the database administrator has a good understanding of the enterprise’s information resources and needs. Database administrator's duties include: Schema definition Storage structure and access method definition Schema and physical organization modification Granting user authority to access the database Specifying integrity constraints Acting as liaison with users Monitoring performance and responding to changes in requirements 2019-05-01 Silberschartz-Korth-Byun

Transaction Management 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. “all or none” or “all or nothing” Concurrency-control manager controls the interaction among the concurrent transactions, to ensure the consistency of the database. 2019-05-01 Silberschartz-Korth-Byun

Database System Structure Storage Manager is a program module that provides the interface between the low-level data stored in the database and the application program and queries. interaction with the file manager efficient storing, retrieving and updating of data components: Authorization and integrity manager Transaction manager File manager Buffer manager Physical System Implementation: Data files, Data dictionary, Indices 2019-05-01 Silberschartz-Korth-Byun

Database System Structure (cont.) The Query Processor DDL interpreter DML compiler Query evaluation engine 2019-05-01 Silberschartz-Korth-Byun

Application Architecture Two-tier architecture client database sever Three-tier architecture application server database server 2019-05-01 Silberschartz-Korth-Byun

Overall System Structure 2019-05-01 Silberschartz-Korth-Byun

Application Architectures Two-tier architecture: E.g. client programs using ODBC/JDBC to communicate with a database Three-tier architecture: E.g. web-based applications, and applications built using “middleware” 2019-05-01 Silberschartz-Korth-Byun

Silberschartz-Korth-Byun 데이터베이스 시스템의 역사 1950년대와 1960년대 초반 천공카드 입력, 자기테이프 저장, 월급지급 자동화 => 순차파일 방식 처리 1960년대 후반 ~ 1970년대 하드디스크로 획기적 자료처리, 자료구조 기반 네트워크 또는 계층 DB 등장 1970 Codd 관계형 모델 정의, 비절차적 질의 방식 제안, RDBS 탄생, Codd 튜링상 수상 1980년대 시스템 성능 저조, IBM의 시스템 R에 의한 상황변화로 SQL/DS 탄생, 이후 IBM DB2, Oracle, Ingres, DEC Rdb이 효율적 질의 처리 기법 발전 80년대 초반, 관계형 모델이 계층모델이나 네트웤 모델의 성능 추월 경쟁력 갖춤 2019-05-01 Silberschartz-Korth-Byun

Silberschartz-Korth-Byun 데이터베이스 시스템의 역사(계속) 1980년대(계속) 선언적 질의 작성으로 사용하기 매우 쉽다. 1980대 이후 관계형 모델은 제왕적 위치 또한 이 시기에 병렬,분산 데이터베이스 연구 활발, 객체지형 데이터베이스 태동 1990년대 초반 트랜잭션 처리 중심에서 의사결정 시스템과 질의 처리가 주요 응용으로 부상, 대량의 자료 분석 도구 발달 1990년대 후반 웹의 발전으로 db의 초고속처리, 매우 견고한 신뢰성 확보 24 X 7 가용성 갖춤 웹 인터페이스 갖춤 2019-05-01 Silberschartz-Korth-Byun