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Introduction to Database Systems Yuri Breitbart MW 4:45 – 6:00pm Fall 2004 Course Goals This course is an introduction to the design, use and internal workings of database systems. We consider here systems that are based on relational model – that is, users data is represented as a set of two dimensional tables. During the class we learn the ways to organize the data so that the user applications may work concurrently and get data from database quickly and reliably. We first study the data modeling techniques and how to convert a data model into a set of relations. We then study SQL query language. Finally, we study database internal organization of data a concurrency control and recovery issues in database systems. References • A. Silberschatz, H. F. Korth, S Sudarshan, Database System Concepts, 4th Ed., McGrow Hill, 2002 http://www.bell-labs.com/topic/books/db-book • Hector Garcia-Molina, Jeffrey D. Ullman, Jennifer Widom, Database Systems, The Complete Book, Prentice Hall, 2002 http://www-db.stanford.edu/~ullman/dscb.html • Class notes Prerequisites • • • • CS 33001 – Data Structures CS31011 – Discrete Structures Structured Programming Language (C++) Software engineering topics related to project documentation and project design Workload & Requirements • • • • 4 Homeworks Project Midterm and Final Exams Homeworks: 20% of the final grade Project 35% of the final grade Midterm 20% of the final grade Final 25% of the final grade • No late homeworks and/or projects are accepted • A – 91 – 100; B – 80-90; C – 70–79; D - >64 Exam, Project, and Homeworks Due Dates • Homework 1 – Out: 9/08/2004 In: 9/13/2004 Homework 2 – Out: 9/13/2004 In: 9/17/2004 Homework 3 – Out: 9/20/2004 In: 9/24/2004 Homework 4 - Out: 9/27/2004 In: 10/04/2004 • Midterm 10/13/2004 • Final 12/13/2004 • Project – Out: 10/18/2004 In: 12/01/2004 • Exams are all inclusive Class Schedule • • • • • • • Week 1 – Database Overview Week 2 – ER model Week 3 – Relational Model Week 4 – Relational Model Week 5 – OO Model and XML Week 6 – OO Model and XML Week 7 – Relational Algebra • • • • • • • Week 8 - SQL Week 9 – Constraints & Triggers Week 10 –Data Storage Week 11 – Indexes Week 12 - Query Processing Week 13 – Transactions Week 14 – Recovery Project You will build a database application using Oracle. The project consists of several parts: – ER diagram for the application, – conversion of the ER diagram into a set of relations, – normalizing a set of relations, – creating database under ORACLE, – loading database, – creating ORACLE application programs, – testing the system. Programming should be done in C++. Project documentation should include: – application description, – ER diagram, – normalized set of relation, – description of each application program, – sample data for each relation, and – description on how to install and run your application. Database Overview • File Management vs Database Management • Advantages of Database systems: storage persistence, programming interface, transaction management • Three level Data Model • DBMS Architecture • Database System Components • Users classification File Management Systems • File is uninterpreted, unstructured collection of information • File operations: delete, catalog, create, rename, open, close, read, write, find, … • Access methods: Algorithms to implement operations along with internal file organization • Examples: File of Customers, File of Students; Access method: implementation of a set of operations on a file of students or customers. File Management System Problems • • • • • • • Data redundancy Data Access: New request-new program Data is not isolated from the access implementation Format incompatible data Concurrent program execution on the same file Difficulties with security enforcement Integrity issues Concurrent Program Execution What is the final value of the account AC? Program1 AC=AC-50 AC Program2 AC=AC-100 #103 450 Security Problems • • • • • Allow access to the file only to the authorized personnel Ability to restrict access to parts of the record Ability to control operation usage by different users Protection from unauthorized use Protection from the derivation of unauthorized information Data Integrity • A database constraint is a logical constraint about the data expressed in a logical language. – STUDENT.AGE >15 – If (STUDENT.CLASS ==cs43005) then (STUDENT.PRIOR_CLASS ==cs31001) • Database is consistent if data at each time satisfies all integrity constraints. • Input to any application is a set of consistent data. An application output is a set of consistent data. Collection of Files 60’s 70's Hierarchical 80's Relational Network Choice for most new applications 90’s Object Bases Knowledge Bases now Advantages of Databases • Persistent Storage – Database not only provides persistent storage but also efficient access to large amounts of data • Programming Interface – Database allows users to access and modify data using powerful query language. It provides flexibility in data management • Transaction Management – Database supports a concurrent access to the data Early Database Applications • Airline Reservation Systems – Data items are: single passenger reservations; Information about flights and airports; Information about ticket prices and tickets restrictions. • Banking Systems – Data items are accounts, customers, loans, mortgages, balances, etc. Failures are not tolerable. Concurrent access must be provided • Corporate Records – Data items are: sales, accounts, bill of materials records, employee and their dependents Modern Database Applications • Client – Server architecture – DBMS serves as a server and client queries are sent to servers – Where to locate servers • Multimedia Applications • Multidatabase Applications • Data Warehouses Three Aspects to Studying DBMS's 1. Modeling and design of databases. – Allows exploration of issues before committing to an implementation. 2. Programming: queries and DB operations like update. – SQL = “intergalactic dataspeak.” 3. DBMS implementation. . Definitions • A database is a collection of stored operational data used by various applications and/or users by some particular enterprise or by a set of outside authorized applications and authorized users • A DataBase Management System (DBMS) is a software system that manages execution of users applications to access and modify database data so that the data security, data integrity, and data reliability is guaranteed for each application and each application is written with an assumption that it is the only application active in the database. What Is Data ? • Different view points: – A sequence of characters stored in computer memory or storage – Interpreted sequence of characters stored in computer memory or storage – Interpreted set of objects Data Levels and their Roles • Physical – corresponds to the first view of data: How data is stored, how is it accessed, how data is modified, is data ordered, how data is allocated to computer memory and/or peripheral devices, how data items are actually represented (ASCI, EBCDIC,…) • Conceptual – corresponds to the second view of data: What we want the data to express and what relationships between data we must express, what “ story” data tells, are all data necessary for the “story’ are discussed. • View – corresponds to the third view of data:What part of the data is seen by a specific application Physical Data - Example • Physical 10 benjamin 3 63 6 10 J 0000035000 james 3 3 6 000375 . . . . . . . . . Examples • Conceptual 1 TA 2 Name char(10), 2 Age char (3), 2 Salary Fixed Dec(6); 1 Student 2 Name char(10), 2 Year-of_study char(3) 2 GPA Fixed Dec(5,2); Examples 1 STUDENTS-TA 2 Name char(25), 2 Age char (3), 2 Salary Fixed Dec(8,2), 2 Year-of_study char(3) 2 GPA Fixed Dec(3,2); A view Three Level Data View – Data Abstractions View1 . . . Conceptual View Of Data Phyisal Data Storage . . View k DBMS Architecture Logical and Physical Database Components • Data Definition Language (DDL) • • • • • Data Manipulation Language (DML) Host Language Interface Data Administrator Users Query Processor – Compiler – Optimizer • Management – Transaction Manager – File Manager – Buffer Manager – Authorization and Integrity Manager Logical Physical Database Languages Department Faculty Name Dept Dept Chair SQL SELECT Chair FROM Faculty, Department WHERE Faculty.name = “Ken Noname” AND Faculty.Dept = Department.Dept Data definition language (DDL) ~ like type definitions in C or C++ Data Manipulation Language (DML) Query (SELECT) UPDATE < relation name > SET <attribute> = < new-value> WHERE <condition> Data Definition Language • Specification notation for defining the database schema – E.g. 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 (i.e., 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 Data Manipulation Language • Language for accessing and manipulating the data organized by the appropriate data model • 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 query language Database Host Languages C, C++, Fortran, Lisp, COBOL Application prog. Calls to DB DBMS Local Vars (Memory) (Storage) Host language is completely general Query language—less general "non procedural" and optimizable Data 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 Database Users • Naïve – do not know about database too much, invoke application programs that are prepared already • Application Programmers – know how to interact with the system but may not know how DBMS is designed • Sophisticated users that know advanced use of the system and can use the system and packages on the top of the system • DBMS system users – write specialized database applications that do not fit into the traditional data processing framework Query Processor • Compiler – verifies whether a program or query is written in accordance with DDL and DML rules • Optimizer – Finds the most effective way to access the required data and supply it in a user requested form. Monitors the query execution and modifies a query evaluation plan if necessary. 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. • Concurrency-control manager controls the interaction among the concurrent transactions, to ensure the consistency of the database. 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. • The storage manager is responsible to the following tasks: – interaction with the file manager – efficient storing, retrieving and updating of data File Manager • File Manager is responsible for mapping logical database units (objects, relations, etc.) into a set of low level files. • It is responsible for maintenance of files and indexes on them. It should be able to create and destroy index and collect unused storage space to eliminate an unneeded gaps on disks. Buffer Manager • Buffer Manager is responsible for the allocation and maintenance buffer space in a memory to facilitate processing database data by several concurrent applications. • Buffer Manager decides when to load data from a buffer to a database or discard the data and under what conditions a new data should be put into a buffer Authorization and Integrity Manager • This manager is responsible for granting an access to database or portions thereof only to authorized users and preventing the access to unauthorized users • Integrity manager must assure data integrity during normal database operations as well as during the database failures The DBMS Marketplace • Relational DBMS companies – Oracle, Sybase – are among the largest software companies in the world. • IBM offers its relational DB2 system. With IMS, a nonrelational system, IBM is by some accounts the largest DBMS vendor in the world. • Microsoft offers SQL-Server, plus Microsoft Access for the cheap DBMS on the desktop, answered by “lite” systems from other competitors. • Relational companies also challenged by “object-oriented DB” companies. • But countered with “object-relational” systems, which retain the relational core while allowing type extension as in OO systems. Logical Data Models • A collection of tools for describing – data – data relationships – data semantics – data constraints • Value based models: ER Model, OO Model • Record Based Models: Relational Model Entity-Relationship Model • The enterprise data can be described as a set of entities and a set of relationships between them. • Entity – a data that pertains to, or describes some component of the enterprise • Each entity is characterized by a set of attributes • Relationship – describes an interconnection between different entities • Entity Set – a set of entities that are characterized by the same entity definition • Relationship Set – a set of relationships of the same type Entity-Relationship Model Example of schema in the entity-relationship model Object – Oriented Model • An enterprise is described as a collection of objects and a collection of algorithms that work with objects • Example: Person is an object. • Object is characterized by a set of public attributes. Applications may refer only to public attributes; private attributes . Algorithms that implement the object may refer to private attributes; a set of protected attributes and a set of methods • Attribute of an object can be another object • Objects are nested into a hierarchy and can inherit attributes of their parents Object Oriented Model OBJECT DATA MODEL 1. 2. 3. 4. Complex Objects – Nested Structure (pointers or references) Encapsulation, set of Methods/Access functions Object Identity Inheritance – Defining new classes like old classes Object model: usually find objects via explicit navigation Also query language in some systems Example • Class Person{ public: Person(); ~Person(); float GetSalary(); float PutSalary(float&); string Name; int SSN; date BirthDate; private: float salary; } Object-Oriented Model Data Encapsulation • An object contains both data and methods to work with the data • The physical data representation is visible only to the object creator. • The implementation details of methods are not visible to object users • An interface of the object consists of public attributes and methods • Each object is characterized by an object identity Relational Model • An enterprise is represented as a set of relations • Domain – is a set of atomic values. Each domain has a NULL value. • Data type – Description of a form that domain values can be represented. • Relation is a subset of a cartesian product of one or more domains • The elements of relations are called tuples. Each element in the cartesian product is called attribute. Relational model is good for: Large amounts of data —> simple operations Navigate among small number of relations Difficult Applications for relational model: • VLSI Design (CAD in general) • CASE • Graphical Data ALU ADDER A FA CPU Adder ALU ADDER Bill of Materials or transitive closure Attributes Relational Model Student-id Name 192-83-7465 Johnson 019-28-3746 Smith 192-83-7465 Johnson 321-12-3123 Jones 019-28-3746 Smith Street City gpa • Example of tabular data in the relational model Alma Palo Alto 3.6 North Rye 2.7 Alma Palo Alto 3.2 Main Harrison 4.0 North Rye 3.45