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Introduction to Database Systems

Introduction to Database Systems. Yuri Breitbart TTH 9:15 – 10:30pm Fall 2007 rm MS115. Course Goals. This course is an introduction to the design, use, and internal workings of database management system We consider here systems that are based on relational

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Introduction to Database Systems

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  1. Introduction to Database Systems Yuri Breitbart TTH 9:15 – 10:30pm Fall 2007 rm MS115

  2. Course Goals This course is an introduction to the design, use, and internal workings of database management system 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 into relations so that the user applications may concurrently manipulate the data from database quickly and reliably. We briefly discuss the relational model and then concentrate on relational query language SQL. We continue with the study of relational database design. Finally, we study database internal storage organization and concurrency control issues.

  3. References • A. Silberschatz, H. F. Korth, S Sudarshan, Database System Concepts, 5th Ed., McGrow Hill, 2005 http://www.db-book.com • 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

  4. Prerequisites • CS 33001 – Data Structures • CS31011 – Discrete Structures • Structured Programming Language (C++) • Software engineering topics related to project documentation and project design

  5. Workload & Requirements • Project • 3 Exams during the semester and Final Exam • Project 20% of the final grade 3 Exams 15% of the final grade per each exam Final 25% of the final grade Attendance 10% • No late projects are accepted • A – 91 – 100; B – 80-90; C – 70–79; D - >64

  6. Week 1 – Database Overview Week 2 – Relational Model Week 3 – Relational Model Week 4 – SQL Week 5 – Advanced SQL Week 6 – ER Model Week 7 – Relational Database Design Theory Week 8 – Relational Database Design Theory Week 9 – Application Design and Development Week 10 –Storage and File Structures Week 11 – Indexing Week 12 - Indexing Week 13 – Query Processing Week 14 – Transaction Management Week 15– Transaction Management Class Schedule

  7. 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

  8. 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.

  9. File Management System Problems • Data redundancy • Data Access: New request-new program • Data is not isolated from the access implementation • Concurrent program execution on the same file • Difficulties with security enforcement • Integrity issues

  10. Concurrent Program Execution What is the final value of the account AC? Program1 AC=AC-50 AC #103 450 Program2 AC=AC-100

  11. 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

  12. 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.

  13. Collection of Files 60’s 70's 80's 90’s now Hierarchical Network Relational Choice for most new applications Object Bases Knowledge Bases

  14. 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

  15. 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

  16. 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

  17. 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. .

  18. 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.

  19. 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

  20. 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

  21. Physical Data - Example • Physical 10 3 6 10 3 6 james J 3 000375 0000035000 . . . . . . . . . benjamin 63

  22. 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);

  23. 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

  24. Three Level Data View –Data Abstractions . . . . . View1 View k Conceptual View Of Data Phyisal Data Storage

  25. DBMS Architecture

  26. Logical and Physical Database Components Logical • 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 Physical

  27. Database Languages Department Faculty Dept Chair Name Dept SELECT Chair FROM Faculty, DepartmentWHERE 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> SQL

  28. Data Definition Language • Specification notation for defining the database schema • E.g. create tableaccount (account-numberchar(10),balanceinteger) • 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

  29. 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

  30. Database Host Languages C, C++, Fortran, Lisp, COBOL Application prog. DBMS Host language is completely general Query language—less general "non procedural" and optimizable Calls to DB Local Vars (Memory) (Storage)

  31. 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

  32. 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

  33. 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.

  34. 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.

  35. 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

  36. 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.

  37. 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

  38. 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

  39. 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.

  40. Logical Data Models • Acollectionoftoolsfordescribing • data • datarelationships • datasemantics • dataconstraints • Valuebasedmodels: ERModel, OOModel • Record Based Models: Relational Model

  41. 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

  42. Entity-Relationship Model Example of schema in the entity-relationship model

  43. 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

  44. Object Oriented Model OBJECT DATA MODEL 1. Complex Objects – Nested Structure (pointers or references) 2. Encapsulation, set of Methods/Access functions 3. Object Identity 4. Inheritance – Defining new classes like old classes Object model: usually find objects via explicit navigation Also query language in some systems

  45. Example • Class Person{ public: Person(); ~Person(); float GetSalary(); float PutSalary(float&); string Name; int SSN; date BirthDate; private: float salary; }

  46. Object-Oriented ModelData 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

  47. 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.

  48. 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 CPU A FA Adder ALU ADDER Bill of Materials or transitive closure

  49. Relational Model Attributes Street City gpa Name Student-id • Example of tabular data in the relational model Johnson Smith Johnson Jones Smith 192-83-7465 019-28-3746 192-83-7465 321-12-3123 019-28-3746 Alma North Alma Main North 3.6 2.7 3.2 4.0 3.45 Palo Alto Rye Palo Alto Harrison Rye

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