Relational Databases - Lecture 1 - Introduction
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Introduction the the relational databases class
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Relational Databases - Lecture 1 - Introduction
- 2. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Objectives • Understand the basics of • relational model • database organisation • theoretical foundation • SQL language • Learn • to read and to understand models • to model databases • basic management and query
- 3. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Planning • Modelling and design of databases • Conceptual model • Logical model • Physical model • Managing and querying • SQL
- 4. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Practical work • TD1 - ER diagram • TD2 - Logical and physical models • TD3 - Understand SQL basics • TD4 - SQL queries • TD5 - SQL-injection
- 7. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Database • An organized collection of data. • A collection of information that is organized so that it can easily be accessed, managed, and updated. • A structured set of data held in a computer, especially one that is accessible in various ways.
- 8. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Why database? • Manage many data • Access, add, modify and delete data easily • Avoid redundancy • Keep data up-to-date • Keep coherence in the data • Keep data integrity • Allow multiple users • Be efficient and keep data accurate
- 9. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Relational database • Invented by Edgar Frank "Ted" Codd, IBM, 1970 • Present data as relations - collection of tables • Tables consists of rows and columns • Relational algebra - theoretical foundation • Relational database management system (RDBMS) • Used by all major commercial database systems • High-level query language
- 13. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Example • University application example • SSN and name • Universities student is applying to • High school attended and it’s location • Hobbies Apply(SSN, stName, university, HS, HSlocation, hobby) SSN stName university HS HSlocation hobby
- 14. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Example Mary (SSN 567) from Marie Curie College in Troyes plays tennis and piano and applies to UTT, PSB and Stanford. SSN stName university HS HSlocation hobby 567 Mary UTT Marie Curie Troyes tennis 567 Mary PSB Marie Curie Troyes tennis 567 Mary Stanford Marie Curie Troyes tennis 567 Mary UTT Marie Curie Troyes piano … … … … … …
- 15. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Design “anomalies” SSN stName university HS HSlocation hobby 567 Mary UTT Marie Curie Troyes tennis 567 Mary PSB Marie Curie Troyes tennis 567 Mary Stanford Marie Curie Troyes tennis 567 Mary UTT Marie Curie Troyes piano … … … … … … • Redundancy • Update anomaly • Delete anomaly
- 16. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Split the table • No anomalie • No lost data • Student (SSN, Name) • Apply (SSN, University) • StudentHS(SSN, HS, HSlocation) • StudentHobby(SSN, hobby)
- 19. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Exercise 1 Apply(SSN, studentName, university) SSN studentName university 567 Mary UTT 567 Mary PSB 567 Mary Stanford 567 Mary TKK … … …
- 20. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Exercise 1 Student(SSN, studentName) Apply(SSN, university) SSN studentName 567 Mary SSN university 567 UTT 567 PSB 567 Stanford Student Apply
- 21. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Exercise 2 Apply(SSN, highSchool, university) SSN highSchool university 567 Marie Curie UTT 567 Marie Curie PSB 567 Marie Curie Stanford 567 Paris 13 UTT … … …
- 22. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Exercise 2 Studied(SSN, highSchool) Apply(SSN, university) SSN highSchool 567 Marie Curie 567 Paris 13 SSN university 567 UTT 567 PSB 567 Stanford Studied Apply
- 23. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Exercise 3 Took(studentID, studentName, courseNum, courseTitle) University wants to keep records of all students taking courses. Students have a unique student ID and a name; courses have a unique course number and a title. Each tuple in the relation encodes the fact that the given student took the given course. • Give the schema of the relation where all attributes are stored together? • Is it optimised?
- 24. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Exercise 3 Student(studentID, name) Course(courseNumber, title) Took(studentID, courseNumber) studentID name 123 Nick 134 Pole studentNumber courseNumber 123 IF26 123 RE21 134 IF26 Student Took courseNum title IF26 Data storage RE21 Java Course
- 25. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Exercise 4 Apply(studentID, universityName, applicationDate, major) • Is it optimised? • Student can apply for only one major in only one university • Student can apply for each major in each university only once. • Student can apply for each major in each university multiple times.
- 26. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Exercise 5 Course(courseID, courseName, teacherName) • Is it optimised? • Course can be lectured by one teacher • Course can be lectured by many teachers
- 27. 1 0 1 0 0 1 0 1 0 1 0 0 1 0 1 0 0 1 0 0 1 0 ✐ ✐ ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ ✐ ✑ ✐ ✑ ✑ 1 1 1 0 0 1 0 1 0 0 1 1 0 0 1 1 1 0 0 0 1 0 1 1 ✑ ✐ ✑ ✐ ✐ ✑ ✑ ✐ ✐ ✑ ✐ 1 1 1 0 0 1 0 1 0 0 1 0 1 0 0 1 1 0 1 0 1 1 0 1 1 0 0 1 ✑ ✑ 1 ✑ ✑ 1 0 1 Exercise 6 University(name, country) UniversitySize(name, enrolment) UniversityScore(name, score) UniversityMajor(name, majorName) UniversityPhone(name, phoneNum) UniversityLocation(name, location) • Is it optimised? • Is it a good design?