Database Design and MySQL

1. Database Design and MySQL Session 4 INFM 718N Web-Enabled Databases

2. Agenda • Database design • MySQL • Project teams: next steps • (if we have time) Programming

3. (PC) Interface Design (IE, Firefox) Client-side Programming (JavaScript) Interaction Design Interchange Language (HTML, XML) Server-side Programming (PHP) Business rules (MySQL) (PC, Unix) • Relational normalization • Structured programming • Software patterns • Object-oriented design • Functional decomposition Client Hardware Web Browser Database Server Hardware

4. Databases • Database • Collection of data, organized to support access • Models some aspects of reality • DataBase Management System (DBMS) • Software to create and access databases • Relational Algebra • Mathematical theory that supports optimization

5. Database “Programming” • Structured Query Language (SQL) • Consistent, unambiguous interface to any DBMS • Simple command structure: • e.g., SELECT last-name FROM students WHERE dept=“CLIS” • Useful standard for inter-process communications • Visual programming (e.g., Microsoft Access) • Unambiguous, and easier to learn than SQL • Natural language (e.g., interactive voice response system) • Improves ease of use, but with potential for ambiguity and error • e.g., Show me the last names of students in CLIS

6. Getting Started • What questions must you answer? • What data is needed to generate the answers? • Entities • Attributes of those entities • Relationships • Nature of those relationships • How will the user interact with the system? • Relating the question to the available data • Expressing the answer in a useful form

7. An E-R Example manage-role 1 1 M member-of student team 1 M creates human implement-role 1 1 needs M client project d php-project ajax-project

8. E-R Diagrams • Entities • Types • Subtypes (disjoint / overlapping), aggregation • Attributes • Mandatory / optional • Identifier • Relationships • Cardinality • Existence • Degree

9. Making Tables from E-R Diagrams • Pick a primary key for each entity • Build the tables • One per entity • Plus one per M:M relationship • Choose terse but memorable table and field names • Check for parsimonious representation • Relational “normalization” • Redundant storage of computable values • Implement using a DBMS

10. Table-Oriented Lingo • Field An “atomic” unit of data • number, string, true/false, … • Record A collection of related fields • Table A collection of related records • Each record is one row in the table • Each field is one column in the table • Primary Key The field that identifies a record • Values of a primary key must be unique • Database A collection of tables

11. Relational Lingo • Tables represent “relations” • Course, course description • Name, email address, department • Named fields represent “attributes” • Each row in the table is called a “tuple” • The order of the rows is not important • Queries specify desired conditions • The DBMS then finds data that satisfies them

12. Visualizing Tables primary key

13. Key Lingo • “Primary Key” uniquely identifies a record • e.g. student ID in the student table • “Compound” primary key • Synthesize a primary key with a combination of fields • e.g., Student ID + Course ID in the enrollment table • “Foreign Key” is primary key in the other table • Note: it need not be unique in this table

14. Goals of “Normalization” • Save space • Save each fact only once • More rapid updates • Every fact only needs to be updated once • More rapid search • Finding something once is good enough • Avoid inconsistency • Changing data once changes it everywhere

15. Normalization • 1NF: Single-valuedindivisible (atomic) attributes • Split “Doug Oard” to two attributes as (“Doug”, “Oard”) • Model M:M implement-role relationship with a table • 2NF: Attributes depend on complete primary key • (id, impl-role, name)->(id, name)+(id, impl-role) • 3NF: Attributes depend directly on primary key • (id, addr, city, state, zip)->(id, addr, zip)+(zip, city, state) • 4NF: Divide independent M:M tables • (id, role, courses) -> (id, role) + (id, courses) • 5NF: Don’t enumerate derivable combinations

16. Normalized Table Structure • Persons: id, fname, lname, userid, password • Contacts: id, ctype, cstring • Ctlabels: ctype, string • Students: id, team, mrole • Iroles: id, irole • Rlabels: role, string • Projects: team, client, pstring

17. Referential Integrity • “Foreign key” values must exist in another table • If not, those records cannot be joined • Checked when data added to this table • MySQL “Error 150” • Triggers when data deleted/changed in other table • Specify SET NULL, RESTRICT or CASCADE

18. Getting started with MySQL • “root” creates database, grants permissions • By you on WAMP (mysql –u root –p) • By Charles Goldman on OTAL • CREATE DATABASE team1; • GRANT SELECT, INSERT, UPDATE, DELETE, INDEX, ALTER, CREATE, DROP ON team1.* TO ‘foo’@’localhost’ IDENTIFIED BY ‘bar’; • FLUSH PRIVILEGES; • Start mysql • Start->Run->cmd for WAMP, ssh for OTAL • mysql –u foo –p bar [you can cd to your playspace first, but you don’t need to] • Connect to your database • USE team1;

19. Some Useful MySQL Commands • Looking around • SHOW DATABASES; • SHOW TABLES; • DESCRIBE tablename; • SELECT * FROM tablename; • Optimization • SHOW TABLE STATUS \G; • OPTIMIZE TABLE tablename; • EXPLAIN <SQLquery>; • ALTER TABLE tablename ADD INDEX fieldname;

20. Creating Tables CREATE TABLE contacts ( ckey MEDIUMINT UNSIGNED NOT NULL AUTO_INCREMENT, id MEDIUMINT UNSIGNED NOT NULL, ctype SMALLINT UNSIGNED NOT NULL, cstring VARCHAR(40) NOT NULL, FOREIGN KEY (id) REFERENCES persons(id) ON DELETE CASCADE, FOREIGN KEY (ctype) REFERENCES ctlabels(ctype) ON DELETE RESTRICT, PRIMARY KEY (ckey) ) ENGINE=INNODB; • To delete: DROP TABLE contacts;

21. Populating Tables INSERT INTO ctlabels (string) VALUES ('primary email'), ('alternate email'), ('home phone'), ('cell phone'), ('work phone'), ('AOL IM'), ('Yahoo Chat'), ('MSN Messenger'), (‘other’); • To empty a table: DELETE FROM ctlabels;

22. The SQL SELECT Command • SELECT (“projection”) chooses columns • Based on their label • WHERE (“restriction”) chooses rows • Based on their contents • e.g. department ID = “HIST” • These can be specified together • SELECT Student ID, Dept WHERE Dept = “History”

23. WHERE Clause • Each SELECT contains a single WHERE • Numeric comparison <, >, =, <>, … • e.g., grade<80 • Boolean operations • e.g., Name = “John” AND Dept <> “HIST”

24. A Denormalized “Flat File”

25. A Normalized Relational Database Student Table Department Table Course Table Enrollment Table

26. “Joined” Table Example of Join Student Table Department Table

27. Project New Table SELECT Student ID, Department

28. Restrict New Table WHEREDepartment ID = “HIST”

29. What are Requirements? • Attributes • Appearance • Concepts (represented by data) • Behavior • What it does • How you control it • How you observe the results

30. Who Sets the Requirements? • People who need the task done (customers) • People that will operate the system (users) • People who use the system’s outputs • People who provide the system’s inputs • Whoever pays for it (requirements commissioner)

31. The Requirements Interview • Focus the discussion on the task • Look for entities that are mentioned • Discuss the system’s most important effects • Displays, reports, data storage • Learn where the system’s inputs come from • People, stored data, devices, … • Note any data that is mentioned • Try to understand the structure of the data • Shoot for the big picture, not every detail

32. First Things First • Functionality • Content • Usability • Security/Stability

33. Language Learning • Learn some words • Put those words together in simple ways • Examine to broaden your understanding • Create to deepen your mastery • Repeat until fluent

34. Thinking About PHP • Local vs. Web-server-based display • HTML as an indirect display mechanism • “View Source” for debugging • Procedural perspective (vs. object-oriented)

35. Arrays in PHP • A set of key-element pairs $days = array(“Jan”->31, “Feb”=>28, …); $months = explode(“/”, “Jan/Feb/Mar/…/Dec”); $_POST • Each element is accessed by the key • {$days[“Jan”]} • $months[0]; • Arrays and loops work naturally together

36. Thinking about Arrays • Naturally encodes an order among elements • $days = rksort($days); • Natural data structure to use with a loop • Do the same thing to different data • PHP unifies arrays and hashtables • Elements may be different types

37. Functions in PHP • Declaration function multiply($a, $b=3){return $a*$b;} • Invoking a method $b = multiply($b, 7); • All variables in a function have only local scope • Unless declared as global in the function

38. Why Modularity? • Limit complexity • Extent • Interaction • Abstraction • Minimize duplication

39. Using PHP with (X)HTML Forms <form action=“formResponseDemo.php”, method=“post”> email: <input type=“text”, name=“email”, value=“<?php echo $email ?>”, size=30 /> <input type=“radio”, name=“sure”, value=“yes” /> Yes <input type=“radio”, name=“sure”, value=“no” /> No <input type=“submit”, name=“submit”, value=“Submit” /> <input type=“hidden”, name=“submitted”, value=“TRUE” /> </form> if (isset($_POST[“submitted”])) { echo “Your email address is $email.”; } else { echo “Error: page reached without proper form submission!”; }

40. Sources of Complexity • Syntax • Learn to read past the syntax to see the ideas • Copy working examples to get the same effect • Interaction of data and control structures • Structured programming • Modularity

41. Syntax How layout helps reading How variables are named How strings are used How input is obtained How output is created Structured Programming How things are nested How arrays are used Modular Programming Functional decomposition How functions are invoked How arguments work How scope is managed How errors are handled How results are passed Some Things to Pay Attention To

42. Programming Skills Hierarchy • Reusing code [run the book’s programs] • Understanding patterns [read the book] • Applying patterns [modify programs] • Coding without patterns [programming] • Recognizing new patterns

43. Best Practices • Design before you build • Focus your learning • Program defensively • Limit complexity • Debug syntax from the top down

44. Rapid Prototyping + Waterfall Update Requirements Write Specification Initial Requirements Choose Functionality Create Software Build Prototype Write Test Plan

45. Focus Your Learning • Find examples that work • Tutorials, articles, examples • Cut them down to focus on what you need • Easiest to learn with throwaway programs • Once it works, include it in your program • If it fails, you have a working example to look at

46. Defensive Programming • Goal of software is to create desired output • Programs transform input into output • Some inputs may yield undesired output • Methods should enforce input assumptions • Guards against the user and the programmer! • Everything should be done inside methods

47. Limiting Complexity • Single errors are usually easy to fix • So avoid introducing multiple errors • Start with something that works • Start with an existing program if possible • If starting from scratch, start small • Add one new feature • Preferably isolated in its own method

48. Types of Errors • Syntax errors • Detected at compile time • Run time exceptions • Cause system-detected failures at run time • Logic errors • Cause unanticipated behavior (detected by you!) • Design errors • Fail to meet the need (detected by stakeholders)

49. Debugging Syntax Errors • Focus on the first error message • Fix one thing at a time • The line number is where it was detected • It may have been caused much earlier • Understand the cause of “warnings” • They may give a clue about later errors • If all else fails, comment out large code regions • If it compiles, the error is in the commented part

50. Run Time Exceptions • Occur when you try to do the impossible • Use a null variable, divide by zero, … • The cause is almost never where the error is • Why is the variable null? • Exceptions often indicate a logic error • Find why it happened, not just a quick fix!