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

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

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

Databases Database DataBase Management System (DBMS) 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

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

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

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

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

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

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

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

Visualizing Tables primary key

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

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

Normalization 1NF: Single-valued indivisible (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

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

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

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;

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;

Creating Tables To delete: DROP TABLE contacts; 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;

Populating Tables To empty a table: DELETE FROM ctlabels; 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;

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”

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

A Denormalized “Flat File”

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

Example of Join Student Table Department Table “Joined” Table

Project New Table SELECT Student ID, Department

Restrict New Table WHERE Department ID = “HIST”

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

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)

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

First Things First Functionality Content Usability Security/Stability

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

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

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

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

Functions in PHP Declaration Invoking a method 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

Why Modularity? Limit complexity Minimize duplication Extent Interaction Abstraction Minimize duplication

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!”; }

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

Some Things to Pay Attention To 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

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

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

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

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

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

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

Types of Errors Syntax errors Run time exceptions Logic 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)

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

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!

Debugging Run-Time Exceptions Run the program to get a stack trace Where was this function called from? Print variable values before the failure Reason backwards to find the cause Why do they have these values? If necessary, print some values further back

Logic Errors Evidenced by inappropriate behavior Can’t be automatically detected “Inappropriate” is subjective Sometimes very hard to detect Sometimes dependent on user behavior Sometimes (apparently) random Cause can be hard to pin down

Debugging Logic Errors First, look where the bad data was created If that fails, print variables at key locations if (DEBUG) echo “\$foobar = $foobar”; Examine output for unexpected patterns Once found, proceed as for run time errors define (“DEBUG”, FALSE); to clean the output

Three Big Ideas Functional decomposition High-level languages Patterns Outside-in design High-level languages Structured programming, object-oriented design Patterns Design patterns, standard algorithms, code reuse

One-Minute Paper What was the muddiest point in today’s class? Be brief! No names!