IT 3203 Introduction to Web Development

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1 IT 3203 Introduction to Web Development Databases and SQL April 7 Notice: This session is being recorded. Copyright 2007 by Bob Brown Disadvantages of File Processing Program-Data Dependence All programs maintain metadata for each file they use Duplication of Data Different systems/programs have separate copies of the same data Limited Data Sharing No centralized control of data Lengthy Development Times Programmers must design their own file formats Excessive Program Maintenance 80% of information systems budget Problems with Data Dependence Each application programmer must maintain their own data Each application program needs to include code for the metadata of each file Each application program must have its own processing routines for reading, inserting, updating and deleting data Lack of coordination and central control Non-standard file formats Problems with Data Redundancy Waste of space to have duplicate data Causes more maintenance headaches The biggest problem: When data changes in one file, could cause inconsistencies with others Compromises data integrity Solution: The Database Approach Central repository of shared data Data is managed by a controlling agent Stored in a standardized, convenient form 1

2 What is a Database? Database: An organized, self-defining collection of logically-related data Data: stored representations of meaningful objects and events Structured: numbers, text, dates Unstructured: images, video, documents Information: data processed to increase knowledge in the person using the data Metadata: The descriptive data that makes the database self-defining. The metadata is stored in the database. Relational Databases Database models: Hierarchical Network model (Object-oriented) Relational Relational model: A database modeled as tables with rows and columns. Solid theoretical basis, developed by: E.F. Codd ( ) IBM 1960s/1970s About the Relational Model A collection of tables, called relations With columns defined by the database designer called attributes or sometimes fields An arbitrary number of rows sometimes called entity instances Each row has a unique primary key SQL (sometimes pronounced sequel ) a powerful data manipulation language. Relations Definition: A relation is a named, two-dimensional table of data Table consists of rows (records), and columns (attribute or field) Requirements for a table to qualify as a relation: It must have a unique name. Every attribute value must be atomic (not multivalued, not composite) Every row must be unique (can t have two rows with exactly the same values for all their fields) Attributes (columns) in tables must have unique names The order of the columns must be irrelevant The order of the rows must be irrelevant NOTE: all relations are in First Normal form 10 Key Fields Keys are special fields that serve two main purposes: Primary keys are unique identifiers of the relation in question. Examples include employee numbers, social security numbers, etc. This is how we can guarantee that all rows are unique Foreign keys are identifiers that enable a dependent relation (on the many side of a relationship) to refer to its parent relation (on the one side of the relationship) Keys can be simple (a single field) or composite (more than one field) Keys usually are used as indexes to speed up the response to user queries Integrity Constraints Domain Constraints Allowable values for an attribute. Entity Integrity No primary key attribute t may be null. All primary key fields MUST have data Action Assertions Business rules. 12 2

3 Integrity Constraints Referential Integrity rule that states that any foreign key value (on the relation of the many side) must match a primary key value in the relation of the one side. (Or the foreign key can be null) For example: Delete Rules Restrict don t allow delete of parent side if related rows exist in dependent side Cascade automatically delete dependent side rows that correspond with the parent side row to be deleted Set-to-Null set the foreign key in the dependent side to null if deleting from the parent side not allowed for weak entities Data Normalization Primarily a tool to validate and improve a logical design so that it satisfies certain constraints that avoid unnecessary duplication of fd data The process of decomposing relations with anomalies to produce smaller, well- structured relations Well-Structured Relations A relation that contains minimal data redundancy and allows users to insert, delete, and update rows without causing data inconsistencies Goal is to avoid anomalies Insertion Anomaly adding new rows forces user to create duplicate data Deletion Anomaly deleting rows may cause a loss of data that would be needed for other future rows Modification Anomaly changing data in a row forces changes to other rows because of duplication General rule of thumb: a table should not pertain to more than one entity type Functional Dependencies and Keys Functional Dependency: The value of one attribute (the determinant) ) determines the value of another attribute Candidate Key: A unique identifier. One of the candidate keys will become the primary key E.g. perhaps there is both credit card number and SS# in a table in this case both are candidate keys Each non-key field is functionally dependent on every candidate key Data Modeling Information systems model the real world; Can t build an effective information system without a well-defined model. The example problem: Store information about for sale Cars State where located What equipment The Table State_ID Abbrev Name 1 AL Alabama 2 AK Alaska 3 AZ Arizona 4 AR Arkansas 5 CA California 6 CO Colorado 7 CT Connecticut 3

4 The Table ID Body Miles Year State 1 coupe hatchback convertible hatchback Foreign key Entity-Relationship Diagrams A graphical way of showing relationships among database entities. A given Corvette is in one and only one state. There may be many in one state. The Table Problem: Specifying equipment uniformly ID Equip 1 Automatic 2 4-speed 3 5-speed 4 6-speed 5 CD 6 Leather Many-to-Many Relationships Problem: How to relate the equipment to the Connecting to Cars A helper table, or associative entity Connecting to Cars A helper table, or associative entity 4

5 The _ Table ID Equip 1 Vette 1 1 Automatic 1 5 CD Player 1 6 Leather Another Look at the E-R Diagram _ Composite primary key Working with Databases SQL SQL: Structured Query Language IBM: 1970s ISO: 1986, 1992, 1999 Data Definition Language Data Manipulation Language Data Control llanguage Vendor-specific implementations are converging to the standard Data Definition Creating a table: CREATE TABLE states ( id INTEGER PRIMARY KEY NOT NULL, abbrev char(2), name char(20)); And a word about capitalization. Data Manipulation Populating a table with insert INSERT INTO states (id, abbrev, name) VALUES (1, 'AL', 'Alabama'); Most DBMSs provide a mass copy function for initial database loading. Data Manipulation select An extremely powerful SQL statement SELECT * FROM states; id abbrev name AL Alabama 2 AK Alaska 3 AZ Arizona 4 AR Arkansas 5 CA California 5

6 More About Select You can specify which columns You can provide selection criteria SELECT id, miles, year FROM corvettes WHERE miles < 15.0; id miles year Sorting with Select The order by clause sorts output SELECT id, miles, year FROM corvettes WHERE miles < 25.0 ORDER BY year; id miles year (6 rows) General Form of select SELECT column list FROM table list WHERE selection and join criteria ORDER BY column list ; Updating Tables Change values with update UPDATE corvettes SET miles=59.0 WHERE id=2; There are no training wheels! UPDATE corvettes SET miles=59.0; Deleting Data Use the delete statement DELETE FROM states WHERE name='texas'; There are no training wheels! DELETE FROM states; Data From More Than One Table select can join tables SELECT corvettes.id, states.name FROM corvettes, states WHERE corvettes.state=states.id; We name the tables as well as the columns. The where clause describes the join criteria. i (It can also select data.) 6

7 Result of the Join id name Alabama 6 Alaska 4 Alaska 1 Arkansas 9 California 8 California 5 California 2 Connecticut 10 Connecticut (9 rows) A More Complex Join Find all with CD players and show mileage: SELECT corvettes.id, corvettes.miles, corvettes_equipment.equip FROM corvettes, corvettes_equipment WHERE corvettes.id = corvettes_equipment.idequipment.id AND corvettes_equipment.equip=5; Result of the Join id miles equip (5 rows) Using Three Tables... and put CD on the listing... SELECT corvettes.id, corvettes.miles, equipment.equip FROM corvettes, corvettes_equipment, equipment WHERE corvettes.id = corvettes_equipment.id AND corvettes_equipment.equip= equipment.id AND corvettes_equipment.equip=5; Result of the Join id miles equip CD CD 9 17 CD 8 17 CD 1 18 CD (5 rows) A Really Complex Join SELECT corvettes.id, corvettes.body_style, corvettes.miles, corvettes.year, states.name as state FROM corvettes, corvettes_equipment, equipment, states WHERE corvettes.id = corvettes_equipment.id AND corvettes_ equipment.equip=equipment.id q p q p AND equipment.equip='cd' AND corvettes.state=states.id ORDER BY body_style; 7

8 Results of the Join id body_style miles year state convertible California 1 coupe Arkansas 10 hardtop Connecticut 9 hatchback California 2 hatchback Connecticut (5 rows) Architecture for Database-Backed Web Sites CGI or other middleware serves as the glue to connect a Web server and a database. The Internet Web Middleware Server Database General Approach 1. Build SQL statements (e.g. in a string variable) 2. Pass SQL to the DBMS 3. Retrieve the results via an API 4. Do something with the results Database Access with PHP: DB-specific functions and procedural programming PEAR DB object-oriented with Java: JDBC (note: server-side!) with ASP.NET database connection and data reader Questions 8