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Relational Databases. COMP 416 Fall 2010 Lecture 21. What’s a database?. A collection of data Examples of collections of data? Library Web Stacks of papers on your desk Set of baseball cards. Are all of these things databases?. Web vs. Library. What’s the big difference? Organization - PowerPoint PPT Presentation
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Relational Databases
COMP 416
Fall 2010
Lecture 21
What’s a database?
• A collection of data
• Examples of collections of data?– Library– Web– Stacks of papers on your desk– Set of baseball cards.
• Are all of these things databases?
Web vs. Library
• What’s the big difference?– Organization– In what ways is the library organized?
• Databases have organization.
Library vs Baseball Cards• What’s the primary object in these two
collections?– Libraries: books– Baseball card collections: baseball cards
• How alike are books?– Somewhat, but large variatations
• How alike are baseball cards?– Very alike.
• Things in databases are highly structured.
One library vs another
• What’s the difference between the Brauer Library and the House Library?
• Different purposes leads to different priorities (in organization and content).
• Databases are built for a purpose.– The more specific the purpose, the more
specific its structure and organization.
So, what’s a database
• A database is an collection of structured information organized for a specific purpose.
Relational Databases
• Relational databases are the most prevalent type of database used.
• Information is organized into related tables.
• Each table captures information about a different entity.– Columns are different fields of information
(attributes of the entity).– Each row represents one instance (a specific
example of the entity).
Design Goals• What kinds of information do we want to
keep track of?
• What do we want to do with that information?
Entities
• First step in database design is to identify entities.– Think of entities as “things” that you want to
know information about.– What do we care about for our bookstore?
• Books (duh?)
Attributes
• Next step is to identify attributes of those entities.
• An attribute is labeled piece of information (i.e., a name/value pair)
• In general, we expect every instance of a particular entity to have specific values for a set of common attributes.
Book Entity
BookAuthor(s)
Title
Publisher
Genre
Price
Normalization
• Not all database designs are equal.
• Experience and research has shown that certain structures and relationships are easier to maintain and process than others.
• Normalization: a process through which a database design is “cleaned up”
• Well-defined set of “normal forms” which are the incremental result of this process.
1NF
• First Normal Form– All attributes are single-valued.– All instances have a unique identifier.
Book Entity Revisited
• Is our book entity in 1NF?
BookAuthor(s)
Title
Publisher
Genre
Price
Bookstore Entities (1NF)
• Multi-valued attributes generally indicate the need for a new entity.
BookTitle
Publisher
Genre
Price
AuthorFirst
Last
Birthday
Unique Identifiers
• What in our book and author entities can act as a unique identifier?
• Often (almost always) the best way to create a unique identifier is to create an artificial one.– Book ID, Author ID.– Assigned by the database itself.– No inherent semantics.
Book Entities (1NF) v2
Book
Title
Publisher
Genre
Price
ID
Author
First
Last
Birthday
ID
Modeling Relationships
• Two relationship types.– One-to-Many– Many-to-Many
• For now, we’ll just model this pictorially like this:
Book
Title
Publisher
Genre
Price
ID
Author
First
Last
Birthday
ID
2NF
• Second Normal Form– Already in 1NF– Non-identifying attributes are dependent on the
entity’s unique identifier.• Rule of thumb: if the same value appears multiple
times for a particular attribute, think hard if what you really need is another entity.
Bookstore Entities
• What might we pull out into an entity? Book
Title
Publisher
Genre
Price
ID
Author
First
Last
Birthday
ID
Bookstore Entities (2NF)
Book
Title
Price
ID
Author
First
Last
Birthday
ID
Publisher
Name
Address
State
State Abbrev.
ID
Genre
Genre Name
ID
3NF
• Third Normal Form– In 2NF– No attributes dependent on each other.
• What part of our data model violates this?
• To fix, generally want to pull the dependent attributes out into their own entity.
Bookstore Entities (3NF)
Book
Title
Price
ID
Author
First
Last
Birthday
ID
Publisher
Name
Address
ID
Genre
Genre Name
ID
Long NameAbbrev.
StateID
Logical vs Physical Design• Result so far is “logical” database design.• Still need to implement this design as a specific
database.• Relational databases:
– Each entity associated with a table.– Attributes are columns of the table.– Each attribute is given a data type.– Unique identifiers are “primary keys”– Relationships are embodied as “foreign keys”
• An attribute whose value is the unique identifier in another table.
Implementing 1-to-many
• To implement a 1-to-many relationship, add an attribute on the “many” side which is the unique identifier of the “one” side.
Implementing 1-to-many
Author
First
Last
Birthday
ID
Genre
Genre Name
ID
Long NameAbbrev.
StateID
Publisher
NameAddress
ID
StateID
Book
TitlePrice
ID
PubIDGenreID
Resolving M-to-M
• Many-to-many relationships are hard to implement in a database.
• Why is this?– Foreign key attribute which is supposed to
implement the relationship requires multiple values.
– This breaks 1NF structure.
• How might we fix it?
Junction Entities
• A junction entity is an abstract entity provides a level of indirection for a many-to-many relationship.
Adding BookAuthor Junction
Author
First
Last
Birthday
ID
Genre
Genre Name
ID
Long NameAbbrev.
StateID
Publisher
NameAddress
ID
StateID
Book
TitlePrice
ID
PubIDGenreID
BookAuthor
BookIDID
AuthorID
SQL
• Structured Query Language (SQL)– The language in which we express actions to be
performed on a relational database.– Standardized to allow portability across
different products.• SQL92 (aka SQL2) is the latest standard.
– Product specific differences and extensions still exist, but much better than before.
MySQL• MySQL
– Open-source– Great for small to mid-sized organizations.– Fast, efficient, cheap– Doesn’t support full SQL but a good portion of it.
Web App Model
JavaScriptProgrammable,
dynamic interface to the
document
Browser Web ServerHTTP Requests
HTTP Responses
DBOn Disk
SQLPHPProgrammable,
dynamic, document
construction
DatabaseStructured, table-based, information
storage