Introduction to Databases CS420 Software Engineering in Practice

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Introduction to DatabasesCS420 Software
Engineering in Practice
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Basic Structure

• Formally, given sets D1, D2, . Dn a relation r
  is a subset of D1 x D2 x x DnThus,
  a relation is a set of n-tuples (a1, a2, , an)
  where each ai ? Di
• Example If customer_name Jones, Smith,
  Curry, Lindsay customer_street Main, North,
  Park customer_city Harrison, Rye,
  PittsfieldThen r (Jones, Main, Harrison),
  (Smith, North, Rye),
  (Curry, North, Rye),
  (Lindsay, Park, Pittsfield) is a relation over
  
• customer_name x customer_street x
  customer_city

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Example of a Relation
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Attribute Types

• Each attribute of a relation has a name
• The set of allowed values for each attribute is
  called the domain of the attribute
• Attribute values are (normally) required to be
  atomic that is, indivisible
• Note composite attribute values are not atomic
• The special value null is a member of every
  domain
• The null value causes complications in the
  definition of many operations

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Relation Schema

• A1, A2, , An are attributes
• R (A1, A2, , An ) is a relation schema
• Example
• Customer_schema (customer_name,
  customer_street, customer_city)

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Relation Instance

• The current values (relation instance) of a
  relation are specified by a table
• An element t of r is a tuple, represented by a
  row in a table

attributes (or columns)
customer_name
customer_street
customer_city
Jones Smith Curry Lindsay
Main North North Park
Harrison Rye Rye Pittsfield
tuples (or rows)
customer
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Relations are Unordered

• Order of tuples is irrelevant (tuples may be
  stored in an arbitrary order)
• Example account relation with unordered tuples

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Database

• A database consists of multiple relations
• Information about an enterprise is broken up into
  parts, with each relation storing one part of
  the information
• account stores information about accounts
  depositor stores information about which
  customer owns which
  account customer stores information
  about customers
• Storing all information as a single relation such
  as bank(account_number, balance,
  customer_name, ..)results in
• repetition of information (e.g., two customers
  own an account)
• the need for null values (e.g., represent a
  customer without an account)
• Normalization theory deals with how to design
  relational schemas

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The depositor Relation
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Keys

• Let K ? R
• K is a superkey of R if values for K are
  sufficient to identify a unique tuple of each
  possible relation r(R)
• by possible r we mean a relation r that could
  exist in the enterprise we are modeling.
• Example customer_name, customer_street and
  customer_name are both superkeys
  of Customer, if no two customers can possibly
  have the same name.
• K is a candidate key if K is minimalExample
  customer_name is a candidate key for Customer,
  since it is a superkey (assuming no two customers
  can possibly have the same name), and no subset
  of it is a superkey.

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Query Languages

• Language in which user requests information from
  the database.
• Categories of languages
• Procedural
• Non-procedural, or declarative
• Pure languages
• Relational algebra
• Tuple relational calculus
• Domain relational calculus
• Pure languages form underlying basis of query
  languages that people use.

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SQL

• Most popular computer language used to create,
  modify and retrieve data from relational database
  management systems.
• SQL is not a procedural language but a
  declarative language. You write a single SQL
  declaration and hand it to the DBMS. The DBMS
  then executes internal code, which is hidden from
  us.
• In a declarative language, we carefully phrase
  what we want and then let the DBMS get it for us.
  
• Procedural languages result in many lines of
  code. Declarative languages result in one
  statement of the desired result.

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SQL - Select

• SELECT is used to retrieve zero or more rows from
  one or more tables in a database. In specifying a
  SELECT query, the user specifies a description of
  the desired result set, but they do not specify
  what physical operations must be executed to
  produce that result set. Translating the query
  into an efficient query plan is left to the
  database system, more specifically to the query
  optimizer.
• Commonly available keywords related to SELECT
  include
• FROM is used to indicate from which tables the
  data is to be taken, as well as how the tables
  join to each other.
• WHERE is used to identify which rows to be
  retrieved, or applied to GROUP BY.
• GROUP BY is used to combine rows with related
  values into elements of a smaller set of rows.
• HAVING is used to identify which of the "combined
  rows" (combined rows are produced when the query
  has a GROUP BY keyword or when the SELECT part
  contains aggregates), are to be retrieved.
• ORDER BY is used to identify which columns are
  used to sort the resulting data

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SQL Example

• Example SELECT FROM my_table WHERE id gt 10

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Data manipulation

• First there are the standard Data Manipulation
  Language (DML) elements. DML is the subset of the
  language used to add, update and delete data.
• INSERT is used to add zero or more rows (formally
  tuples) to an existing table.
• UPDATE is used to modify the values of a set of
  existing table rows.
• MERGE is used to combine the data of multiple
  tables. It is something of a combination of the
  INSERT and UPDATE elements. It is defined in the
  SQL2003 standard prior to that, some databases
  provided similar functionality via different
  syntax, sometimes called an "upsert".
• DELETE deletes all data from a table
  (non-standard, but common SQL command).
• TRUNCATE removes zero or more existing rows from
  a table.

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Entity-Relationship Model

• Design Process
• Modeling
• Constraints
• E-R Diagram
• Design Issues
• Weak Entity Sets
• Extended E-R Features
• Design of the Bank Database
• Reduction to Relation Schemas
• Database Design
• UML

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Modeling

• A database can be modeled as
• a collection of entities,
• relationship among entities.
• An entity is an object that exists and is
  distinguishable from other objects.
• Example specific person, company, event, plant
• Entities have attributes
• Example people have names and addresses
• An entity set is a set of entities of the same
  type that share the same properties.
• Example set of all persons, companies, trees,
  holidays

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Entity Sets customer and loan
customer_id customer_ customer_ customer_
loan_ amount
name street city
number
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Relationship Sets

• A relationship is an association among several
  entities
• Example Hayes depositor A-102 customer
  entity relationship set account entity
• A relationship set is a mathematical relation
  among n ? 2 entities, each taken from entity sets
• (e1, e2, en) e1 ? E1, e2 ? E2, , en ?
  Enwhere (e1, e2, , en) is a relationship
• Example
• (Hayes, A-102) ? depositor

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Relationship Set borrower
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Relationship Sets (Cont.)

• An attribute can also be property of a
  relationship set.
• For instance, the depositor relationship set
  between entity sets customer and account may have
  the attribute access-date

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Degree of a Relationship Set

• Refers to number of entity sets that participate
  in a relationship set.
• Relationship sets that involve two entity sets
  are binary (or degree two). Generally, most
  relationship sets in a database system are
  binary.
• Relationship sets may involve more than two
  entity sets.
• Relationships between more than two entity sets
  are rare. Most relationships are binary. (More
  on this later.)

• Example Suppose employees of a bank may have
  jobs (responsibilities) at multiple branches,
  with different jobs at different branches. Then
  there is a ternary relationship set between
  entity sets employee, job, and branch

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Attributes

• An entity is represented by a set of attributes,
  that is descriptive properties possessed by all
  members of an entity set.
• Domain the set of permitted values for each
  attribute
• Attribute types
• Simple and composite attributes.
• Single-valued and multi-valued attributes
• Example multivalued attribute phone_numbers
• Derived attributes
• Can be computed from other attributes
• Example age, given date_of_birth

Example customer (customer_id,
customer_name, customer_street,
customer_city ) loan (loan_number, amount )
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Composite Attributes
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Mapping Cardinality Constraints

• Express the number of entities to which another
  entity can be associated via a relationship set.
• Most useful in describing binary relationship
  sets.
• For a binary relationship set the mapping
  cardinality must be one of the following types
• One to one
• One to many
• Many to one
• Many to many

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Mapping Cardinalities
One to one
One to many
Note Some elements in A and B may not be mapped
to any elements in the other set
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Mapping Cardinalities
Many to one
Many to many
Note Some elements in A and B may not be mapped
to any elements in the other set
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Keys

• A super key of an entity set is a set of one or
  more attributes whose values uniquely determine
  each entity.
• A candidate key of an entity set is a minimal
  super key
• Customer_id is candidate key of customer
• account_number is candidate key of account
• Although several candidate keys may exist, one of
  the candidate keys is selected to be the primary
  key.

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Keys for Relationship Sets

• The combination of primary keys of the
  participating entity sets forms a super key of a
  relationship set.
• (customer_id, account_number) is the super key of
  depositor
• NOTE this means a pair of entity sets can have
  at most one relationship in a particular
  relationship set.
• Example if we wish to track all access_dates to
  each account by each customer, we cannot assume a
  relationship for each access. We can use a
  multivalued attribute though
• Must consider the mapping cardinality of the
  relationship set when deciding the what are the
  candidate keys
• Need to consider semantics of relationship set in
  selecting the primary key in case of more than
  one candidate key

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E-R Diagrams

• Rectangles represent entity sets.
• Diamonds represent relationship sets.
• Lines link attributes to entity sets and entity
  sets to relationship sets.
• Ellipses represent attributes
• Double ellipses represent multivalued attributes.
• Dashed ellipses denote derived attributes.
• Underline indicates primary key attributes (will
  study later)

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E-R Diagram With Composite, Multivalued, and
Derived Attributes
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Relationship Sets with Attributes
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Roles

• Entity sets of a relationship need not be
  distinct
• The labels manager and worker are called
  roles they specify how employee entities
  interact via the works_for relationship set.
• Roles are indicated in E-R diagrams by labeling
  the lines that connect diamonds to rectangles.
• Role labels are optional, and are used to clarify
  semantics of the relationship

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Cardinality Constraints

• We express cardinality constraints by drawing
  either a directed line (?), signifying one, or
  an undirected line (), signifying many,
  between the relationship set and the entity set.
• One-to-one relationship
• A customer is associated with at most one loan
  via the relationship borrower
• A loan is associated with at most one customer
  via borrower

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One-To-Many Relationship

• In the one-to-many relationship a loan is
  associated with at most one customer via
  borrower, a customer is associated with several
  (including 0) loans via borrower