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Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Lecture 12 of 42
Wednesday, 20 September 2006
William H. Hsu
Department of Computing and Information Sciences, KSU
KSOL course page: http://snipurl.com/va Course web site: http://www.kddresearch.org/Courses/Fall-2006/CIS Instructor home page: http://www.cis.ksu.edu/~bhsu
Reading for Next Class: Section 6.1 – 6.2, Silberschatz et al. , 5th^ edition
Database Design Overview
Notes: Relational Calculi, PS
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Domain Relational CalculusDomain Relational Calculus
z A nonprocedural query language equivalent in power to the tuple
relational calculus
z Each query is an expression of the form:
{ < x 1 , x 2 , …, x n > | P ( x 1 , x 2 , …, x n )}
x 1 , x 2 , …, xn represent domain variables P represents a formula similar to that of the predicate calculus
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Example Queries Example Queries
z Find the loan_number, branch_name, and amount for loans of
over $
Find the names of all customers who have a loan from the Perryridge branch and the loan amount: f {< c, a > | ∃ l (< c, l > ∈ borrower ∧ ∃ b (< l, b, a > ∈ loan ∧ b = “Perryridge”))} f {< c, a > | ∃ l (< c, l > ∈ borrower ∧ < l, “ Perryridge ”, a > ∈ loan )}
{< c > | ∃ l, b, a (< c, l > ∈ borrower ∧ < l, b, a > ∈ loan ∧ a > 1200)}
Find the names of all customers who have a loan of over $
{< l , b, a > | < l , b, a > ∈ loan ∧ a > 1200}
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Example Queries Example Queries
z Find the names of all customers having a loan, an account, or
both at the Perryridge branch:
{< c > | ∃ s, n (< c, s, n > ∈ customer) ∧ ∀ x,y,z (< x, y, z > ∈ branch ∧ y = “Brooklyn”) ⇒ ∃ a,b (< x, y, z > ∈ account ∧ < c,a > ∈ depositor )}
Find the names of all customers who have an account at all branches located in Brooklyn:
{< c > | ∃ l ( < c, l > ∈ borrower ∧ ∃ b,a (< l, b, a > ∈ loan ∧ b = “Perryridge”)) ∨ ∃ a (< c, a > ∈ depositor ∧ ∃ b,n (< a, b, n > ∈ account ∧ b = “Perryridge”))}
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Query-by-Example (QBE) Query-by-Example (QBE)
z Basic Structure
z Queries on One Relation
z Queries on Several Relations
z The Condition Box
z The Result Relation
z Ordering the Display of Tuples
z Aggregate Operations
z Modification of the Database
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
QBE — Basic Structure QBE — Basic Structure
z A graphical query language which is based (roughly) on the
domain relational calculus
z Two dimensional syntax – system creates templates of
relations that are requested by users
z Queries are expressed “by example”
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
QBE Skeleton Tables for the Bank ExampleQBE Skeleton Tables for the Bank Example
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Query Example Query Example
z Find all customers who have an account at all branches located
in Brooklyn.
Approach: for each customer, find the number of branches in Brooklyn at which they have accounts, and compare with total number of branches in Brooklyn QBE does not provide subquery functionality, so both above tasks have to be combined in a single query. Ö Can be done for this query, but there are queries that require subqueries and cannot always be expressed in QBE.
In the query on the next page f CNT.UNQ.ALL._ w specifies the number of distinct branches in Brooklyn. Note: The variable _ w is not connected to other variables in the query f CNT.UNQ.ALL._ z specifies the number of distinct branches in Brooklyn at which customer x has an account.
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Deletion Query ExamplesDeletion Query Examples
z Delete all loans with a loan amount greater than $1300 and less
than $1500.
For consistency, we have to delete information from loan and borrower tables
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Deletion Query Examples (Cont.) Deletion Query Examples (Cont.)
z Delete all accounts at branches located in Brooklyn.
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Modification of the Database – InsertionModification of the Database – Insertion
z Insertion is done by placing the I. operator in the query
expression.
z Insert the fact that account A-9732 at the Perryridge branch
has a balance of $700.
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Modification of the Database – Insertion (Cont.) Modification of the Database – Insertion (Cont.)
Provide as a gift for all loan customers of the Perryridge branch, a new $200 savings account for every loan account they have, with the loan number serving as the account number for the new savings account.
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
An Example Query in Microsoft Access QBE An Example Query in Microsoft Access QBE
Example query: Find the customer_name , account_number and balance for all accounts at the Perryridge branch
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
An Aggregation Query in Access QBE An Aggregation Query in Access QBE
Find the name, street and city of all customers who have more than one account at the bank
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Aggregation in Access QBE Aggregation in Access QBE
z The row labeled Total specifies
which attributes are group by attributes which attributes are to be aggregated upon (and the aggregate function). For attributes that are neither group by nor aggregated, we can still specify conditions by selecting where in the Total row and listing the conditions below
z As in SQL, if group by is used, only group by attributes and
aggregate results can be output
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Banking ExampleBanking Example
z branch ( branch_name, branch_city, assets )
z customer ( customer_name, customer_street, customer_city )
z account ( account_number, branch_name, balance )
z loan ( loan_number, branch_name, amount )
z depositor ( customer_name, account_number )
z borrower ( customer_name, loan_number )
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Entity SetsEntity Sets^ customercustomer^ andand loanloan customer_id customer_ customer_ customer_ loan_ amount name street city number
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Relationship Sets Relationship Sets
z A relationship is an association among several entities
Example:
Hayes depositor A-
customer entity relationship set account entity
z A relationship set is a mathematical relation among n ≥ 2
entities, each taken from entity sets
{( e 1 , e 2 , … e n ) | e 1 ∈ E 1 , e 2 ∈ E 2 , …, e n ∈ En }
where ( e 1 , e 2 , …, e n ) is a relationship
Example: (Hayes, A-102) ∈ depositor
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Relationship SetRelationship Set borrowerborrower
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
Relational Database DesignRelational Database Design
z Features of Good Relational Design
z Atomic Domains and First Normal Form
z Decomposition Using Functional Dependencies
z Functional Dependency Theory
z Algorithms for Functional Dependencies
z Decomposition Using Multivalued Dependencies
z More Normal Form
z Database-Design Process
z Modeling Temporal Data
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
A Combined Schema Without RepetitionA Combined Schema Without Repetition
z Consider combining loan_branch and loan
loan_amt_br = ( loan_number , amount , branch_name )
z No repetition (as suggested by example below)
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
What About Smaller Schemas?What About Smaller Schemas?
z Suppose we had started with bor_loan. How would we know to split up ( decompose ) it into borrower and loan? z Write a rule “if there were a schema ( loan_number, amount ), then loan_number would be a candidate key” z Denote as a functional dependency : loan_number → amount z In bor_loan , because loan_number is not a candidate key, the amount of a loan may have to be repeated. This indicates the need to decompose bor_loan. z Not all decompositions are good. Suppose we decompose employee into employee1 = ( employee_id , employee_name ) employee2 = ( employee_name , telephone_number , start_date ) z The next slide shows how we lose information -- we cannot reconstruct the original employee relation -- and so, this is a lossy decomposition.
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
A Lossy Decomposition A Lossy Decomposition
Computing & Information Sciences CIS 560: Database System Concepts Wednesday, 20 Sep 2006 Kansas State University
First Normal Form First Normal Form
z Domain is atomic if its elements are considered to be indivisible
units
Examples of non-atomic domains: Ö Set of names, composite attributes Ö Identification numbers like CS101 that can be broken up into parts
z A relational schema R is in first normal form if the domains of all
attributes of R are atomic
z Non-atomic values complicate storage and encourage redundant
(repeated) storage of data
Example: Set of accounts stored with each customer, and set of owners stored with each account We assume all relations are in first normal form (and revisit this in Chapter 9)
