Functional Dependency Graphs and SQL

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Functional Dependency Graphs and SQL
CS157A
Lecture 11

• Prof. Sin-Min Lee
• Department of Computer Science
• San Jose State University

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Data Normalization

• Primarily a tool to validate and improve a
  logical design so that it satisfies certain
  constraints that avoid unnecessary duplication of
  data.
• The process of decomposing relations with
  anomalies to produce smaller, well-structured
  relations.
• Primary Objective Reduce Redundancy,Reduce
  nulls,
• Improve modify activities
• insert,
• update,
• delete,
• but not read
• Price degraded query, display, reporting

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Functional Dependency and Keys

• Functional Dependency The value of one attribute
  (the determinant) determines the value of another
  attribute.
• Candidate Key Each non-key field is functionally
  dependent on every candidate key.

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Functional dependency

• a constraint between two attributes (columns) or
  two sets of columns
• A ? B if for every valid instance of A, that
  value of A uniquely determines the value of B
• or A ?B if there exists at most one value of B
  for every value of A

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Functional Dependencies
R
X Y Z

• FDs defined over two sets of attributes X, Y
  Ì R
• Notation X à Y reads as X determines Y
• If X à Y, then all tuples that agree on X must
  also agree on Y

1 2 3 2 4 5 1 2 4 1 2 7 2 4 8 3 7 9
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Functional Dependencies Graph(example)
X Y Z
X Y Z
1 2 3 2 4 5 1 2 4 1 2 7 2 4 8 3 7 9
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functional dependency

• some examples
• SSN ? Name, Address, Birthdate
• VIN ? Make, Model, Color
• note the LHS is the determinant
• so functional dependency is the technical term
  for determines

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Candidate Keys

• an attribute (or set of attributes) that uniquely
  identifies a row
• primary key is a special candidate key
• values cannot be null
• e.g.
• ENROLL (Student_ID, Name, Address, )
• PK Student_ID
• candidate key Name, Address

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candidate key

• a candidate key must satisfy
• unique identification.
• implies that each nonkey attribute is
  functionally dependent on the key (for not(A ? B)
  to be true, A must occur more than once (with a
  different B), or A must map to more than one B in
  a given row)
• nonredundancy
• no attribute in the key can be deleted and still
  be unique
• minimal set of columns (Simsion)

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keys and dependencies
EMPLOYEE1 (Emp_ID, Name, Dept_Name, Salary)
determinant
Emp_ID Name Dept_Name Salary
functional dependency
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EMPLOYEE2 (Emp_ID, Course_Title, Name,
Dept_Name, Salary, Date_Completed)
Emp_ID Course_ Title Name Dept_ Name Salary Date_Comp.
not fully functionally dependant on the primary
key
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determinants candidate keys

• candidate key is always a determinant (one way to
  find a determinant)
• determinant may or may not be a candidate key
• ? candidate key is a determinant that uniquely
  identifies the remaining (nonkey) attributes
• determinant may be
• a candidate key
• part of a composite candidate key
• nonkey attribute

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Introduction

• Data integrity maintained by various constraints
  on data
• Functional dependencies are application
  constraints that help DB model real-world entity
• Join dependencies are a further constraint that
  help resolve some FD constraint limitations

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What is SQL?

• It is a language used to communicate with a
  database.
• SQL statements are used to perform tasks such as
  update or retrieve data from a database.
• Standard SQL commands Select, Create,
  Insert, Update, Delete, and Drop can be
  used to accomplish almost everything that a
  database needs to do.

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History

• Originally developed by IBM at San Jose Research
  Laboratory (a.k.a. Almaden Research Center)
• Oracle, Sybase, Microsoft SQL server are some
  common relational database management systems
  that use SQL

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Table Basics

• Data or information for the database are stored
  in tables.
• Tables are uniquely identified by their names and
  are comprised of columns and rows.
• Rows contain data for the columns.

City State High Low
Phoenix Arizona 105 90
Tucson Arizona 101 92
Flagstaff Arizona 88 69
San Diego California 77 60
San Jose California 80 65
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Basic Structure

• The basic structure of an SQL expression consists
  of three clauses select, from, and where.
• The select clause corresponds to the projection
  operation of the relational algebra. It is used
  to list attributes desired in the result.
• The from clause corresponds to the
  Cartesian-product operation of the relational
  algebra. It lists the relations to be scanned in
  the evaluation of the expression.
• The where clause corresponds to the selection
  predicate of the relational algebra. It consists
  of a predicate involving attributes of the
  relations that appear in the from clause.

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Selecting Data

• The Select statement is used to query the
  database and retrieve selected data that match
  the criteria that you specify
• Example
• select column1
• ,column2, etc
• from tablename
• where condition
• optional continued

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Selecting Data cont

• The column names that follow the select keyword
  determine which columns will be returned in the
  results.
• The table name that follows the keyword from
  specifies the table that will be queried to
  retrieve the desired results.
• cont

• Example
• select column1
• ,column2, etc
• from tablename
• where condition
• optional

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Selecting Data cont

• The where clause is optional and specifies which
  data values or rows will be returned or
  displayed, based on the criteria described on the
  condition.
• Conditional selections used in the where clause
  , gt, lt, gt, lt, and ltgt (not equal to).

• Example
• select column1
• ,column2, etc
• from tablename
• where condition
• optional

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The where Clause

• Problem Find all loan numbers for loans made at
  the Perryridge branch with loan amounts greater
  than 1200.

• Answer
• select loan-number
• from loan
• where branch-name Perryridge and amount gt
  1200
• SQL uses the logical connectives and, or, and
  not rather than the mathematical symbols in the
  where clause.

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The from Clause

• The from clause, by itself, defines a Cartesian
  product of the relations in the clause.
• Problem For all customers who have a loan from
  the bank, find their names, loan numbers, and
  loan amount.

• Answer
• select customer-name, borrower.loan- number,
  amount
• from borrower, loan
• where borrower.loan- number loan.loan- number

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Creating Tables

• Example of simple create table statement
• create table tablename
• (column1 data type,
• column2 data type,
• column3 data type)

• The create table statement is used to create a
  new table.
• The data types specify what the type of data can
  be for that particular column.

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Most Common Data Types

• char (size) Fixed length character string. Size
  is specified in parenthesis. Max 255 bytes.
• varchar (size) Variable-length character
  string. Max size is specified in parenthesis.
• number (size) Number value with a max number of
  column digits specified in parenthesis.
• date Date value
• number (size, d) Number value with a max number
  of digits of size total, with a max number of
  d digits to the right of the decimal.

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Creating Tables cont

• Example
• Problem Create a table for a new company that
  contains the following information about your new
  employees first name, last name, title, age, and
  salary.

• Answer
• Create table myemployees
• (firstname varchar(30),
• lastname varchar(30),
• title varchar (30),
• age number(2),
• salary number(8, 2))

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Inserting into a Table

• Example 1
• Insert into tablename
• (first_column, last_column)
• values (first_value,last_value)
• Example 2
• Insert into employee
• (first, last, age, address, city, state)
• values (Luke, Duke, 45, 2130 Boars Nest,
  Hazard Co., Georgia)

• The insert statement is used to insert or add a
  row of data into the table.
• Strings should be enclosed in single quotes, and
  numbers should not.

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Updating Records

• The update statement is used to update or change
  records that match a specified criteria.
• This is accomplished by carefully constructing a
  where clause.
• Example 1
• update phone_book
• set area_code 623
• where prefix 979

• Example 2
• update tablename
• set columnname newvalue
• ,nextcolumn newvalue2
• where columnname
• OPERATOR value
• and or column
• OPERATOR value
• optional

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Deleting Records

• The delete statement is used to delete records or
  rows from the table.
• To delete an entire row/record, enter delete
  from followed by the table name, the where
  clause.
• If you leave off the where clause, it will
  delete all records.

• Example
• delete from tablename
• where columnname
• OPERATOR value
• and or column
• OPERATOR value
• optional

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Drop a Table

• The drop table command is used to delete a table
  and all rows in the table.
• drop table is different from deleting all of the
  records in the table. Dropping the table removes
  the table definition as well as all of its rows.

• Example
• Drop table tablename

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Ordering the Display of Tuples

• Example To list in alphabetic order all
  customers who have a loan at the Perryridge
  branch
• select distinct customer-name
• from borrower, loan
• where borrower.loan-number loan.loan-number
  and branch-name Perryridge
• order by customer-name

• The order by clause causes the tuples in the
  result of a query to appear in sorted order.
• By default, the order by clause lists items in
  ascending order.

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Aggregates

• Functions that operate on sets
• COUNT, SUM, AVG, MAX, MIN
• Produce numbers (not tables)
• Not part of relational algebra

SELECT COUNT() FROM Professor P
SELECT MAX (Salary) FROM Employee E
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Aggregates
Count the number of courses taught in S2000
SELECT COUNT (T.CrsCode) FROM Teaching T WHERE
T.Semester S2000
But if multiple sections of same course are
taught, use
SELECT COUNT (DISTINCT T.CrsCode) FROM Teaching
T WHERE T.Semester S2000
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Aggregates Proper and Improper Usage
SELECT COUNT (T.CrsCode), T. ProfId
makes no sense (in the absence of
GROUP BY clause)
SELECT COUNT (), AVG (T.Grade)
but this is OK
WHERE T.Grade gt COUNT (SELECT .)
aggregate cannot be applied to result
of SELECT statement
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Grouping

• But how do we compute the number of courses
  taught in S2000 per professor?
• Strategy 1 Fire off a separate query for each
  professor
• SELECT COUNT(T.CrsCode)
• FROM Teaching T
• WHERE T.Semester S2000 AND T.ProfId
  123456789
• Cumbersome
• What if the number of professors changes? Add
  another query?
• Strategy 2 define a special grouping operator
• SELECT T.ProfId, COUNT(T.CrsCode)
• FROM Teaching T
• WHERE T.Semester S2000
• GROUP BY T.ProfId

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GROUP BY
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GROUP BY - Example
Transcript
Attributes -students Id -avg grade
-number of courses
1234 1234 1234 1234
1234 3.3 4
SELECT T.StudId, AVG(T.Grade), COUNT () FROM
Transcript T GROUP BY T.StudId
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HAVING Clause

• Eliminates unwanted groups (analogous to WHERE
  clause)
• HAVING condition constructed from attributes of
  GROUP BY list and aggregates of attributes not in
  list

SELECT T.StudId, AVG(T.Grade) AS CumGpa,
COUNT () AS NumCrs FROM
Transcript T WHERE T.CrsCode LIKE CS GROUP
BY T.StudId HAVING AVG (T.Grade) gt 3.5
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Evaluation of GroupBy with Having
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Example

• Output the name and address of all seniors on the
  Deans List

SELECT S.Id, S.Name FROM Student S,
Transcript T WHERE S.Id T.StudId AND
S.Status senior GROUP BY HAVING AVG
(T.Grade) gt 3.5 AND SUM (T.Credit) gt 90
S.Id -- wrong S.Id, S.Name --
right
Every attribute that occurs in SELECT clause must
also occur in GROUP BY or it must be an
aggregate. S.Name does not.
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ORDER BY Clause

• Causes rows to be output in a specified order

SELECT T.StudId, COUNT () AS NumCrs,
AVG(T.Grade) AS CumGpa FROM Transcript
T WHERE T.CrsCode LIKE CS GROUP BY
T.StudId HAVING AVG (T.Grade) gt 3.5 ORDER BY
DESC CumGpa, ASC StudId
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Query Evaluation Strategy

• Evaluate FROM produces Cartesian product, A, of
  tables in FROM list
• Evaluate WHERE produces table, B, consisting of
  rows of A that satisfy WHERE condition
• Evaluate GROUP BY partitions B into groups that
  agree on attribute values in GROUP BY list
• Evaluate HAVING eliminates groups in B that do
  not satisfy HAVING condition
• Evaluate SELECT produces table C containing a
  row for each group. Attributes in SELECT list
  limited to those in GROUP BY list and aggregates
  over group
• Evaluate ORDER BY orders rows of C

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Nested Queries
List all courses that were not taught in S2000
SELECT C.CrsName FROM Course C WHERE C.CrsCode
NOT IN (SELECT T.CrsCode --subquery
FROM Teaching T WHERE T.Sem
S2000)
Evaluation strategy subquery evaluated once
to produces set of courses taught in S2000.
Each row (as C) tested against this set.
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Correlated Nested Queries
Output a row ltprof, deptgt if prof has taught a
course in dept.
SELECT P.Name, D.Name --outer
query FROM Professor P, Department D WHERE
P.Id IN (set of Ids of all profs who
have taught a course in
D.DeptId)
SELECT T.ProfId
--subquery FROM Teaching T, Course C WHERE
T.CrsCodeC.CrsCode AND
C.DeptIdD.DeptId --correlation
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Correlated Nested Queries (cont)

• Tuple variables T and C are local to subquery
• Tuple variables P and D are global to subquery
• Correlation subquery uses a global variable, D
• The value of D.DeptId parameterizes an
  evaluation of the subquery
• Subquery must (at least) be re-evaluated for
  each distinct value of D.DeptId
• Correlated queries can be expensive to evaluate

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Division SQL Solution
SELECT P.Id FROM Professor P WHERE NOT EXISTS
(SELECT D.DeptId -- set B of all dept
Ids FROM Department D EXCEPT
SELECT C.DeptId -- set A of dept
Ids of depts in
-- which P has taught a course
FROM Teaching T, Course C WHERE
T.ProfIdP.Id -- global variable
AND T.CrsCodeC.CrsCode)
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Division

• Query type Find the subset of items in one set
  that are related to all items in another set
• Example Find professors who have taught courses
  in all departments
• Why does this involve division?

ProfId DeptId
DeptId
Contains row ltp,dgt if professor p has taught
a course in department d
All department Ids
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Division

• Strategy for implementing division in SQL
• Find set of all departments in which a particular
  professor, p, has taught a course - A
• Find set of all departments - B
• Output p if A ? B, or equivalently if B-A is
  empty

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Division SQL Solution
SELECT P.Id FROM Professor P WHERE NOT EXISTS
(SELECT D.DeptId -- B set of all dept
Ids FROM Department D EXCEPT
SELECT C.DeptId -- A set of dept
Ids of depts in
-- which P has taught a course
FROM Teaching T, Course C WHERE
T.ProfIdP.Id --global variable
AND T.CrsCodeC.CrsCode)
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GROUP BY
Table output by WHERE clause - Divide
rows into groups based on subset of
attributes - All members of a group
agree on those attributes
a a b b c c c c c d d d
group
Each group can be described by a single row in a
table with attributes limited to -Attributes
all group members share (listed in GROUP
BY clause) -Aggregates over group
GROUP BY attributes
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GROUP BY - Example
Transcript
Attributes -students Id -avg grade
-number of courses
1234 1234 1234 1234
1234 3.3 4
SELECT T.StudId, AVG(T.Grade), COUNT () FROM
Transcript T GROUP BY T.StudId
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HAVING Clause

• Eliminates unwanted groups (analogous to WHERE
  clause)
• HAVING condition constructed from attributes of
  GROUP BY list and aggregates of attributes not in
  list

SELECT T.StudId, AVG(T.Grade) AS CumGpa,
COUNT () AS NumCrs FROM Transcript
T WHERE T.CrsCode LIKE CS GROUP BY
T.StudId HAVING AVG (T.Grade) gt 3.5
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Example

• Output the name and address of all seniors on the
  Deans List

SELECT S.Name, S.Address FROM Student S,
Transcript T WHERE S.StudId T.StudId AND
S.Status senior GROUP BY HAVING AVG
(T.Grade) gt 3.5 AND SUM (T.Credit) gt 90
S.StudId -- wrong S.Name,
S.Address -- right
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SQL and Relational Algebra

• RELATIONAL ALGEBRA SQL 
• PSEUDO-CODE
•  
• 1) R customers where city 'Dallas' SELECT
  from customers where city 'Dallas'
•  
• For c1 first row of customers until c1 last
  row of customers
• If c1.city Dallas
• Display c1.
• End-If
• End-For
•  
•  
• 2) R customers cid, cname SELECT
  cid, cname from customers
•  
• For c1 first row of customers until c1 last
  row of customers
• Display c1.cid, c1.cname
• End-For

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Constructing SQL
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Aggregate Functions

• Aggregate Functions are functions that take a
  collection (a set or multiset) of values as input
  and return a single value.
• SQL offers five built-in aggregate functions
• Average avg
• Minimum min
• Maximum max
• Total sum
• Count count

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Embedded SQL

• The SQL standard defines embeddings of SQL in a
  variety of programming languages such as C,
  Cobol, Java, Pascal, etc.
• A language in which SQL queries are embedded is
  referred to as a host language, and the SQL
  structures permitted in the host language
  constitute embedded SQL.

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Embedded SQL cont

• Two important reasons why a programmer must have
  access to a database from a general purpose
  programming language
• 1. Not all queries can be expressed in SQL,
  since SQL does not provide the full expressive
  power of a general-purpose language.
• 2. Nondeclarative actions such as printing a
  report, interacting with a user, or sending the
  results of a query to a graphical user interface
  cannot be done from within SQL.

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Dynamic SQL

• The dynamic SQL component of SQL allows programs
  to construct and submit SQL queries at run-time.
• Using dynamic SQL, programs can create SQL
  queries as strings at run time (perhaps based on
  input from the user) and can either have them
  executed immediately or have them prepared for
  subsequent use.

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Relational Algebra and SQL
Read the following
http//www.cs.ru.nl/gerp/IS0/sheets/IS0_Relatione
le_Algebra_SQL2.pdf