sql-dml.ppt

SQL – DISTINCT
• Eliminates all the duplicate entries in the table resulting from the query.
Syntax:
Select [DISTINCT] select_list
From table[, table, …]
[Where expression]
[Order By expression]
Example:
Select DISTINCT studio_id, director_id
From Movies
studio_id director_id
1 1
2 2
2 10
3 1
3 9

SQL – Order By
• Used to sort the results based on contents of a column
• Multiple levels of sort can be done by specifying
multiple columns
• An expression can be used in Order By clause
Syntax:
Select function(column)
From table1 [, table2 …]
[Where condition]
[Order By {Column | alias | position} [ASC | DESC]]

SQL – Order By
Example: Sort Movies by profits in Ascending order
Select MovieTitle, Gross, Budget, (Gross – Budget) as profits
From movies
Order BY profits
Great Escape
67.5 70 -2.5
Upside Down 54 50 4
Green Warrior 96 80 16
Blue Oranges 28 7 21
Movie_title Gross Budget Profit

Aggregate Queries – Group
By
• Categorizes the query results according to the contents of a
column in the database
• Multiple levels of subgroups can be created by specifying
multiple columns
Syntax:
Select column1, [column2, …]
From table [, table …]
[Where condition]
Group By column1, [column2, ….]
Having [Condition]

By
Example: Get # of movies by each director for each studio
Select studio_id, director_id, count(*)
From Movies
Group By director_id, studio_id
Example: Get # of movies by each studio ordered by studio_id
Select studio_id, count(*)
From Movies
Group By studio_id
Order By studio_id

By
Example:
Select studio_id, Sum(budget)
From movies
Group by studio_id
Having Sum(budget) > 60
Example:
Select studio_id, count(*)
From Movies
Group By studio_id
Order By studio_id

Aggregate Queries
• Aggregate queries provides a more holistic view of
the data by further processing the retrieved data.
• They can work on
– On all the rows in a table
– A subset of rows in a table selected using a where clause
– Groups of selected data organized using Group By clause.
Syntax:
Select function(column)
From <list of tables>
Where <condition>
Group By <list of columns>
Having <condition>

Aggregate Queries
• Functions:
– Sum() Returns a sum of the column
– Count()Returns a total number of rows returned by a query
– Avg() Returns the average of a column
– Min() Returns minimum value of the column returned by query
– Max() Returns maximum value of the column returned by query
Notes 1: Count function does not include columns containing null values in total
Notes 2: Count can be used with distinct to count the number of distinct rows
Example:
Query: Select sum(budget)
From movies
Where studio_id = 3
Output: Sum(budget)
---------------
65.1

SQL – Join
• A Join is a Query that combines data from multiple
tables
– Multiple tables are specified in the From Clause
– For two tables to be joined in a sensible manner, they need
to have data in common
Example:
Schema: Movies (movie_title, director_id, release_date)
People(person_fname, person_lname, person_id)
Query: Select movie_title, person_fname, person_lname
From Movies, People
Where director_id = person_id

SQL – Joining Condition
• For a useful Join query a joining condition is required
– Defined in where clause as relationships between columns
– Multiple conditions may be defined if multiple columns
shared
– More than two tables can be joined in a query
Example: Find people who live in same state as studio
Schema:
Studios(studio_id, studio_state, studio_name, studio_city)
People(person_fname, person_lname, person_id, person_state, person_city)
Query:
Select person_fname, person_lname, studio_name
From Movies, People
Where studio_city = person_city
AND studio_state = person_state

SQL – More than two tables
Example: Get title, director, studio, city for all movies in
the database
Schema:
Movies(movie_title, director_id, studio_id)
Query:
Select M.movie_title, M.studio_id, P.person_fname, P.person_lname,
S.studio_city
From Movies M, People P, Studio S
Where M.director_id = P.person_id
AND M.studio_id = P.person_id

SQL – Self Join
• Required to compare values within a single column
– Need to define aliases for the table names
Example: Find actors living in the same state
Schema:
Query:
Select p1.person_id, p1.person_fname, p1.person_lname, p1.person_state
From People p1, People p2
Where p1.person_state = p2.person_state
AND p1.person_id != p2.person_id
Note: Distinct operator is critical because if there are more than two people
from any state each person will appear as many times as there are
people from the state

SQL-92 – Join
• More verbose than pervious versions of SQL
– Need to define aliases for the table names
• Separates the condition for joining from condition for filtering
Example: Find actors living in the same state
Schema:
Query:
Select movie_title, person_fname, person_lname
From Movies INNER JOIN People
ON director_id = person_id
From Movies INNER JOIN People
ON director_id = person_id
Where studio_id = 1

SQL-92 – Multiple Table Join
Example: Get title, director, studio, city for all movies in database
Schema:
Query:
Select Movies.movie_title, Movies.studio_id, Person.person_fname,
Person.person_lname, Studio.studio_city
From (People Inner Join
(Movies Inner Join Studio
On Studio.studio_id = Movie.studio_id)
On Movie.director_id = Person.person_id

SQL-92 – Left/Right Join
Example:
Schema:
Movies(movie_id, movie_title, director_id, studio_id)
Location(movie_id, city, state)
Query:
Select movie_title, city, state
From Movies Left Join Locations
On Movies.movie_id = Locations.movie_id
From Movies Right Join People
On Movies.director_id = Person.person_id
Includes all
non matched
movie titles
Includes
all people
not matching
to directors

Nested Queries
• A sub query is a query nested within another query
– The enclosing query also called outer query
– Nested query is called inner query
• There can be multiple levels of nesting
Example:
Select movie_title
From movies
Where director_id IN (
Select person_id
From People
Where person_state = ‘TX’)

Nested Queries - Types
Non-Correlated Sub Queries:
– Requires data required by outer query before it can be executed
– Inner query does not contain any reference to outer query
– Behaves like a function
Example:
Movies(movie_id, movie_title, director_id, studio_id)
Select movie_title, studio_id
From Movies
Where director_id IN (
Select person_id
From People
Where person_state = ‘TX’)
Steps:
1. Subquery is executed
2. Subquery results are plugged into the outer query
3. The outer query is processed

Nested Queries - Types
Correlated Sub Queries:
– Contains reference to the outer query
– Behaves like a loop
Example:
Cast_Movies(cast_member_id, role, movie_id)
Select person_fname, person_lname
From People p1
Where ‘Pam Green’ in (
Select role
From Cast_Movies
Where p1.person_id = cast_member_id
)
Steps:
– Contents of the table row in outer query are read
– Sub-query is executed using data in the row being processed.
– Results of the inner query are passed to the where in the outer query
– The Outer query is Processed

Equivalent Join Query
Example:
Cast_Movies(cast_member_id, role, movie_id)
Select person_fname, person_lname
From People, Cast_Movies
Where Cast_member_id = person_id
And role = ‘Pam Green’

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