1. CPSC-310 Database Systems
Professor Jianer Chen
Room 315C HRBB
Lecture #13

2. SQL (continued) Basic Query Statement: SELECT attributes
FROM tables
WHERE conditions
The result of the query is a relation, which can be used in places where a regular relation appears.

3. Our Running Example
Our SQL queries will be based on the following database schema (Underline indicates key attributes)
Beers(name, manf)
Bars(name, addr, license)
Drinkers(name, addr, phone)
Likes(drinker, beer)
Sells(bar, beer, price)
Frequents(drinker, bar)

4. Subqueries
A parenthesized SELECT-FROM- WHERE statement (subquery) can be used as a value in a number of places, including FROM and WHERE clauses.

5. Subqueries
A parenthesized SELECT-FROM- WHERE statement (subquery) can be used as a value in a number of places, including FROM and WHERE clauses.
Example: in place of a relation in the FROM clause, we can place another query, and then query its result.

6. Subqueries
A parenthesized SELECT-FROM- WHERE statement (subquery) can be used as a value in a number of places, including FROM and WHERE clauses.
Example: in place of a relation in the FROM clause, we can place another query, and then query its result.
* Better use a tuple-variable to name tuples of the result.

7. Subqueries That Return One Tuple
If a subquery is guaranteed to produce one tuple, then the subquery can be used as a value.
Usually, the tuple has one component.
A run-time error occurs if there is no tuple or more than one tuple.

8. Query + Subquery Solution
Sells(bar, beer, price)
Query + Subquery Solution
SELECT bar
FROM Sells
WHERE beer = ’Miller’ AND
price = (SELECT price
WHERE bar = ’Joe’’s Bar’
AND beer = ’Bud’);
The price at
which Joe
sells Bud

9. The IN Operator

10. The IN Operator
<tuple> IN <relation> is true if and only if the tuple is a member of the relation.

11. The IN Operator
<tuple> IN <relation> is true if and only if the tuple is a member of the relation.
-- <tuple> NOT IN <relation> means the opposite.

12. The IN Operator
<tuple> IN <relation> is true if and only if the tuple is a member of the relation.
-- <tuple> NOT IN <relation> means the opposite.
IN-expressions can appear in WHERE clauses.

13. The IN Operator
<tuple> IN <relation> is true if and only if the tuple is a member of the relation.
-- <tuple> NOT IN <relation> means the opposite.
IN-expressions can appear in WHERE clauses.
The <relation> is often a subquery.

14. The IN Operator
<tuple> IN <relation> is true if and only if the tuple is a member of the relation.
-- <tuple> NOT IN <relation> means the opposite.
IN-expressions can appear in WHERE clauses.
The <relation> is often a subquery.
Example. From Beers(name, manf) and Likes(drinker, beer), find the name and manufacturer of each beer that Fred likes.

15. The IN Operator
<tuple> IN <relation> is true if and only if the tuple is a member of the relation.
-- <tuple> NOT IN <relation> means the opposite.
IN-expressions can appear in WHERE clauses.
The <relation> is often a subquery.
Example. From Beers(name, manf) and Likes(drinker, beer), find the name and manufacturer of each beer that Fred likes.
beers Fred
likes
(SELECT beer
FROM Likes
WHERE drinker = ’Fred’);

16. The IN Operator
<tuple> IN <relation> is true if and only if the tuple is a member of the relation.
-- <tuple> NOT IN <relation> means the opposite.
IN-expressions can appear in WHERE clauses.
The <relation> is often a subquery.
Example. From Beers(name, manf) and Likes(drinker, beer), find the name and manufacturer of each beer that Fred likes.
SELECT *
FROM Beers
WHERE name IN
beers Fred
likes
(SELECT beer
FROM Likes
WHERE drinker = ’Fred’);

17. The IN Operator
<tuple> IN <relation> is true if and only if the tuple is a member of the relation.
-- <tuple> NOT IN <relation> means the opposite.
IN-expressions can appear in WHERE clauses.
The <relation> is often a subquery.
Example. From Beers(name, manf) and Likes(drinker, beer), find the name and manufacturer of each beer that Fred likes.
SELECT *
FROM Beers
WHERE name IN
beers Fred
likes
(SELECT beer
FROM Likes
WHERE drinker = ’Fred’);

18. The IN Operator
<tuple> IN <relation> is true if and only if the tuple is a member of the relation.
-- <tuple> NOT IN <relation> means the opposite.
IN-expressions can appear in WHERE clauses.
The <relation> is often a subquery.
Example. From Beers(name, manf) and Likes(drinker, beer), find the name and manufacturer of each beer that Fred likes.
SELECT *
FROM Beers
WHERE name IN
(SELECT beer
FROM Likes
WHERE drinker = ’Fred’);

19. The Exists Operator
EXISTS(<relation>) is true if and only if the <relation> is not empty.

20. The Exists Operator
EXISTS(<relation>) is true if and only if the <relation> is not empty.
Example: From Beers(name, manf), find those beers that are the unique beer by their manufacturer.

21. The Exists Operator
EXISTS(<relation>) is true if and only if the <relation> is not empty.
Example: From Beers(name, manf), find those beers that are the unique beer by their manufacturer.
SELECT name
FROM Beers b1
WHERE NOT EXISTS (SELECT *
FROM Beers
WHERE manf = b1.manf AND
name <> b1.name);

22. The Exists Operator
EXISTS(<relation>) is true if and only if the <relation> is not empty.
Example: From Beers(name, manf), find those beers that are the unique beer by their manufacturer.
SELECT name
FROM Beers b1
WHERE NOT EXISTS (SELECT *
FROM Beers
WHERE manf = b1.manf AND
name <> b1.name);
There should not be other beers that are made by the manf of b1

23. The Exists Operator
EXISTS(<relation>) is true if and only if the <relation> is not empty.
Example: From Beers(name, manf), find those beers that are the unique beer by their manufacturer.
SELECT name
FROM Beers b1
WHERE NOT EXISTS (SELECT *
FROM Beers
WHERE manf = b1.manf AND
name <> b1.name);
The set of beers that are not b1 but made by the same manf of b1 should be empty

24. The Exists Operator
EXISTS(<relation>) is true if and only if the <relation> is not empty.
Example: From Beers(name, manf), find those beers that are the unique beer by their manufacturer.
SELECT name
FROM Beers b1
WHERE NOT EXISTS (SELECT *
FROM Beers
WHERE manf = b1.manf AND
name <> b1.name);
The set of beers that are not b1 but made by the same manf of b1 should be empty

25. The Exists Operator
EXISTS(<relation>) is true if and only if the <relation> is not empty.
Example: From Beers(name, manf), find those beers that are the unique beer by their manufacturer.
SELECT name
FROM Beers b1
WHERE NOT EXISTS (SELECT *
FROM Beers
WHERE manf = b1.manf AND
name <> b1.name);
The set of beers that are not b1 but made by the same manf of b1 should be empty

26. The Exists Operator
EXISTS(<relation>) is true if and only if the <relation> is not empty.
Example: From Beers(name, manf), find those beers that are the unique beer by their manufacturer.
Notice scope rule: manf refers
to closest nested FROM with
a relation having that attribute.
SELECT name
FROM Beers b1
WHERE NOT EXISTS (SELECT *
FROM Beers
WHERE manf = b1.manf AND
name <> b1.name);
The set of beers that are not b1 but made by the same manf of b1 should be empty

27. The Exists Operator
EXISTS(<relation>) is true if and only if the <relation> is not empty.
Example: From Beers(name, manf), find those beers that are the unique beer by their manufacturer.
Notice scope rule: manf refers
to closest nested FROM with
a relation having that attribute.
SELECT name
FROM Beers b1
WHERE NOT EXISTS (SELECT *
FROM Beers
WHERE manf = b1.manf AND
name <> b1.name);
The set of beers that are not b1 but made by the same manf of b1 should be empty
Notice the SQL “not equals” operator

28. The Exists Operator
EXISTS(<relation>) is true if and only if the <relation> is not empty.
Example: From Beers(name, manf), find those beers that are the unique beer by their manufacturer.
SELECT name
FROM Beers b1
WHERE NOT EXISTS (SELECT *
FROM Beers
WHERE manf = b1.manf AND
name <> b1.name);

29. The Operators ANY and ALL

30. The Operators ANY and ALL
x = ANY(<relation>) is true if x equals at least one tuple in the relation.

31. The Operators ANY and ALL
x = ANY(<relation>) is true if x equals at least one tuple in the relation.
= can be any other comparison operators.

32. The Operators ANY and ALL
x = ANY(<relation>) is true if x equals at least one tuple in the relation.
= can be any other comparison operators.
-- Example: x >= ANY(<relation>) means x is not smaller than the smallest tuple in the relation.

33. The Operators ANY and ALL
x = ANY(<relation>) is true if x equals at least one tuple in the relation.
= can be any other comparison operators.
-- Example: x >= ANY(<relation>) means x is not smaller than the smallest tuple in the relation. -- Here, tuples must have only one component.

34. The Operators ANY and ALL
x = ANY(<relation>) is true if x equals at least one tuple in the relation.
= can be any other comparison operators.
-- Example: x >= ANY(<relation>) means x is not smaller than the smallest tuple in the relation. -- Here, tuples must have only one component.
x <> ALL(<relation>) is true if for every tuple t in the relation, x is not equal to t. -- That is, x is not a member of the relation.

35. The Operators ANY and ALL
x = ANY(<relation>) is true if x equals at least one tuple in the relation.
= can be any other comparison operators.
-- Example: x >= ANY(<relation>) means x is not smaller than the smallest tuple in the relation. -- Here, tuples must have only one component.
x <> ALL(<relation>) is true if for every tuple t in the relation, x is not equal to t. -- That is, x is not a member of the relation.
<> can be any other comparison operator.

36. The Operators ANY and ALL
x = ANY(<relation>) is true if x equals at least one tuple in the relation.
= can be any other comparison operators.
-- Example: x >= ANY(<relation>) means x is not smaller than the smallest tuple in the relation. -- Here, tuples must have only one component.
x <> ALL(<relation>) is true if for every tuple t in the relation, x is not equal to t. -- That is, x is not a member of the relation.
<> can be any other comparison operator. -- Example: x >= ALL(<relation>) means there is no tuple larger than x in the relation

37. Example
From Sells(bar, beer, price), find the beer(s) sold for the highest price.

38. Example
From Sells(bar, beer, price), find the beer(s) sold for the highest price.
SELECT price
FROM Sells
collect all beer prices

39. Example
From Sells(bar, beer, price), find the beer(s) sold for the highest price.
SELECT beer
FROM Sells
WHERE price >= ALL( );
SELECT price
FROM Sells
select the beers whose price is not smaller than any price
collect all beer prices

40. Example
From Sells(bar, beer, price), find the beer(s) sold for the highest price.
SELECT beer
FROM Sells
WHERE price >= ALL( );
SELECT price
FROM Sells

41. Union, Intersection, and Difference
Union, intersection, and difference of relations are expressed by the following forms, each involving subqueries:
(subquery) UNION (subquery)
(subquery) INTERSECT (subquery)
(subquery) EXCEPT (subquery)

42. Likes(drinker, beer)
Sells(bar, beer, price)
Frequents(drinker, bar)
Example
From relations Likes, Sells, and Frequents, find the drinkers and beers such that:
The drinker likes the beer, and
The drinker frequents at least one bar that sells the beer.

43. Likes(drinker, beer)
Sells(bar, beer, price)
Frequents(drinker, bar)
Example
From relations Likes, Sells, and Frequents, find the drinkers and beers such that:
The drinker likes the beer, and
The drinker frequents at least one bar that sells the beer.
the drinker likes the beer.
(SELECT * FROM Likes)

44. Likes(drinker, beer)
Sells(bar, beer, price)
Frequents(drinker, bar)
Example
From relations Likes, Sells, and Frequents, find the drinkers and beers such that:
The drinker likes the beer, and
The drinker frequents at least one bar that sells the beer.
the drinker likes the beer.
(SELECT * FROM Likes)
INTERSECT
(SELECT drinker, beer
FROM Sells, Frequents
WHERE Frequents.bar = Sells.bar );
The drinker frequents a bar that sells the beer.

45. Likes(drinker, beer)
Sells(bar, beer, price)
Frequents(drinker, bar)
Example
From relations Likes, Sells, and Frequents, find the drinkers and beers such that:
The drinker likes the beer, and
The drinker frequents at least one bar that sells the beer.
the drinker likes the beer.
(SELECT * FROM Likes)
INTERSECT
(SELECT drinker, beer
FROM Sells, Frequents
WHERE Frequents.bar = Sells.bar );
The drinker frequents a bar that sells the beer.

46. Likes(drinker, beer)
Sells(bar, beer, price)
Frequents(drinker, bar)
Example
From relations Likes, Sells, and Frequents, find the drinkers and beers such that:
The drinker likes the beer, and
The drinker frequents at least one bar that sells the beer.
(SELECT * FROM Likes)
INTERSECT
(SELECT drinker, beer
FROM Sells, Frequents
WHERE Frequents.bar = Sells.bar );

47. Bag Semantics

48. Bag Semantics
Although the SELECT-FROM-WHERE statement uses bag semantics, the default for union, intersection, and difference is set semantics.
-- That is, duplicates are eliminated

49. Bag Semantics
Although the SELECT-FROM-WHERE statement uses bag semantics, the default for union, intersection, and difference is set semantics.
-- That is, duplicates are eliminated
Why?

50. Bag Semantics
Although the SELECT-FROM-WHERE statement uses bag semantics, the default for union, intersection, and difference is set semantics.
-- That is, duplicates are eliminated
Why?  for efficiency

51. Bag Semantics
Although the SELECT-FROM-WHERE statement uses bag semantics, the default for union, intersection, and difference is set semantics.
-- That is, duplicates are eliminated
Why?  for efficiency
When doing projection, it is easier to avoid eliminating duplicates.
-- Just work tuple-at-a-time.

52. Bag Semantics
Although the SELECT-FROM-WHERE statement uses bag semantics, the default for union, intersection, and difference is set semantics.
-- That is, duplicates are eliminated
Why?  for efficiency
When doing projection, it is easier to avoid eliminating duplicates.
-- Just work tuple-at-a-time.
For intersection or difference, it is most efficient to sort the relations first.

53. Bag Semantics
Although the SELECT-FROM-WHERE statement uses bag semantics, the default for union, intersection, and difference is set semantics.
-- That is, duplicates are eliminated
Why?  for efficiency
When doing projection, it is easier to avoid eliminating duplicates.
-- Just work tuple-at-a-time.
For intersection or difference, it is most efficient to sort the relations first.
-- So you may as well eliminate the duplicates anyway.

54. Controlling Duplicate Elimination
Force the result to be a set by SELECT DISTINCT . . .

55. Controlling Duplicate Elimination
Force the result to be a set by SELECT DISTINCT . . .
Force the result to be a bag (i.e., don’t eliminate duplicates) by ALL, as in UNION ALL . . .

56. Example: DISTINCT
From Sells(bar, beer, price), find all the different prices charged for beers:

57. Example: DISTINCT
From Sells(bar, beer, price), find all the different prices charged for beers:
SELECT DISTINCT price
FROM Sells;

58. Example: DISTINCT
From Sells(bar, beer, price), find all the different prices charged for beers:
SELECT DISTINCT price
FROM Sells;
Notice that without DISTINCT, each price would be listed as many times as there were bar/beer pairs at that price.

59. Example: ALL
Using relations Frequents(drinker, bar) and Likes(drinker, beer), list drinkers who frequent more bars than they like beers, and does so as many times as the difference of those counts.

60. Example: ALL
Using relations Frequents(drinker, bar) and Likes(drinker, beer), list drinkers who frequent more bars than they like beers, and does so as many times as the difference of those counts.
(SELECT drinker FROM Frequents)
EXCEPT ALL
(SELECT drinker FROM Likes);

61. Join Expressions SQL provides several versions of (bag) joins.
These expressions can be stand-alone queries or used in place of relations in a FROM clause.

62. Products and Natural Joins
Cross join (Cartesian Product): R CROSS JOIN S;

63. Products and Natural Joins
Cross join (Cartesian Product): R CROSS JOIN S;
A B 2
3 4
CROSS JOIN
B C D
5 6 R S
A R.B S.B C D

64. Products and Natural Joins
Natural join (join tuples agreeing on common attributes): R NATURAL JOIN S;

65. Products and Natural Joins
Natural join (join tuples agreeing on common attributes): R NATURAL JOIN S;
A B 2
3 4
NATURAL JOIN
B C D
5 6 R S
A B C D

66. Theta Join
R JOIN S ON <condition>

67. Theta Join R JOIN S ON <condition> R S A B B C D 2 5 6 4 5 JOIN
4 5
JOIN
B C D
5 6 R S
A R.B S.B C D
ON A < D;

68. Theta Join R JOIN S ON <condition>
Drinkers(name, addr)
Frequents(drinker, bar)
Theta Join
R JOIN S ON <condition>
Example: using Drinkers and Frequents:
Drinkers JOIN Frequents
ON name = drinker;
gives all (d, a, d, b) quadruples such that drinker d lives at address a and frequents bar b.
A B 2
4 5
JOIN
B C D
5 6 R S
A R.B S.B C D
ON A < D;

69. Outerjoins
R OUTER JOIN S is the core of an outerjoin expression. It is modified by:
Optional NATURAL in front of OUTER.
Optional ON <condition> after JOIN.
Optional LEFT, RIGHT, or FULL before OUTER.
LEFT = pad dangling tuples of R only.
RIGHT = pad dangling tuples of S only.
FULL = pad both; this choice is the default.

70. Outerjoins (Examples)
R NATURAL FULL OUTER JOIN S
R NATURAL LEFT OUTER JOIN S
R NATURAL RIGHT OUTER JOIN S

71. Outerjoins (Examples)
R NATURAL FULL OUTER JOIN S
A B 2
3 9
B C D
5 6 R
NATURAL FULL OUTER JOIN S
A B C D
N N N

72. Outerjoins (Examples)
R NATURAL LEFT OUTER JOIN S
A B 2
3 9
B C D
5 6 R
NATURAL LEFT OUTER JOIN S
A B C D
N N

73. Outerjoins (Examples)
R NATURAL RIGHT OUTER JOIN S
A B 2
3 9
B C D
5 6 R
NATURAL RIGHT OUTER JOIN S
A B C D N