1. CPSC-608 Database Systems
Fall 2017
Instructor: Jianer Chen
Office: HRBB 315C
Phone:
Notes 3

2. SQL: Structured Query language
a very-high-level language. * say “what to do” rather than “how to do it.” * avoid a lot of data-manipulation details needed in procedural languages like C or Java.
Database management system figures out the “best” way to execute queries * called “query optimization”
For both data definition and data manipulation.

3. Creating (Declaring) a Relation
Simplest form is:
CREATE TABLE <name> (
<list of elements> );

4. Creating (Declaring) a Relation
Simplest form is:
CREATE TABLE <name> (
<list of elements> );
Example:
CREATE TABLE Drinkers (
name CHAR(30) PRIMARY KEY,
addr CHAR(50)
DEFAULT ’123 Sesame St.’,
phone CHAR(16) NOT NULL );

5. Changing Relation Schema: Adding Attributes
We may add a new attribute (“column”) to a relation schema by:
ALTER TABLE <name> ADD
<attribute declaration>;

6. Changing Relation Schema: Adding Attributes
We may add a new attribute (“column”) to a relation schema by:
ALTER TABLE <name> ADD
<attribute declaration>;
Example:
ALTER TABLE Bars ADD
phone CHAR(16)DEFAULT ’unlisted’;

7. Changing Relation Schema: Deleting Attributes
Remove an attribute from a relation schema by:
ALTER TABLE <name>
DROP <attribute>;

8. Changing Relation Schema: Deleting Attributes
Remove an attribute from a relation schema by:
ALTER TABLE <name>
DROP <attribute>;
Example: we don’t really need the license attribute for bars:
ALTER TABLE Bars DROP license;

9. Changing Relation Schema: Removing Relations
To delete a relation:
DROP TABLE <name>;

10. SQL: Structured Query language
How does SQL manipulate (search in/read from/write to) tables?

11. SQL: Structured Query language
How does SQL manipulate (search in/read from/write to) tables?
This is the job of a data manipulation language (DML). DML does not change database schema.

12. Select-From-Where Statements
SELECT attributes
FROM tables
WHERE conditions

13. Select-From-Where Statements
SELECT attributes
FROM tables
WHERE conditions
input

14. Select-From-Where Statements
SELECT attributes
FROM tables
WHERE conditions
output (as a table)
input

15. Our Running Example
All 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)

16. Example
Using Beers(name, manf), what beers are made by Anheuser-Busch?
SELECT name
FROM Beers
WHERE manf=’Anheuser-Busch’;

17. Example
Using Beers(name, manf), what beers are made by Anheuser-Busch?
SELECT name
FROM Beers
WHERE manf=’Anheuser-Busch’;
Notice SQL uses single-quotes for strings.
SQL is case-insensitive, except inside strings.

18. Result of Query name Bud Bud Lite Michelob ……
The answer is a relation with a single attribute,
name, and tuples with the name of each beer
by Anheuser-Busch, such as Bud.

19. Meaning of Single-Relation Query

20. Meaning of Single-Relation Query
Begin with the relation in the FROM clause.

21. Meaning of Single-Relation Query
Begin with the relation in the FROM clause.
Apply the selection indicated by the WHERE clause.

22. Meaning of Single-Relation Query
Begin with the relation in the FROM clause.
Apply the selection indicated by the WHERE clause.
Apply the extended projection indicated by the SELECT clause.

23. Meaning of Single-Relation Query
Begin with the relation in the FROM clause.
Apply the selection indicated by the WHERE clause.
Apply the extended projection indicated by the SELECT clause.
SELECT attributes
FROM tables
WHERE conditions

24. Meaning of Single-Relation Query
Begin with the relation in the FROM clause.
Apply the selection indicated by the WHERE clause.
Apply the extended projection indicated by the SELECT clause.
SELECT attributes
FROM tables
WHERE conditions
Step 3
Step 1
Step 2

25. Operational Semantics
Beers
name
manf
Bud
Anheuser-Busch
SELECT name
FROM Beers
WHERE manf=’Anheuser-Busch’;

26. Operational Semantics
Beers
name
manf
Bud
Anheuser-Busch
To implement this algorithm think of a tuple variable tv ranging over each tuple of the relation mentioned in the FROM Clause. tv
SELECT name
FROM Beers
WHERE manf=’Anheuser-Busch’;

27. Operational Semantics
Beers
name
manf
Bud
Anheuser-Busch
To implement this algorithm think of a tuple variable tv ranging over each tuple of the relation mentioned in the FROM Clause.
Check if the “current” tuple satisfies the WHERE clause. tv
Check if manf =
Anheuser-Busch
SELECT name
FROM Beers
WHERE manf=’Anheuser-Busch’;

28. Operational Semantics
Beers
Include tv.name
in the result
name
manf
Bud
Anheuser-Busch
To implement this algorithm think of a tuple variable tv ranging over each tuple of the relation mentioned in the FROM Clause.
Check if the “current” tuple satisfies the WHERE clause.
If so, compute the attributes or expressions of the SELECT clause using the components of this tuple. tv
Check if manf =
Anheuser-Busch
SELECT name
FROM Beers
WHERE manf=’Anheuser-Busch’;

29. * in SELECT clauses

30. * in SELECT clauses
When there is one relation in the FROM clause, * in the SELECT clause stands for “all attributes of this relation.”

31. * in SELECT clauses SELECT *
When there is one relation in the FROM clause, * in the SELECT clause stands for “all attributes of this relation.”
Example using Beers(name, manf):
SELECT *
FROM Beers
WHERE manf = ’Anheuser-Busch’;

32. * in SELECT clauses SELECT *
When there is one relation in the FROM clause, * in the SELECT clause stands for “all attributes of this relation.”
Example using Beers(name, manf):
SELECT *
FROM Beers
WHERE manf = ’Anheuser-Busch’;
The output has the same schema as Beers:
name
manf
Bud
Anheuser-Busch
Bud Lite
Michelob ……

33. Renaming Attributes

34. Renaming Attributes
you want the result to have different attribute names, use “AS <new name>” to rename an attribute.

35. Renaming Attributes SELECT name AS beer, manf
you want the result to have different attribute names, use “AS <new name>” to rename an attribute.
Example using Beers(name, manf):
SELECT name AS beer, manf
FROM Beers
WHERE manf = ’Anheuser-Busch’

36. Renaming Attributes SELECT name AS beer, manf
you want the result to have different attribute names, use “AS <new name>” to rename an attribute.
Example using Beers(name, manf):
SELECT name AS beer, manf
FROM Beers
WHERE manf = ’Anheuser-Busch’
The result is:
beer
manf
Bud
Anheuser-Busch
Bud Lite
Michelob ……

37. Expressions in SELECT Clauses

38. Expressions in SELECT Clauses
Any expression that makes sense can appear as an element of a SELECT clause.

39. Expressions in SELECT Clauses
Any expression that makes sense can appear as an element of a SELECT clause.
Example: from Sells(bar, beer, price):
SELECT bar, beer,
price*114 AS priceInYen
FROM Sells;

40. Expressions in SELECT Clauses
Any expression that makes sense can appear as an element of a SELECT clause.
Example: from Sells(bar, beer, price):
SELECT bar, beer,
price*114 AS priceInYen
FROM Sells;
The result is
bar
beer
priceInYen
Joe’s
Bud
285
Sue’s
Miller
342 ……

41. Expressions in SELECT Clauses
We can also have a “constant expression” in the SELECT clause.

42. Expressions in SELECT Clauses
We can also have a “constant expression” in the SELECT clause.
Example: from Likes(drinker, beer):
SELECT drinker,
‘likes Bud’ AS whoLikesBud
FROM Likes;
WHERE beer = ‘Bud’;

43. Expressions in SELECT Clauses
We can also have a “constant expression” in the SELECT clause.
Example: from Likes(drinker, beer):
SELECT drinker,
‘likes Bud’ AS whoLikesBud
FROM Likes;
WHERE beer = ‘Bud’;
The result is
drinker
whoLikesBud
Sally
likes Bud
Fred ……

44. Complex Conditions in WHERE Clause
From Sells(bar, beer, price), find the price Joe’s Bar charges for Bud:
SELECT price
FROM Sells
WHERE bar = ’Joe’’s Bar’ AND
beer = ’Bud’;

45. Complex Conditions in WHERE Clause
From Sells(bar, beer, price), find the price Joe’s Bar charges for Bud:
SELECT price
FROM Sells
WHERE bar = ’Joe’’s Bar’ AND
beer = ’Bud’;
Notice how we get a single-quote in strings.

46. Patterns
WHERE clauses can have conditions in which a string is compared with a pattern, to check match.

47. Patterns
WHERE clauses can have conditions in which a string is compared with a pattern, to check match.
General form: <Attribute> LIKE <pattern> or <Attribute> NOT LIKE <pattern>

48. Patterns
WHERE clauses can have conditions in which a string is compared with a pattern, to check match.
General form: <Attribute> LIKE <pattern> or <Attribute> NOT LIKE <pattern>
Pattern is a quoted string with % = “any string”; _ = “any character.”

49. Patterns
WHERE clauses can have conditions in which a string is compared with a pattern, to check match.
General form: <Attribute> LIKE <pattern> or <Attribute> NOT LIKE <pattern>
Pattern is a quoted string with % = “any string”; _ = “any character.”
Example. From Drinkers(name, addr, phone), find the drinkers with exchange 555
SELECT name
FROM Drinkers
WHERE phone LIKE ’%555-_ _ _ _’;

50. NULL Values
Tuples in SQL relations can have NULL as a value for one or more components.
Meaning depends on context. Two common cases:
Missing value : e.g., we know Joe’s Bar has some address, but we don’t know what it is.
Inapplicable : e.g., the value of attribute spouse for an unmarried person.

51. Comparing NULL’s to Values
The logic of conditions in SQL is really 3- valued logic: TRUE, FALSE, UNKNOWN.

52. Comparing NULL’s to Values
The logic of conditions in SQL is really 3- valued logic: TRUE, FALSE, UNKNOWN.
When any value is compared with NULL, the truth value is UNKNOWN.

53. Comparing NULL’s to Values
The logic of conditions in SQL is really 3- valued logic: TRUE, FALSE, UNKNOWN.
When any value is compared with NULL, the truth value is UNKNOWN.
But a query only produces a tuple in the answer if its truth value for the WHERE clause is TRUE (not FALSE or UNKNOWN).

54. Three-Valued Logic
To understand how AND, OR, and NOT work in 3-valued logic, think of TRUE = 1, FALSE = 0, and UNKNOWN = 1/2.

55. Three-Valued Logic
To understand how AND, OR, and NOT work in 3-valued logic, think of TRUE = 1, FALSE = 0, and UNKNOWN = 1/2.
AND = MIN; OR = MAX, NOT(x) = 1  x.

56. Three-Valued Logic
To understand how AND, OR, and NOT work in 3-valued logic, think of TRUE = 1, FALSE = 0, and UNKNOWN = 1/2.
AND = MIN; OR = MAX, NOT(x) = 1  x.
Example: TRUE AND (FALSE OR NOT(UNKNOWN))

57. Three-Valued Logic
To understand how AND, OR, and NOT work in 3-valued logic, think of TRUE = 1, FALSE = 0, and UNKNOWN = 1/2.
AND = MIN; OR = MAX, NOT(x) = 1  x.
Example: TRUE AND (FALSE OR NOT(UNKNOWN)) = MIN(1, MAX(0, (11/2)))

58. Three-Valued Logic
To understand how AND, OR, and NOT work in 3-valued logic, think of TRUE = 1, FALSE = 0, and UNKNOWN = 1/2.
AND = MIN; OR = MAX, NOT(x) = 1  x.
Example: TRUE AND (FALSE OR NOT(UNKNOWN)) = MIN(1, MAX(0, (11/2))) = MIN(1, MAX(0, 1/2)

59. Three-Valued Logic
To understand how AND, OR, and NOT work in 3-valued logic, think of TRUE = 1, FALSE = 0, and UNKNOWN = 1/2.
AND = MIN; OR = MAX, NOT(x) = 1  x.
Example: TRUE AND (FALSE OR NOT(UNKNOWN)) = MIN(1, MAX(0, (11/2))) = MIN(1, MAX(0, 1/2) = MIN(1, 1/2)

60. Three-Valued Logic
To understand how AND, OR, and NOT work in 3-valued logic, think of TRUE = 1, FALSE = 0, and UNKNOWN = 1/2.
AND = MIN; OR = MAX, NOT(x) = 1  x.
Example: TRUE AND (FALSE OR NOT(UNKNOWN)) = MIN(1, MAX(0, (11/2))) = MIN(1, MAX(0, 1/2) = MIN(1, 1/2) = 1/2

61. Three-Valued Logic
To understand how AND, OR, and NOT work in 3-valued logic, think of TRUE = 1, FALSE = 0, and UNKNOWN = 1/2.
AND = MIN; OR = MAX, NOT(x) = 1  x.
Example: TRUE AND (FALSE OR NOT(UNKNOWN)) = MIN(1, MAX(0, (11/2))) = MIN(1, MAX(0, 1/2) = MIN(1, 1/2) = 1/2 (= UNKNOWN)

62. Surprising Example

63. Surprising Example From the following Sells relation: Sells bar beer
price
Joe’s Bar
Bud
NULL

64. Surprising Example From the following Sells relation: SELECT bar
beer
price
Joe’s Bar
Bud
NULL
SELECT bar
FROM Sells
WHERE price < 2.00 OR price >= 2.00;

65. Surprising Example From the following Sells relation: SELECT bar
beer
price
Joe’s Bar
Bud
NULL
SELECT bar
FROM Sells
WHERE price < 2.00 OR price >= 2.00;
UNKNOWN
UNKNOWN

66. Surprising Example From the following Sells relation: SELECT bar
beer
price
Joe’s Bar
Bud
NULL
SELECT bar
FROM Sells
WHERE price < 2.00 OR price >= 2.00;
UNKNOWN
UNKNOWN
UNKNOWN

67. Surprising Example From the following Sells relation: SELECT bar
beer
price
Joe’s Bar
Bud
NULL
SELECT bar
FROM Sells
WHERE price < 2.00 OR price >= 2.00;
UNKNOWN
UNKNOWN
UNKNOWN
So Joe’s Bar will not get printed!

68. Reason: 2-Valued Laws  3-Valued Laws

69. Reason: 2-Valued Laws  3-Valued Laws
Some laws in 2-valued logic, like commutativity of AND:  AND  =  AND , also hold in 3-valued logic.

70. Reason: 2-Valued Laws  3-Valued Laws
Some laws in 2-valued logic, like commutativity of AND:  AND  =  AND , also hold in 3-valued logic.
Not all, e.g., the law of the excluded middle:  OR NOT  = TRUE.

71. Reason: 2-Valued Laws  3-Valued Laws
Some laws in 2-valued logic, like commutativity of AND:  AND  =  AND , also hold in 3-valued logic.
Not all, e.g., the law of the excluded middle:  OR NOT  = TRUE.
Always holds in 2-valued logic

72. Reason: 2-Valued Laws  3-Valued Laws
Some laws in 2-valued logic, like commutativity of AND:  AND  =  AND , also hold in 3-valued logic.
Not all, e.g., the law of the excluded middle:  OR NOT  = TRUE.
Always holds in 2-valued logic
In 3-valued logic, when  = UNKNOWN, the left side is MAX(1/2, (1 – 1/2)) = 1/2  1.