1. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 Chapter 6 THE DATABASE LANGUAGE SQL 1

2. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 1. Project due 10/24 2. Exam II 10/22 3. 2.1. 10 multiple choices 3 points each 4. 2.2. 5 written SQL/RA/English 10 pointseach 5. 2.3 Two project questions 10 points each 2

3. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 'STAR''s WARS' 3

4. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 'STAR''s WARS' 4

5. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 SIMPLE QUERIES IN SQL SELECT DISTINCT MODEL FROM APLCHE; SELECT YEAR FROM APLCHE WHERE MODEL='BEL AIR'; SELECT DESCRIPTION, LITRES AS LTR, ENGINE_TYPE AS ENG, CUBIC_INCHES AS CID, RLINK FROM APLCHE WHERE MODEL='BEL AIR' AND YEAR=74; SELECT * FROM RADCRX WHERE RLINK=2080; SELECT MOD4 FROM RADCRX WHERE RLINK=2080; Section 6.1 5

6. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3 Lecture Related 6.3.1 Quizz sent to Dr. Lin 6.3.2 Colloquim talks 6.3.3 Project Related Questions 6

7. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.1.4 Pattern Matching in SQL (cont’d) Example 6.8 SELECT title FROM Movies WHERE title LIKE 'STAR''s%'; Example 6.8 SELECT title FROM Movies WHERE title LIKE 'STAR''s%'; Note that if your string contains single quote, put another single quote to distinguish between surrounding single quotes and the single quote itself. Note that if your string contains single quote, put another single quote to distinguish between surrounding single quotes and the single quote itself. Retrieve all movies that contain the ‘s in their name like: Logan’s Run, Alice’s Restaurant Retrieve all movies that contain the ‘s in their name like: Logan’s Run, Alice’s Restaurant 7

8. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.1.4 Pattern Matching in SQL (DB2) Example 6.8a Example 6.8a SELECT E.SSN, E.LNAME, E.BDATE SELECT E.SSN, E.LNAME, E.BDATE FROM EMPLOYEE E FROM EMPLOYEE E WHERE E.ADDRESS LIKE WHERE E.ADDRESS LIKE '%BELLAIRE%'; '%BELLAIRE%'; 8

9. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.1.4 Pattern Matching in SQL (DB2) Example 6.8b Example 6.8b SELECT E.SSN, E.FNAME, E.LNAME FROM EMPLOYEE E WHERE EXISTS (SELECT * FROM DEPENDENT D WHERE E.SSN = D.DEPSSN) AND EXISTS (SELECT * FROM DEPARTMENT P WHERE E.SSN =P.MGRSSN); 9

10. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6. The Database Language SQL 6.1 Simple Queries in SQL 6.2 Queries Involving More Than One Relation 6.3 Subqueries 6.4 Full-Relation Operation 6.5 Database Modification 6.6 Transactions in SQL 6.7 Summary of Chapter 6 6.8 References for chapter 6 10

11. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 SIMPLE QUERIES IN SQL Section 6.1 11

12. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 RA SQL 12

13. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.1 Simple Queries in SQL 6.1.1 Projecting in SQL 6.1.2 Selecting in SQL 6.1.3 Comparison of Strings 6.1.4 Pattern Matching in SQL 6.1.5 Dates and Times 6.1.6 Null Values and Comparisons Involving NULL 6.1.7 The Truth-Value UNKNOWN 6.1.8 Ordering the Output 6.1.9 Exercises for Section 6.1 13

14. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.1 Simple Queries in SQL (Selection and Projection) Example 6.1 Example 6.1 Selection Selection (SELECT * FROM Movies WHERE studioName = ‘Disney’ AND year = 1990); (SELECT * FROM Movies WHERE studioName = ‘Disney’ AND year = 1990); projection projection SELECT title, length FROM MOVIES SELECT title, length FROM MOVIES 14

15. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.1.6 Null Values and Comparisons Involving NULL (cont’d) Example 6.9 Let x have the value NULL x + 3 is NULL x IS NULL or x IS NOT NULL Example 6.9 Let x have the value NULL x + 3 is NULL x IS NULL or x IS NOT NULL select studioname from movies_null where null +3 = null; NO OUTPUT select studioname from movies_null where null +3 = null; NO OUTPUT select studioname from movies_null where select studioname from movies_null where null +3 IS null; all OUTPUT null +3 IS null; all OUTPUT 15

16. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.1.7 The Truth-Value UNKNOWN Example 6.10 SELECT Studioname Example 6.10 SELECT Studioname FROM Movies_null WHERE length is null; FROM Movies_null WHERE length is null; SELECT Studioname SELECT Studioname FROM Movies_null WHERE length = null; FROM Movies_null WHERE length = null; “>” and comparison are the same; NO PUTPUT 16

17. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.1.8 Ordering the Output (cont’d) Example 6.11 SELECT producerC#,title FROM Movies WHERE studioName = 'DISNEY' AND year = 1990 ORDER BY length DESC, title; Example 6.11 SELECT producerC#,title FROM Movies WHERE studioName = 'DISNEY' AND year = 1990 ORDER BY length DESC, title; Alos can be ORDERed BY year – 10 (expressions) Alos can be ORDERed BY year – 10 (expressions) 17

18. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 QUERIES INVOLVING MORE THAN ONE RELATION Section 6.2 18

19. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.2 Queries Involving More Than One Relation 6.2.1 Products and Joins in SQL 6.2.2 Disambiguating Attributes 6.2.3 Tuple Variables 6.2.4 Interpreting Multi-Relation Queries 6.2.5 Union, Intersection, and Difference of Queries 6.2.6 Exercises for Section 6.2 19

20. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.2.1 Products and Joins in SQL (Cartesian Product) Example 6.12a Movies(title, year, length, genre, studioName, producerC#) MovieExec(name, address, cert#, netWorth) SELECT * FROM Movies, MovieExec 20

21. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.2.1 Products and Joins in SQL (Equi/Theta Join) Example 6.12a SELECT * SELECT * FROM Movies, MovieExec WHERE title = 'STAR''s WARS' AND producerC# = cert#; 21

22. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.2.1 Products and Joins in SQL (Natural Join) Example 6.12b SELECT SELECT title, year, length, InColor, studioName, producerC#,name,address,netWorth FROM Movies, MovieExec WHERE title = 'STAR''s WARS' AND producerC# = cert#; 22

23. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.2.1 Natural Joins in SQL (DB1) SELECT S.SNUM, S.SNAME, S.STATUS, S.CITY, P.PNUM, P.PNAME, P.COLOR, P.WEIGHT FROMSUPPLIERS S, PARTS P Where S.CITY=P.CITY; 23

24. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.2.2 Disambiguating Attributes Example 6.13 SELECT MovieStar.name, MovieExec.name FROM MovieStar, MovieExec WHERE MovieStar.address = MovieExec.address; MovieExec.address; 24

25. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.2.3 Tuple Variables (cont’d) Example 6.14 SELECT Star1.name, Star2.name FROM MovieStar Star1, MovieStar Star2 WHERE Star1.address = Star2.address AND Star1.name < Star2.name; What’s the role of the second condition? What’s the role of the second condition? What would happen if we use <>? What would happen if we use <>? 25

26. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.2.4 Interpreting Multi-Relation Queries (relational algebra) Example 6.15 Convert the query of example 6.14 to RA. Π L1 (σ C1 And C2 (R X T)) Where: R = MovieStar Star1 T = MovieStar Star2 L1 = Star1.name, Start2.name C1 = Star1.address = Star2.address C2 = Star1.name < Star2.name 26

27. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.2.5 Union, Intersection, and Difference of Queries (cont’d) Example 6.16 (SELECT name, address FROM MovieStar WHERE gender = 'M') INTERSECT (SELECT name, address FROM MovieExec WHERE netWorth > 10000000); 27

28. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.2.5 Union, Intersection, and Difference of Queries (cont’d) Example 6.17 (SELECT name, address FROM MovieStar) MINUS (SELECT name, address FROM MovieExec); 28

29. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.2.5 Union, Intersection, and Difference of Queries (cont’d) Example 6.18 (SELECT title,year FROM Movies) INTERSECT (SELECT movieTitle AS title, movieYear AS year FROM StarsIn ); 29

30. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.2.6 Exercises for Section 6.2 30

31. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 SUBQUERIES Section 6.3 31

32. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3 Subqueries 6.3.1 Subqueries that Produce Scalar Values 6.3.2 Conditions Involving Relations 6.3.3 Conditions Involving Tuples 6.3.4 Correlated Subqueries 6.3.5 Subqueries in From Clauses 6.3.6 SQL Join Expressions 6.3.7 Natural Joins 6.3.8 Outer Joins 6.3.9 Exercises for Section 6.3 32

33. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1 Subqueries that Produce Scalar Values (1) Example 6.12 Two database Pointers) SELECT name FROM MovieExec WHERE cert# = (SELECT producerC# FROM Movies FROM Movies WHERE title = 'STAR''s WARS' and producerC# > 950); WHERE title = 'STAR''s WARS' and producerC# > 950); What would happen if the subquery retrieve zero or more than one tuple? 33

34. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1 Subqueries that Produce Scalar Values (2) Example 6.19 (another version of Example 6.12) SELECT name FROM MovieExec WHERE cert# in (SELECT producerC# FROM Movies FROM Movies WHERE title = 'STAR''s WARS' ); WHERE title = 'STAR''s WARS' ); Explain the movements of database pointers. (double loops) 34

35. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1 Subqueries that Produce Scalar Values (2b) Example 6.19b SELECT name FROM MovieExec WHERE cert# NOT in (SELECT producerC# FROM Movies FROM Movies WHERE title = 'STAR''s WARS' ); WHERE title = 'STAR''s WARS' ); Compare the logic with the logic of next page 35

36. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1 Subqueries that Produce Scalar Values (2c) Example 6.19c Which is correct, b or c? SELECT name FROM MovieExec WHERE cert# in (SELECT producerC# FROM Movies FROM Movies WHERE title <>(NOT =)'STAR''s WARS' ); WHERE title <>(NOT =)'STAR''s WARS' ); Compare the logic with that of last page 36

37. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1 Subqueries that Produce Scalar Values (3) Example 6.19d. SELECT name FROM MovieExec M1 WHERE Exists (SELECT producerC# FROM Movies M2 FROM Movies M2 WHERE title = 'STAR WARS' and M1.cert# = M2.producerC# ); WHERE title = 'STAR WARS' and M1.cert# = M2.producerC# ); Compare the logic with previous pages 37

38. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1 Subqueries that Produce Scalar Values (3 DB1) Example 6.12 Example 6.12 Get supplier names for suppliers who supply part P2. SELECTSNAME FROMSUPPLIERS WHERESNUM in (SELECT SNUM FROM SHIPMENTS WHERE PNUM='P2'); CONVERT into temp join 38

39. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1 Subqueries that Produce Scalar Values (3 DB1) Example 6.12 SELECTSNUM FROMSUPPLIERS WHERECITY = (SELECTCITY FROMSUPPLIERS WHERESNUM='S1'); 39

40. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1 Subqueries that Produce Scalar Values (3 DB1) Example 6.12 SELECTSNAME FROMSUPPLIER WHEREEXISTS (SELECT* FROMSHIPMENT WHERESNUM = Supplier.Snum ANDPNUM = 'P2'); 40

41. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1 Subqueries that Produce Scalar Values (3 DB1) Get supplier names for suppliers who do not supply part P2. SELECTSNAME FROMSUPPLIERS S WHEREEXISTS (SELECT* FROMSHIPMENTS WHERESNUM=S.Snum ANDPNUM='P2'); 41

42. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1 Subqueries that Produce Scalar Values (3b DB2) Example 6.19d. SELECT SELECT E.FNAME, E.LNAME FROM FROM EMPLOYEE E WHERE Exists (SELECT * (SELECT * FROM FROM WORKS_ON W WHERE WHERE W.WSSN = E.SSN AND W.PNO <> 1); 42

43. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1 Subqueries that Produce Scalar Values (4) Example 6.19e. (Temp join) SELECT name FROM MovieExec M, (SELECT producerC# FROM Movies FROM Movies WHERE title = 'STAR WARS‘) T WHERE title = 'STAR WARS‘) T WHERE M.cert# = T.producerC#; Compare the logic with previous pages 43

44. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1N Updates Change (increment) the quantity of every part supplied by supplier S2 by 100. UPDATESHIPMENTS SETQTY = QTY + 100 WHERESNUM = 'S2'; 44

45. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1N Updates Set the shipment quantity to zero for all suppliers in London. UPDATESHIPMENT SETQTY = 0 WHERE'London' = (SELECTCITY FROMSUPPLIER WHERESNUM= SP.SNUM); 45

46. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1N Delete DELETE General format : DELETE FROMtable [WHEREpredicate]; 46

47. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1N Delete Delete part P3. DELETE FROMFIRST1a WHEREPNUM = 'P2' and SNUM = 'S3'; 47

48. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1N Delete Delete all shipments for suppliers in London. DELETE FROMSHIPMENT WHERE'London'= (SELECTCITY FROMSUPPLIER WHERES.SNUM= SP.SNUM); 48

49. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1N 6.3.1N INSERT General format 1 : INSERT INTOtable [(field [,field]...)] VALUES (constant [,constant]...); 49

50. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.1N 6.3.1N INSERT general format 2 : INSERT INTOtable [(field[,field])] SELECTFROMWHERE 50

51. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 51 SELECTSUM(SALARY) FROMFIRST1a

52. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.3 Conditions Involving Tuples (Examples) If the type and the number of attributes in a tuple are the same as of a relation, we can compare them. If the type and the number of attributes in a tuple are the same as of a relation, we can compare them. Example: ('Tom', 'Smith') IN Example: ('Tom', 'Smith') IN (SELECT firstName, LastName FROM foo); (SELECT firstName, LastName FROM foo); Note that the order of the attributes must be the same in the tuple and the SELECT list. Note that the order of the attributes must be the same in the tuple and the SELECT list. 52

53. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.3 Conditions Involving Tuples (skip to examples) A tuple in SQL is represented by a parenthesized list of scalar values. A tuple in SQL is represented by a parenthesized list of scalar values. Examples: (123, ‘I am a string’, 0, NULL) (name, address, salary) Examples: (123, ‘I am a string’, 0, NULL) (name, address, salary) The first example shows all constants and the second shows attributes. The first example shows all constants and the second shows attributes. Mixing constants and attributes are allowed. Mixing constants and attributes are allowed. 53

54. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.3 Conditions Involving Tuples (One/two Columns Relation) Example 6.20: Main Example SELECT name FROM MovieExec WHERE cert# IN (SELECT producerC# FROM Movies (SELECT producerC# FROM Movies WHERE (title, year) IN WHERE (title, year) IN (SELECT movieTitle, movieYear (SELECT movieTitle, movieYear FROM StarsIN FROM StarsIN WHERE starName = 'SAMUEL HENRY') WHERE starName = 'SAMUEL HENRY') ); ); 54

55. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.3 Conditions Involving Tuples (One/two Column Relation) Example 6.20a: Partial checking SELECT producerC# FROM Movies SELECT producerC# FROM Movies WHERE (title, year) IN WHERE (title, year) IN (SELECT movieTitle, movieYear (SELECT movieTitle, movieYear FROM StarsIN FROM StarsIN WHERE starName = 'SAMUEL HENRY'); WHERE starName = 'SAMUEL HENRY'); 55

56. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.3 Conditions Involving Tuples (One/two Column Relation) Example 6.20b: Partial checking (SELECT title, year FROM Movies_e) (SELECT title, year FROM Movies_e) Intersect Intersect (SELECT movieTitle, movieYear (SELECT movieTitle, movieYear FROM StarsIN_e FROM StarsIN_e WHERE starName = 'SAMUEL HENRY'); WHERE starName = 'SAMUEL HENRY'); 56

57. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.3a Conditions Involving Tuples (temp join query) Example 6.20c: (temp join query) SELECT * FROM Movies M, (SELECT movieTitle, movieYear SELECT * FROM Movies M, (SELECT movieTitle, movieYear FROM StarsIN FROM StarsIN WHERE starName = 'SAMUEL HENRY') T WHERE starName = 'SAMUEL HENRY') T WHERE M.title=T.movieTitle and WHERE M.title=T.movieTitle and M.year =T.movieyear; M.year =T.movieyear; 57

58. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.3 Conditions Involving Tuples (using Join Queries) For example, the previous query can be written as join query: (not recommended) For example, the previous query can be written as join query: (not recommended) SELECT name FROM MovieExec, Movies, StarsIN WHERE title = movieTitle AND year = movieYear And starName = 'SAMUEL HENRY'; 58

59. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.3 Conditions Involving Tuples (One/two Column Relation) Example 6.20: Main Example Query all the producers of movies in which 'SAMUEL HENRY stars. SELECT name FROM MovieExec WHERE cert# IN (SELECT producerC# FROM Movies (SELECT producerC# FROM Movies WHERE (title, year) IN WHERE (title, year) IN (SELECT movieTitle, movieYear (SELECT movieTitle, movieYear FROM StarsIN FROM StarsIN WHERE starName = 'SAMUEL HENRY') WHERE starName = 'SAMUEL HENRY') ); ); 59

60. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.4 Correlated Subqueries The simplest subquery is evaluated once and the result is used in a higher-level query. The simplest subquery is evaluated once and the result is used in a higher-level query. Some times a subquery is required to be evaluated several times, once for each assignment of a value that comes from a tuple variable outside the subquery. Some times a subquery is required to be evaluated several times, once for each assignment of a value that comes from a tuple variable outside the subquery. A subquery of this type is called correlated subquery. A subquery of this type is called correlated subquery. 60

61. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.4 Correlated Subqueries (Monday) Example 6.21 Query the titles that have been used for two or more movies. SELECT title FROM Movies old WHERE year <= ANY (SELECT year FROM Movies (SELECT year FROM Movies WHERE title = old.title); WHERE title = old.title); 61

62. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.5 Subqueries in From Clauses In a FROM list, we my use a parenthesized subquery. In a FROM list, we my use a parenthesized subquery. The subquery must have a tuple variable or alias. The subquery must have a tuple variable or alias. 62

63. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.5 Subqueries in From Clauses (cont'd) Example 6.22 Query the producers of Harrison Ford's movies. Select name FROM MovieExec, (SELECT producerC# FROM Movies, StarsIN (SELECT producerC# FROM Movies, StarsIN WHERE title = movieTitle WHERE title = movieTitle AND year = movieYear AND year = movieYear AND starName ='SAMUEL HENRY' AND starName ='SAMUEL HENRY' ) Prod ) Prod WHERE cert# = Prod.producerC#; 63

64. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.5 Subqueries in From Clauses (cont'd) Example 6.22 Query the producers of Harrison Ford's movies. Select name FROM MovieExec, (SELECT producerC# FROM Movies, StarsIN (SELECT producerC# FROM Movies, StarsIN WHERE title = movieTitle WHERE title = movieTitle AND year = movieYear AND year = movieYear AND starName ='SAMUEL HENRY' AND starName ='SAMUEL HENRY' ) Prod ) Prod WHERE cert# = Prod.producerC#; 64

65. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.6 SQL Join Expressions(SKIP) Join operators construct new temp relations from existing relations. Join operators construct new temp relations from existing relations. These relations can be used in any part of the query that you can put a subquery. These relations can be used in any part of the query that you can put a subquery. Cross join is the simplest form of a join. Cross join is the simplest form of a join. Actually, this is synonym for Cartesian product. Actually, this is synonym for Cartesian product. For example: From Movies CROSS JOIN StarsIn is equal to: From Movies, StarsIn For example: From Movies CROSS JOIN StarsIn is equal to: From Movies, StarsIn 65

66. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 66 SELECT E.SSN, E.LNAME, E.BDATE FROM EMPLOYEE E WHERE E.ADDRESS LIKE '%BELLAIRE%';

67. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.6 SQL Join Expressions ((SKIP)) If the relations we used are: Movies(title, year, length, genre, studioName, producerC#) StarsIn(movieTitle, movieYear, starName) Then the result of the CROSS JOIN would be a relation with the following attributes: R(title, year, length, genre, studioName, producerC#, movieTitle, movieYear, starName) If the relations we used are: Movies(title, year, length, genre, studioName, producerC#) StarsIn(movieTitle, movieYear, starName) Then the result of the CROSS JOIN would be a relation with the following attributes: R(title, year, length, genre, studioName, producerC#, movieTitle, movieYear, starName) Note that if there is a common name in the two relations, then the attributes names would be qualified with the relation name. Note that if there is a common name in the two relations, then the attributes names would be qualified with the relation name. 67

68. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.6 SQL Join Expressions ((SKIP)) Cross join by itself is rarely a useful operation. Cross join by itself is rarely a useful operation. Usually, a theta-join is used as follows: FROM R JOIN S ON condition Usually, a theta-join is used as follows: FROM R JOIN S ON condition For example: Movies JOIN StarsIn ON title = movieTitle AND year = movieYear For example: Movies JOIN StarsIn ON title = movieTitle AND year = movieYear The result would be the same number of attributes but the tuples would be those that agree on both the title and year. The result would be the same number of attributes but the tuples would be those that agree on both the title and year. 68

69. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.6 SQL Join Expressions ((SKIP)) Note that in the previous example, the title and year are repeated twice. Once as title and year and once as movieTitle and movieYear. Note that in the previous example, the title and year are repeated twice. Once as title and year and once as movieTitle and movieYear. Considering the point that the resulting tuples have the same value for title and movieTitle, and year and movieYear, then we encounter the redundancy of information. Considering the point that the resulting tuples have the same value for title and movieTitle, and year and movieYear, then we encounter the redundancy of information. One way to remove the unnecessary attributes is projection. You can mention the attributes names in the SELECT list. One way to remove the unnecessary attributes is projection. You can mention the attributes names in the SELECT list. 69

70. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.7 Natural Joins((SKIP)) Natural join and theta-join differs in: Natural join and theta-join differs in: 1. The join condition All pairs of attributes from the two relations having a common name are equated, and also there are no other conditions. 2. The attributes list One of each pair of equated attributes is projected out. Example MovieStar NATURAL JOIN MovieExec Example MovieStar NATURAL JOIN MovieExec 70

71. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.7 Natural Joins ((SKIP)) Example 6.24 Query those stars who are executive as well. The relations are: MovieStar(name, address, gender, birthdate) MovieExec(name, address, cert#, netWorth) SELECT MovieStar.name FROM MovieStar NATURAL JOIN MovieExec 71

72. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.8 Outer Joins(SKIP) Outer join is a way to augment the result of a join by dangling tuples, padded with null values. Outer join is a way to augment the result of a join by dangling tuples, padded with null values. 72

73. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.8 Outer Joins ((SKIP)) Example 6.25 Consider the following relations: MovieStar(name, address, gender, birthdate) MovieExec(name, address, cert#, netWorth) Then MovieStar NATURAL FULL OUTER JOIN MovieExec Will produce a relation whose tuples are of 3 kinds: 1. Those who are both movie stars and executive 2. Those who are movie star but not executive 3. Those who are executive but not movie star 73

74. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.8 Outer Joins ((SKIP)) We can replace keyword FULL with LEFT or RIGHT to get two new join. We can replace keyword FULL with LEFT or RIGHT to get two new join. NATURAL LEFT OUTER JOIN would yield the first two tuples but not the third. NATURAL LEFT OUTER JOIN would yield the first two tuples but not the third. NATURAL RIGHT OUTER JOIN would yield the first and third tuples but not the second. NATURAL RIGHT OUTER JOIN would yield the first and third tuples but not the second. 74

75. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.8 Outer Joins ((SKIP)) We can have theta-outer-join as follows: We can have theta-outer-join as follows: R FULL OUTER JOIN S ON condition R FULL OUTER JOIN S ON condition R LEFT OUTER JOIN S ON condition R LEFT OUTER JOIN S ON condition R RIGHT OUTER JOIN S ON condition R RIGHT OUTER JOIN S ON condition 75

76. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.3.9 Exercises for Section 6.3 76

77. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 FULL-RELATION OPERATIONS Section 6.4 77

78. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4 Full-Relation Operations 6.4.1 Eliminating Duplicates 6.4.2 Duplicates in Unions, Intersections, and Differences 6.4.3 Grouping and Aggregation in SQL 6.4.4 Aggregation Operators 6.4.5 Grouping 6.4.6 Grouping, Aggregation, and Nulls 6.4.7 Having Clauses 6.4.8 Exercises for Section 6.4 78

79. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.1 Eliminating Duplicates SQL does not eliminate duplicate tuples by itself. So, it does not treat the relations as a set. It treats the relations as a bag. SQL does not eliminate duplicate tuples by itself. So, it does not treat the relations as a set. It treats the relations as a bag. To eliminate duplicate tuples, use DISTINCT keyword after SELECT as the next example shows. To eliminate duplicate tuples, use DISTINCT keyword after SELECT as the next example shows. Note that duplicate tuples elimination is a very expensive operation for database, so, use DISTINCT keyword wisely. Note that duplicate tuples elimination is a very expensive operation for database, so, use DISTINCT keyword wisely. 79

80. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.1 Eliminating Duplicates Example 6.27(new ex) Query all the producers of movies in which 'SAMUEL HENRY' stars. SELECT DISTINCT name FROM MovieExec, Movies, StarsIN WHERE cert# = producerC# AND title = movieTitle AND year = movieYear And starName = 'SAMUEL HENRY'; 80

81. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.2 Duplicates in Unions, Intersections, and Differences Duplicate tuples are eliminated in UNION, INTERSECT, and EXCEPT. Duplicate tuples are eliminated in UNION, INTERSECT, and EXCEPT. In other words, bags are converted to sets. In other words, bags are converted to sets. If you don't want this conversion, use keyword ALL after the operators. If you don't want this conversion, use keyword ALL after the operators. Example 6.28 Example 6.28 ( SELECT title, year FROM Movies) UNION ALL (SELECT movieTitle AS title, movieYear AS year FROM StarsIn); 81

82. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.3 Grouping and Aggregation in SQL We can partition the tuples of a relation into "groups" based on the values of one or more attributes. The relation can be an output of a SELECT statement. We can partition the tuples of a relation into "groups" based on the values of one or more attributes. The relation can be an output of a SELECT statement. Then, we can aggregate the other attributes using aggregation operators. Then, we can aggregate the other attributes using aggregation operators. For example, we can sum up the salary of the employees of each department by grouping the company into departments. For example, we can sum up the salary of the employees of each department by grouping the company into departments. 82

83. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.4 Aggregation Operators SQL uses the five aggregation operators: SUM, AVG, MIN, MAX, and COUNT SQL uses the five aggregation operators: SUM, AVG, MIN, MAX, and COUNT These operators can be applied to scalar expressions, typically, a column name. These operators can be applied to scalar expressions, typically, a column name. One exception is COUNT(*) which counts all the tuples of a query output. One exception is COUNT(*) which counts all the tuples of a query output. We can eliminate the duplicate values before applying aggregation operators by using DISTINCT keyword. For example: COUNT(DISTINCT x) We can eliminate the duplicate values before applying aggregation operators by using DISTINCT keyword. For example: COUNT(DISTINCT x) 83

84. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.4 Aggregation Operators (cont'd) Example 6.29 Find the average net worth of all movie executives. SELECT AVG(netWorth) FROM MovieExec; 84

85. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.4 Aggregation Operators (cont'd) Example 6.30 Count the number of tuples in the StarsIn relation. SELECT COUNT(*) FROM StarsIn; SELECT COUNT(starName) FROM StarsIn; These two statements do the same but you will see the difference in later slides. 85

86. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.5 Grouping We can group the tuples by using GROUP BY clause following the WHERE clause. We can group the tuples by using GROUP BY clause following the WHERE clause. The keywords GROUP BY are followed by a list of grouping attributes. The keywords GROUP BY are followed by a list of grouping attributes. 86

87. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.5 Grouping (cont'd) Example 6.31 Find sum of the movies length each studio is produced. SELECT studioName, SUM(length) AS Total_Length SUM(length) AS Total_Length FROM Movies GROUP BY studioName; 87

88. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.5 Grouping (cont'd) In a SELECT clause that has aggregation, only those attributes that are mentioned in the GROUP BY clause may appear unaggregated. In a SELECT clause that has aggregation, only those attributes that are mentioned in the GROUP BY clause may appear unaggregated. For example, in previous example, if you want to add genre in the SELECT list, then, you must mention it in the GROUP BY list as well. For example, in previous example, if you want to add genre in the SELECT list, then, you must mention it in the GROUP BY list as well. SELECT studioName, incolor, SUM(length) AS Total_Length SUM(length) AS Total_Length FROM Movies GROUP BY studioName, incolor; 88

89. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.5 Grouping (cont'd) It is possible to use GROUP BY in a more complex queries about several relations. It is possible to use GROUP BY in a more complex queries about several relations. In these cases the following steps are applied: In these cases the following steps are applied: 1. Produce the output relation based on the select-from-where parts. 2. Group the tuples according to the list of attributes mentioned in the GROUP BY list. 3. Apply the aggregation operators 89

90. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.5 Grouping (cont'd) Example 6.32 Create a list of each producer name and the total length of film produced. SELECT name, SUM(length) FROM MovieExec, Movies WHERE producerC# = cert# GROUP BY name; 90

91. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.6 Grouping, Aggregation, and Nulls What would happen to aggregation operators if the attributes have null values? What would happen to aggregation operators if the attributes have null values? There are a few rules to remember There are a few rules to remember 91

92. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.6 Grouping, Aggregation, and Nulls (cont'd) 1. NULL values are ignored when the aggregation operator is applied on an attribute. 2. COUNT(*) counts all tuples of a relation, therefore, it counts the tuples even if the tuple contains NULL value. 3. NULL is treated as an ordinary value when forming groups. 4. When we perform an aggregation, except COUNT, over an empty bag, the result is NULL. The COUNT of an empty bag is 0 92

93. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.6 Grouping, Aggregation, and Nulls (cont'd) Example 6.33 Consider a relation R(A, B) with one tuple, both of whose components are NULL. What's the result of the following SELECT? SELECT A, COUNT(B) FROM R GROUP BY A; The result is (NULL, 0) but why? 93

94. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.6 Grouping, Aggregation, and Nulls (cont'd) What's the result of the following SELECT? SELECT A, COUNT(*) FROM R GROUP BY A; The result is (NULL, 1) because COUNT(*) counts the number of tuples and this relation has one tuple. 94

95. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.6 Grouping, Aggregation, and Nulls (cont'd) What's the result of the following SELECT? SELECT A, SUM(B) FROM R GROUP BY A; The result is (NULL, NULL) because SUM(B) addes one NULL value which is NULL. 95

96. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.7 HAVING Clauses So far, we have learned how to restrict tuples from contributing in the output of a query. So far, we have learned how to restrict tuples from contributing in the output of a query. How about if we don't want to list all groups? How about if we don't want to list all groups? HAVING clause is used to restrict groups. HAVING clause is used to restrict groups. HAVING clause followed by one or more conditions about the group. HAVING clause followed by one or more conditions about the group. 96

97. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.7 HAVING Clauses (cont'd) Example 6.34 Query the total film length for only those producers who made at least one film prior to 2000. SELECT name, year, SUM(length) FROM MovieExec, Movies WHERE producerC# = cert# GROUP BY name, year HAVING MIN(year) < 2000; 97

98. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.7 HAVING Clauses (cont'd) The rules we should remember about HAVING: The rules we should remember about HAVING: 1. An aggregation in a HAVING clause applies only to the tuples of the group being tested. 2. Any attribute of relations in the FROM clause may be aggregated in the HAVING clause, but only those attributes that are in the GROUP BY list may appear unaggregated in the HAVING clause (the same rule as for the SELECT clause). 98

99. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.7 HAVING Clauses (cont'd) The order of clauses in SQL queries would be: The order of clauses in SQL queries would be: SELECT SELECT FROM FROM WHERE WHERE GROUP BY GROUP BY HAVING HAVING Only SELECT and FROM are mandatory. Only SELECT and FROM are mandatory. 99

100. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.4.8 Exercises for Section 6.4 100

101. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 DATABASE MODIFICATIONS Section 6.5 101

102. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.5 Database Modifications 6.5.1 Insertion 6.5.2 Deletion 6.5.3 Updates 6.5.4 Exercises for Section 6.5 102

103. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.5.1 Insertion The syntax of INSERT statement: INSERT INTO R(A 1,..., A N ) VALUES (v 1,..., v n ); The syntax of INSERT statement: INSERT INTO R(A 1,..., A N ) VALUES (v 1,..., v n ); If the list of attributes doesn't include all attributes, then it put default values for the missing attributes. If the list of attributes doesn't include all attributes, then it put default values for the missing attributes. 103

104. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.5.1 Insertion (cont'd) Example 6.35 INSERT INTO StarsIn(MovieTitle, movieYear, starName) VALUES ('The Maltese Falcon', 1942, 'Sydney Greenstreet'); If we are sure about the order of the attributes, then we can write the statement as follows: INSERT INTO StarsIn VALUES ('The Maltese Falcon', 1942, 'Sydney Greenstreet'); 104

105. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.5.1 Insertion (cont'd) The simple insert can insert only one tuple, however, if you want to insert multiple tuples, then you can use the following syntax: The simple insert can insert only one tuple, however, if you want to insert multiple tuples, then you can use the following syntax: INSERT INTO R(A 1,..., A N ) SELECT v 1,..., v n FROM R 1, R 2,..., R N WHERE ; 105

106. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.5.1 Insertion (cont'd) Example 6.36 Suppose that we want to insert all studio names that are mentioned in the Movies relation but they are not in the Studio yet. INSERT INTO Studio(name) SELECT DISTINCT studioName FROM Movies WHERE studionName NOT IN (SELECT name FROM Studio); FROM Studio); 106

107. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.5.2 Deletion The syntax of DELETE statement: DELETE FROM R WHERE ; The syntax of DELETE statement: DELETE FROM R WHERE ; Every tuples satisfying the condition will be deleted from the relation R. Every tuples satisfying the condition will be deleted from the relation R. 107

108. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.5.2 Deletion (cont'd) Example 6.37 DELETE FROM StarsIn WHERE movieTitle = 'The Maltese Falcon' AND movieYear = 1942 AND movieYear = 1942 AND starName = 'Sydney Greenstreet'; starName = 'Sydney Greenstreet'; 108

109. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.5.2 Deletion (cont'd) Example 6.38 Delete all movie executives whose net worth is less than ten million dollars. DELETE FROM MovieExec WHERE netWorth < 10000000; 109

110. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.5.3 Updates The syntax of UPDATE statement: UPDATE R SET WHERE ; The syntax of UPDATE statement: UPDATE R SET WHERE ; Every tuples satisfying the condition will be updated from the relation R. Every tuples satisfying the condition will be updated from the relation R. If there are more than one value-assignment, we should separate them with comma. If there are more than one value-assignment, we should separate them with comma. 110

111. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.5.3 Updates Example 6.39 Attach the title 'Pres.' in front of the name of every movie executive who is the president of a studio. UPDATE MovieExec_e SET name = 'Pres.'||name WHERE cert# IN (SELECT PRODUCERC# FROM Movies); 111

112. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.5.4 Exercises for Section 6.5 112

113. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 TRANSACTIONS IN SQL Section 6.6 113

114. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6 Transactions in SQL 6.6.1 Serializability 6.6.2 Atomicity 6.6.3 Transactions 6.6.4 Read-Only Transactions 6.6.5 Dirty Reads 6.6.6 Other Isolation Levels 6.6.7 Exercises for Section 6.6 114

115. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6 Transactions in SQL Up to this point, we assumed that: Up to this point, we assumed that: the SQL operations are done by one user. the SQL operations are done by one user. The operations are done one at a time. The operations are done one at a time. There is no hardware/software failure in middle of a database modification. Therefore, the operations are done atomically. There is no hardware/software failure in middle of a database modification. Therefore, the operations are done atomically. In Real life, situations are totally different. In Real life, situations are totally different. There are millions of users using the same database and it is possible to have some concurrent operations on one tuple. There are millions of users using the same database and it is possible to have some concurrent operations on one tuple. 115

116. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.1 Serializability In applications like web services, banking, or airline reservations, hundreds to thousands operations per second are done on one database. In applications like web services, banking, or airline reservations, hundreds to thousands operations per second are done on one database. It's quite possible to have two or more operations affecting the same, let's say, one bank account. It's quite possible to have two or more operations affecting the same, let's say, one bank account. If these operations overlap in time, then they may act in a strange way. If these operations overlap in time, then they may act in a strange way. Let's take an example. Let's take an example. 116

117. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.1 Serializability (cont'd) Example 6.40 Consider an airline reservation web application. Users can book their desired seat by themselves. The application is using the following schema: Flights(fltNo, fltDae, seatNo, seatStatus) When a user requests the available seats for the flight no 123 on date 2011-12-15, the following query is issued: 117

118. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.1 Serializability (cont'd) SELECT seatNo FROM Flights WHERE fltNo = 123 AND fltDate = DATE '2011-12-25' AND fltDate = DATE '2011-12-25' AND seatStatus = 'available'; seatStatus = 'available'; When the customer clicks on the seat# 22A, the seat status is changed by the following SQL: UPDATE Flights SET seatStatus = 'occupied' WHERE fltNo = 123 AND fltDate = DATE '2011-12-25' AND fltDate = DATE '2011-12-25' AND seatNo = '22A'; seatNo = '22A'; 118

119. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.1 Serializability (cont'd) What would happen if two users at the same time click on the reserve button for the same seat#? What would happen if two users at the same time click on the reserve button for the same seat#? Both see the same seats available and both reserve the same seat. Both see the same seats available and both reserve the same seat. To prevent these happen, SQL has some solutions. To prevent these happen, SQL has some solutions. We group a set of operations that need to be performed together. This is called 'transaction'. We group a set of operations that need to be performed together. This is called 'transaction'. 119

120. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.1 Serializability (cont'd) For example, the query and the update in example 6.40 can be grouped in a transaction. For example, the query and the update in example 6.40 can be grouped in a transaction. SQL allows the programmer to stat that a certain transaction must be serializable with respect to other transactions. SQL allows the programmer to stat that a certain transaction must be serializable with respect to other transactions. That is, these transactions must behave as if they were run serially, one at a time with no overlap. That is, these transactions must behave as if they were run serially, one at a time with no overlap. 120

121. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.2 Atomicity What would happen if a transaction consisting of two operations is in progress and after the first operation is done, the database and/or network crashes? What would happen if a transaction consisting of two operations is in progress and after the first operation is done, the database and/or network crashes? Let's take an example. Let's take an example. 121

122. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.2 Atomicity (cont'd) Example 6.41 Consider a bank's account records system with the following relation: Accounts(acctNo, balance) Let's suppose that $100 is going to transfer from acctNo 123 to acctNo 456. To do this, the following two steps should be done: 1. Add $100 to account# 456 2. Subtract $100 from account# 123. 122

123. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.2 Atomicity (cont'd) The needed SQL statements are as follows: UPDATE Accounts SET balance = balance + 100 WHERE acctNo = 456; UPDATE Accounts SET balance = balance - 100 WHERE acctNo = 123; What would happen if right after the first operation, the database crashes? 123

124. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.2 Atomicity (cont'd) The problem addressed by example 6.41 is that certain combinations of operations need to be done atomically. The problem addressed by example 6.41 is that certain combinations of operations need to be done atomically. That is, either they are both done or neither is done. That is, either they are both done or neither is done. 124

125. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.3 Transactions The solution to the problems of serialization and atomicity is to group database operations into transactions. The solution to the problems of serialization and atomicity is to group database operations into transactions. A transaction is a set of one or more operations on the database that must be executed atomically and in a serializable manner. A transaction is a set of one or more operations on the database that must be executed atomically and in a serializable manner. To create a transation, we use the following SQL command: To create a transation, we use the following SQL command: START TRANSACTION 125

126. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.3 Transactions (cont'd) There are two ways to end a transaction: There are two ways to end a transaction: 1. The SQL receives COMMIT command. 2. The SQL receives ROLLBACK command. COMMIT command causes all changes become permanent in the database. COMMIT command causes all changes become permanent in the database. ROLLBACK command causes all changes undone. ROLLBACK command causes all changes undone. 126

127. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.4 Read-Only Transactions We saw that when a transaction read a data and then want to write something, is prone to serialization problems. We saw that when a transaction read a data and then want to write something, is prone to serialization problems. When a transaction only reads data and does not write data, we have more freedom to let the transaction execute in parallel with other transactions. When a transaction only reads data and does not write data, we have more freedom to let the transaction execute in parallel with other transactions. We call these transactions read-only. We call these transactions read-only. 127

128. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.4 Read-Only Transactions (cont'd) Example 6.43 Suppose we want to read data from the Flights relation of example 6.40 to determine whether a certain seat was available? What's the worst thing that can happen? When we query the availability of a certain seat, that seat was being booked or was being released by the execution of some other program. Then we get the wrong answer. 128

129. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.4 Read-Only Transactions (cont'd) If we tell the SQL that our current transaction is read-only, then SQL allows our transaction be executed with other read-only transactions in parallel. If we tell the SQL that our current transaction is read-only, then SQL allows our transaction be executed with other read-only transactions in parallel. The syntax of SQL command for read-only setting: The syntax of SQL command for read-only setting: SET TRANSACTION READ ONLY; We put this statement before our read-only transaction. We put this statement before our read-only transaction. 129

130. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.4 Read-Only Transactions (cont'd) The syntax of SQL command for read-write setting: The syntax of SQL command for read-write setting: SET TRANSACTION READ WRITE; We put this statement before our read-write transaction. We put this statement before our read-write transaction. This option is the default. This option is the default. 130

131. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.5 Dirty Reads The data that is written but not committed yet is called dirty data. The data that is written but not committed yet is called dirty data. A dirty read is a read of dirty data written by another transaction. A dirty read is a read of dirty data written by another transaction. The risk in reading dirty data is that the transaction that wrote it never commit it. The risk in reading dirty data is that the transaction that wrote it never commit it. 131

132. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.5 Dirty Reads (cont'd) Example 6.44 Consider the account transfer of example 6.41. Here are the steps: 1. Add money to account 2. 2. Test if account 1 has enough money? a. If there is not enough money, remove the money from account 2 and end. b. If there is, subtract the money from account 1 and end. Imagine, there are 3 accounts A1, A2, and A3 with $100, $200, and $300. 132

133. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.5 Dirty Reads (cont'd) Example 6.44 (cont'd) Let's suppose: Transaction T1 transfers $150 from A1 to A2 Transaction T2 transfers $250 from A2 to A3 What would happen if the dirty read is allowed? 133

134. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.5 Dirty Reads (cont'd) The syntax of SQL command for dirty-read setting: The syntax of SQL command for dirty-read setting: SET TRANSACTION READ WRITE ISOLATION LEVEL READ UNCOMMITTED; We put this statement before our read-write transaction. We put this statement before our read-write transaction. This option is the default. This option is the default. 134

135. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.6 Other Isolation Levels There are four isolation level. There are four isolation level. We have seen the first two before. We have seen the first two before. Serializable (default) Serializable (default) Read-uncommitted Read-uncommitted Read-committed Syntax: SET TRANSACTION ISOLATION LEVEL READ COMMITTED; Read-committed Syntax: SET TRANSACTION ISOLATION LEVEL READ COMMITTED; Repeatable-read Syntax SET TRANSACTION ISOLATION LEVEL READ COMMITTED; Repeatable-read Syntax SET TRANSACTION ISOLATION LEVEL READ COMMITTED; 135

136. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.6 Other Isolation Levels (cont'd) For each the default is 'READ WRITE' (except the isolation READ UNCOMMITTED that the default is 'READ ONLY') and if you want 'READ ONLY', you should mention it explicitly. For each the default is 'READ WRITE' (except the isolation READ UNCOMMITTED that the default is 'READ ONLY') and if you want 'READ ONLY', you should mention it explicitly. The default isolation level is 'SERIALIZABLE'. The default isolation level is 'SERIALIZABLE'. Note that if a transaction T is acting in 'SERIALIZABLE' level and the other one is acting in 'READ UNCOMMITTED' level, then this transaction can see the dirty data of T. It means that each one acts based on their level. Note that if a transaction T is acting in 'SERIALIZABLE' level and the other one is acting in 'READ UNCOMMITTED' level, then this transaction can see the dirty data of T. It means that each one acts based on their level. 136

137. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.6 Other Isolation Levels (cont'd) Under READ COMMITTED isolation, it forbids reading the dirty data. Under READ COMMITTED isolation, it forbids reading the dirty data. But it does not guarantee that if we issue several queries, we get the same tuples. But it does not guarantee that if we issue several queries, we get the same tuples. That's because there may be some new committed tuples by other transactions. That's because there may be some new committed tuples by other transactions. 137

138. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.6 Other Isolation Levels (cont'd) Example 6.46 Let's consider the seat choosing problem under 'READ COMMITTED' isolation. Your query won't see seat as available if another transaction reserved it but not committed yet. You may see different set of seats in subsequent queries depends on if the other transactions commit their reservations or rollback them. 138

139. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.6 Other Isolation Levels (cont'd) Under REPEATABLE READ isolation, if a tuple is retrieved for the first time, then we are sure that the same tuple will be retrieve if the query is repeated. Under REPEATABLE READ isolation, if a tuple is retrieved for the first time, then we are sure that the same tuple will be retrieve if the query is repeated. But the query may show more tuples because of the phantom tuples. But the query may show more tuples because of the phantom tuples. A phantom tuple is a tuple that is inserted by other transactions. A phantom tuple is a tuple that is inserted by other transactions. 139

140. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.6 Other Isolation Levels (cont'd) Example 6.47 Let's continue the seat choosing problem under 'REPEATABLE READ' isolation. If a seat is available on the first query, then it will remain available at the subsequent queries. Now suppose that some new tuples are inserted into the flight relation (phantom tuples) for that particular flight for any reason. Then the subsequent queries retrieve the new tuples as well. 140

141. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.6 Other Isolation Levels (cont'd) Properties of SQL isolation levels Properties of SQL isolation levels 141 Isolation Level Dirty Read Non- repeatable Read Phantom Read Uncommitted Read Committed - Repeatable Read -- Serializable---

142. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.6.7 Exercises for Section 6.6 142

143. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.7 Summary of Chapter 6 143

144. Dr. T. Y. Lin | SJSU | CS 157A | Fall 2011 6.8 References for Chapter 6 144