MIS710 Module 2a Complex SQL Queries

1. MIS710 Module 2aComplex SQL Queries Arijit Sengupta

2. Monotonic and Non-Monotonic Queries • Monotonic queries: queries for which the size of the results either increase or stay the same as the size of the inputs increase. The result size never decreases • Non-monotonic queries: queries for which it is possible that the size of the result will DECREASE when the size of the input increases • Examples of each?

3. Examples of monotonic queries

4. Examples of non-monotonic queries

5. Which of the operations is non-monotonic? • Selection • Projection • Cross Product • Union • Set Difference What does this signify?

6. Identify – monotonic/non-monotonic? • Find students who have taken algebra but not calculus • Monotonic • Non-monotonic • Find students who have taken calculus but are not math majors • Monotonic • Non-monotonic

7. Answers to prev. slide • Find students who have taken algebra but not calculus • Non-monotonic – you take a student who has taken algebra but not calculus, add a new registration for calculus, and he is gone from the result • Find students who have taken calculus but are not math majors • Monotonic! Assume Joe has taken calculus and is not a math major – can you remove him from the result by adding more rows? • Moral: If something is monotonic, you can solve it with basic SELECT-FROM-WHERE • If something is non-monotonic – you HAVE to use something else • Options are: MINUS, NOT IN, NOT EXISTS, Special grouping

8. Identify – monotonic/non-monotonic • Find the students who have taken some CS courses • Find the students who have only taken CS courses • Find the students who have taken all the CS courses • Find the students who have not taken any CS course • Find the students who have taken a non-CS course

9. Answers to previous slide • Monotonic – if someone has taken some CS course, he stays in the results regardless of what you add/remove • Non-monotonic – someone who has only taken CS course will disappear from the result if you add a registration for them for a non-cs course • Non-monotonic – if you add a new CS course, then … • Non-monotonic – if you add a registration for a CS course… • Monotonic! Someone who has taken a non-CS course will continue to stay in the result!

10. Thumb rules • Some clues to identify non-monotonic queries • Every, All • No, None, Never • Only • Remember – these are just thumb rules and not absolute laws – you need to think about how the queries will behave to determine non-monotonicity

11. Lets do the monotonic first! • Find students who have taken some CS course SELECT s.* FROM Student s, Reg r, Course c WHERE s.sid = r.sid AND c.cno = r.cno AND c.dept = 'CS'

12. The other monotonic query • Find Students who have taken a Non-CS Course SELECT s.* FROM Student s, Reg r, Course c WHERE s.sid = r.sid AND c.cno = r.cno AND c.dept != 'CS'

13. Solving non-monotonic queries • We know that MINUS can solve non-monotonic • Unfortunately representing all queries using MINUS is not easy • Some are easy: • Students who have not taken any CS course • All students MINUS students who have taken some CS course

14. Non-monotonic queries using MINUS • All students MINUS students who have taken some CS course SELECT s1.* FROM Student s1 MINUS SELECT s.* FROM Student s, Reg r, Course c WHERE s.sid = r.sid AND c.cno = r.cno AND c.dept = 'CS'

15. Nesting Queries - Syntax SELECT attribute(s) FROM relation(S) WHERE attr [not] {in | comparison operator | exists } ( query statement(s) ); List names of students who are taking “MIS415” select Name from Student where SID in ( select SID from REG where Cno = ‘MIS415’);

16. Sub Queries List all students enrolled in MIS courses select name from STUDENT where SId in (select SId from REG where cno like ‘MIS%’); List all courses taken by Student (Id 1011) select cname from COURSE where cnum = any (select cno from REG where SId = 1011); So, IN and ANY essentially are like joins, not that interesting

17. Sub Queries - continued Who received the highest score in MIS 415 select SId from REG where cno = ‘MIS415’ and score >=all (select score from REG where cno = ‘MIS415’); ALL is quite powerful Since it works on the whole Set returned by the subquery List all students enrolled in MIS courses. select name from STUDENT S where exists (select * from REG where SId = S.SId and cno like ‘MIS%’); Exists is again like A join!

18. Non-monotonic queries using NOT IN and NOT Exists • Students who have not taken CS courses Using NOT IN SELECT s.* FROM Student s WHERE s.sid not IN ( SELECT r.sid FROM Reg r, Course c WHERE r.cno = c.cno AND c.dept = ‘CS’) Using NOT EXISTS SELECT s.* FROM Student s WHERE NOT EXISTS ( SELECT * FROM Reg r, Course c WHERE r.cno = c.cno AND c.dept = ‘CS’ AND r.sid = s.sid) Notice how the alias ‘s’ from outside the subquery is used in the subquery! These are called “correlated” subqueries.

19. The “default” results • Notice that sometimes queries using not exists will give you results that appear “by default” • For example, students who have not taken ANY course will show up in the result of the last query • Okay for this query?

20. Writing non-monotonic queries • See if you can rewrite the statement below in English with double negatives. • Remember – the new sentence MUST mean the same! • Find students who have taken ALL CS courses

21. Try another one • Find students who have got A’s in All courses they took

22. Tackling non-monotonic queries • Try 1: See if you can write it as a difference between two sets • Solve using MINUS or NOT IN • Try 2: Rewrite the query to use the tables and finding ways to use not exists • Find students who have taken all CS courses • Find students such that there is no CS course that they have not taken • Find students such that there doesn’t exist any CS course for which there doesn’t exist a registration for that student in that course! • Yes, a lot of double negatives!

23. Step by Step • Find students who have taken all CS courses Find students such that there doesn’t exist any CS course for which there doesn’t exist a registration for that student in that course! SELECT s.* FROM Student s WHERE not exists ( SELECT c.* FROM Course c WHERE c.dept = ‘CS’ AND NOT EXISTS ( SELECT r.* FROM Reg r WHERE r.sid = s.sid AND r.cno = c.cno))

24. Should we do one more? • Find students who have ONLY taken CS courses • Find students such that every course they have taken is a CS course • Find students such that every registration they have corresponds to a CS course • Find students such that there doesn’t exist any registration record for that student corresponding to a non-CS course

25. Translating this query SELECT s.* FROM Student s WHERE not Exists ( SELECT r.* FROM Reg r, Course c WHERE r.sid = s.sid AND r.cno = c.cno AND c.cno != ‘CS’) Find students such that there doesn’t exist any registration record for that student corresponding to a non-CS course

26. Default result here • You will notice that students who have not taken any courses will show up in this query’s results! • Why? • Logically, students who haven’t taken any courses haven’t taken any non-cs courses  • To get rid of this default behavior, you may want to perform a join on the outermost query, so that you retrieve students who have taken some course

27. Query with the default removed SELECT s.* FROM Student s, Reg R1 WHERE s.sid = R1.sid AND not Exists ( SELECT r.* FROM Reg r, Course c WHERE r.sid = s.sid AND r.cno = c.cno AND c.cno != ‘CS’) Now this query will only retrieve students who have taken at least one course, none of which is CS.

28. View 1 View 2 View N Base Relation 1 Base Relation 2 Relational Views • Relations derived from other relations. • Views have no stored tuples. • Are useful to provide multiple user views. • What level in the three layer model do views belong? • Which kind of independence do they support?

29. View Creation Create View view-name [ ( attr [ , attr ] ...) ] AS subquery [ with check option ] ; DROP VIEW view-name; • Create a view containing the student ID, Name, Age and GPA for those who are qualified to take 300 level courses, i.e., GPA >=2.0.

30. View Options • With Check Option enforces the query condition for insertion or update To enforce the GPA >=2.0 condition on all new student tuples inserted into the view • A view may be derived from multiple base relations Create a view that includes student IDs, student names and their instructors’ names for all CIS 300 students.

31. View Retrieval Queries on views are the same as that on base relations. Queries on views are expanded into queries on their base relations. select Name, Instructor-Name from CIS300-Student where Name = Instructor-Name;

32. View: Update Update on a view actually changes its base relation(s)! update Qualified-Student set GPA = GPA-0.1 where StudentID = ‘s3’; insert into Qualified-Student values ( ‘s9’, ‘Lisa’, 4.0 ) insert into Qualified-Student values ( ‘s10’, ‘Peter’, 1.7 ) Why are some views not updateable? What type of views are updateable?

33. Summary • SQL is a low-complexity, declarative query language • The good thing about being declarative is that internally the query can be changed automatically for optimization • Good thing about being low-complexity? • No SQL query ever goes into an infinite loop • No SQL query will ever take indefinite amount of space to get the solution • Can be used for highly complex problems!