1. 1 Relational Calculus ♦ Comes in two flavors: Tuple relational calculus (TRC) and Domain relational calculus (DRC). ♦ Calculus has variables, constants, comparison ops, logical connectives and quantifiers. ■TRC: Variables range over (i.e., get bound to) tuples. DRC: Variables range over domain elements (= field values). ■Both TRC and DRC are simple subsets of first-order logic. ♦ Expressions in the calculus are called formulas. An answer tuple is essentially an assignment of constants to variables that make the formula evaluate to true.

2. 2 Query Languages Calculus SQL QBE

3. 3 Domain Relational Calculus ♦ Query has the form: { |p( } ♦ Answer includes all tuples { that make the formula p( } be true. Formula is recursively defined, starting with simple atomic formulas (getting tuples from relations or making comparisons of values), and building bigger and better formulas using the logical connectives.

4. 4 DRC Formulas. ♦Atomic formula:. { | ∈ Rname, or X op Y, or X op constant ■op is one of, ≥ ♦Formula: ■ an atomic formula, or ■ ￢ p, p ∧ q,p v q where p and q are formulas, or ■ ∃ X (p(X)), where variable X is free in p(X), or ■ ∀ X (p(X)), where variable X is free in p(X) ♦The use of quantifiers ∃ X and ∀ X is said to bind X. ■A variable that is not bound is free.

5. 5 Free and Bound Variables ♦The use of quantifiers ∃ X and ∀ X in a formula is said to bind X. ■ A variable that is not bound is free. ♦Let us revisit the definition of a query: { |p( } ♦There is an important restriction: the variables x1,..., xn that appear to the left of `|' must be the only free variables in the formula p(...).

6. 6 Find all sailors with a rating above 7 { | ∈ Sailors ∧ T>7} The condition ∈ Sailors ensures that the domain variables I, N, T and A are bound to fields of the same Sailors tuple. The term to the left of I' (which should be read as such that) says that every tuple that satisfies T>7 is in the answer. Modify this query to answer: ■ Find sailors who are older than 18 or have a rating under 9, and are called 'Joe '.

7. 7 Find sailors rated > 7 who’ve reserved boat #103 { | ∈ Sailors ∧ T>7 ∧ ∃ Ir, Br, D ( ∈ Reserves ∧ Ir=I ∧ Br=103)} We have used ∃ Ir, Br, D (...) as a shorthand for ∃ Ir ( ∃ Br ( ∃ D (...))) Note the use of ∃ to find a tuple in Reserves that `joins with' the Sailors tuple under consideration

8. 8 Find sailors rated > 7 who’ve reserved a red boat { | ∈ Sailors ∧ T>7 ∧ ∃ Ir, Br, D ( ∈ Reserves ∧ Ir=I ∧ ∃ B, BN, C ( ∈ Boats ∧ B=Br ∧ C=' red'} Observe how the parentheses control the scope of each quantifier's binding. This may look cumbersome, but with a good user interface, it is very intuitive.

9. 9 Find sailors who’ve reserved all boats { | ∈ Sailors ∧ ∀ B, BN, C ( ￢ ( ∈ Boats )V ( ∃ Ir,Br,D ( ∈ Reserves ∧ Ir=I ∧ B=Br )))} _Find all sailors I such that for each 3-tuple either it is not a tuple in Boats or there is a tuple in Reserves showing that sailor I has reserved it.

10. 10 Unsafe Queries, Expressive Power It is possible to write syntactically correct calculus queries that have an infinite number of answers! Such queries are called unsafe. e.g. {S| ￢ (S ∈ Sailors)} It is known that every query that can be expressed in relational algebra can be expressed as a safe query in DRC / TRC; the converse is also true. Relational Completeness: Query language (e.g., SQL) can express every query that is expressible in relational algebra/calculus.

11. 11 Summary Relational calculus is non-operational, and users define queries in terms of what they want, not in terms of how to compute it. (Declarativeness.) ¡ Algebra and safe calculus have same expressive power, leading to the notion of relational completeness.

12. 12 Example Instances We will use these instances of the Sailors and Reserves relations in our examples. If the key for the Reserves relation contained only the attributes sid and bid, how would the semantics differ?

13. 13 Basic SQL Query SELECT [DISTINCT] target FROM relation-list WHERE qualification relation-list A list of relation names (possibly with a range-variable after each name). target-list A list of attributes of relations in relation-list qualification Comparisons (Attr op const or Attr1 op Attr2, where op is one of, =,, ^ ) combined using AND, OR and NOT. « DISTINCT is an optional keyword indicating that the answer should not contain duplicates. Default is that duplicates are not eliminated!

14. 14 Conceptual Evaluation Strategy. Semantics of an SQL query defined in terms of the following conceptual evaluation strategy: Compute the cross-product of relation-list. Discard resulting tuples if they fail qualifications. Delete attributes that are not in target-list. If DISTINCT is specified, eliminate duplicate rows. This strategy is probably the least efficient way to compute a query! An optimizer will find more efficient strategies to compute the same answers.

15. 15 Example of Conceptual Evaluation.

16. 16 A Note on Range Variables

17. 17 Find sailors who’ve reserved at least one boat SELECT S.sid FROM Sailors S, Reserves R WHERE S.sid=R.sid Would adding DISTINCT to this query make a difference? What is the effect of replacing S.sid by S.sname in the SELECT clause? Would adding DISTINCT to this variant of the query make a difference?

18. 18 Expressions and Strings. SELECT S.age, age1=S.age-5, 2*S.age AS age2 FROM Sailors S WHERE S.sname LIKE ‘B_%B’ Illustrates use of arithmetic expressions and string pattern matching: Find triples (of ages of sailors and two fields defined by expressions) for sailors whose names begin and end with B and contain at least three characters. _ AS and = are two ways to name fields in result. _ LIKE is used for string matching. `_’ stands for any one character and `%’ stands for 0 or more arbitrary characters.

19. 19 Find sid’s of sailors who’ve reserved a red or a green boat.

20. 20 Find sid’s of sailors who’ve reserved a red and a green boat

21. 21 Nested Queries Find names of sailors who’ve reserved boat #103: SELECT S.sname FROM Sailors S WHERE S.sid IN (SELECT R.sid FROM Reserves R WHERE R.bid=103) _ A very powerful feature of SQL: a WHERE clause can itself contain an SQL query! (Actually, so can FROM and HAVING clauses.) _ To find sailors who’ve not reserved #103, use NOT IN. _ To understand semantics of nested queries, think of a nested loops evaluation: For each Sailors tuple, check the qualification by computing the subquery.

22. 22 Nested Queries with Correlation. Find names of sailors who’ve reserved boat #103: _ EXISTS is another set comparison operator, like IN. _ If UNIQUE is used, and * is replaced by R.bid, finds sailors with at most one reservation for boat #103. (UNIQUE checks for duplicate tuples; * denotes all attributes. Why do we have to replace * by R.bid?) _ Illustrates why, in general, subquery must be re-computed for each Sailors tuple.

23. 23 More on Set-Comparison Operators _ We’ve already seen IN, EXISTS and UNIQUE. Can also use NOT IN, NOT EXISTS and NOT UNIQUE. _ Also available: op ANY, op ALL, op IN, ≥ _ Find sailors whose rating is greater than that of some sailor called Horatio: SELECT * FROM Sailors S WHERE S.rating > ANY (SELECT S2.rating FROM Sailors S2 WHERE S2.sname=‘Horatio’).

24. 24 Rewriting INTERSECT Queries Using IN SELECT S.sid FROM Sailors S, Boats B, Reserves R WHERE S.sid=R.sid AND R.bid=B.bid AND B.color=‘red’ AND S.sid IN (SELECT S2.sid FROM Sailors S2, Boats B2, Reserves R2 WHERE S2.sid=R2.sid AND R2.bid=B2.bid AND B2.color=‘green’) _ Similarly, EXCEPT queries re-written using NOT IN. _ To find names (not sid’s) of Sailors who’ve reserved both red and green boats, just replace S.sid by S.sname in SELECT clause. (What about INTERSECT query?)

25. 25 Division in SQL Find sailors who’ve reserved all boats. Let’s do it the hard way, without EXCEPT: (2) SELECT S.sname FROM Sailors S WHERE NOT EXISTS (SELECT B.bid FROM Boats B WHERE NOT EXISTS (SELECT R.bid FROM Reserves R WHERE R.bid=B.bid AND R.sid=S.sid)) Sailors S such that... there is no boat B without... a Reserves tuple showing S reserved B (1) SELECT S.sname FROM Sailors S WHERE NOT EXISTS ((SELECT B.bid FROM Boats B) EXCEPT (SELECT R.bid FROM Reserves R WHERE R.sid=S.sid))

26. 26 Aggregate Operators COUNT (*) COUNT ( [DISTINCT] A) SUM ( [DISTINCT] A) AVG ( [DISTINCT] A) MAX (A) MIN (A) Significant extension of relational algebra.

27. 27 Find name and age of the oldest sailor(s) The first query is illegal! (We’ll look into the reason a bit later, when we discuss GROUP BY.) The third query is equivalent to the second query, and is allowed in the SQL/92 standard, but is not supported in some systems.

28. 28 GROUP BY and HAVING So far, we’ve applied aggregate operators to all (qualifying) tuples. Sometimes, we want to apply them to each of several groups of tuples. Consider: Find the age of the youngest sailor for each rating level. In general, we don’t know how many rating levels exist, and what the rating values for these levels are! Suppose we know that rating values go from 1 to 10; we can write 10 queries that look like this (!): For i = 1, 2,..., 10: SELECT MIN (S.age) FROM Sailors S WHERE S.rating = i

29. 29 Queries With GROUP BY and HAVING SELECT [DISTINCT] target-list FROM relation-list WHERE qualification GROUP BY grouping-list HAVING group-qualification The target-list contains (i) attribute names (ii) terms with aggregate operations (e.g., MIN (S.age)). The attribute list (i) must be a subset of grouping-list. Intuitively, each answer tuple corresponds to a group, and these attributes must have a single value per group. (A group is a set of tuples that have the same value for all attributes in grouping-list.)

30. 30 Conceptual Evaluation The cross-product of relation-list is computed, tuples that fail qualification are discarded, `unnecessary’ fields are deleted, and the remaining tuples are partitioned into groups by the value of attributes in grouping-list. The group-qualification is then applied to eliminate some groups. Expressions in group-qualification must have a single value per group! In effect, an attribute in group-qualification that is not an argument of an aggregate op also appears in grouping-list. (SQL does not exploit primary key semantics here!) One answer tuple is generated per qualifying group

31. 31 SELECT S.rating, MIN (S.age) FROM Sailors S WHERE S.age >= 18 GROUP BY S.rating HAVING COUNT (*) > 1. Only S.rating and S.age are mentioned in the SELECT, GROUP BY or HAVING clauses; other attributes `unnecessary’. 2nd column of result is unnamed. (Use AS to name it.) Find the age of the youngest sailor with age 18, for each rating with at least 2 such sailors

32. 32 For each red boat, find the number of reservations for this boat SELECT B.bid, COUNT (*) AS scount FROM Sailors S, Boats B, Reserves R WHERE S.sid=R.sid AND R.bid=B.bid AND B.color=‘red’ GROUP BY B.bid Grouping over a join of three relations. What do we get if we remove B.color=‘red’ from the WHERE clause and add a HAVING clause with this condition? What if we drop Sailors and the condition involving S.sid?

33. 33 Find the age of the youngest sailor with age > 18, for each rating with at least 2 sailors (of any age) SELECT S.rating, MIN (S.age) FROM Sailors S WHERE S.age > 18 GROUP BY S.rating HAVING 1 < (SELECT COUNT (*) FROM Sailors S2 WHERE S.rating=S2.rating) Shows HAVING clause can also contain a subquery. Compare this with the query where we considered only ratings with 2 sailors over 18 What if HAVING clause is replaced by: HAVING COUNT(*) >1

34. 34 Find those ratings for which the average age is the minimum over all ratings _ Aggregate operations cannot be nested! WRONG: SELECT S.rating FROM Sailors S WHERE S.age = (SELECT MIN (AVG (S2.age)) FROM Sailors S2) v Correct solution (in SQL/92): SELECT Temp.rating, Temp.avgage FROM (SELECT S.rating, AVG (S.age) AS avgage FROM Sailors S GROUP BY S.rating) AS Temp WHERE Temp.avgage = (SELECT MIN (Temp.avgage) FROM Temp).

35. 35 Null Values Field values in a tuple are sometimes unknown (e.g., a rating has not been assigned) or inapplicable (e.g., no spouse’s name). SQL provides a special value null for such situations. The presence of null complicates many issues. E.g.: Special operators needed to check if value is/is not null. Is rating>8 true or false when rating is equal to null? What about AND, OR and NOT connectives? We need a 3-valued logic (true, false and unknown). Meaning of constructs must be defined carefully. (e.g., WHERE clause eliminates rows that don’t evaluate to true.) New operators (in particular, outer joins) possible/needed.

36. 36 Integrity Constraints (Review) An IC describes conditions that every legal instance of a relation must satisfy. Inserts/deletes/updates that violate IC’s are disallowed. Can be used to ensure application semantics (e.g., sid is a key), or prevent inconsistencies (e.g., sname has to be a string, age must be < 200) Types of IC’s: Domain constraints, primary key constraints, foreign key constraints, general constraints. Domain constraints: Field values must be of right type. Always enforced.

37. 37 General Constraints Useful when more general ICs than keys are involved. Can use queries to express constraint. Constraints can be named. CREATE TABLE Sailors ( sid INTEGER, sname CHAR(10), rating INTEGER, age REAL, PRIMARY KEY (sid), CHECK ( rating >= 1 AND rating <= 10 ) CREATE TABLE Reserves ( sname CHAR(10), bid INTEGER, day DATE, PRIMARY KEY (bid,day), CONSTRAINT noInterlakeRes CHECK (`Interlake’ <> ( SELECT B.bname FROM Boats B WHERE B.bid=bid)))

38. 38 Triggers Trigger: procedure that starts automatically if specified changes occur to the DBM Three parts: Event (activates the trigger) Condition (tests whether the triggers should run) Action (what happens if the trigger runs)

39. 39 Triggers: Example (SQL:1999) CREATE TRIGGER youngSailorUpdate AFTER INSERT ON SAILORS REFERENCING NEW TABLE NewSailors FOR EACH STATEMENT INSERT INTO YoungSailors(sid, name, age, rating) SELECT sid, name, age, rating FROM NewSailors N WHERE N.age <= 18

40. 40 Summary SQL was an important factor in the early acceptance of the relational model; more natural than earlier, procedural query languages. Relationally complete; in fact, significantly more expressive power than relational algebra. Even queries that can be expressed in RA can often be expressed more naturally in SQL. Many alternative ways to write a query; optimizer should look for most efficient evaluation plan. In practice, users need to be aware of how queries are optimized and evaluated for best results. NULL for unknown field values brings many complications SQL allows specification of rich integrity constraints Triggers respond to changes in the database

41. 41 QBE: Intro A “GUI” for expressing queries. Based on the DRC! Actually invented before GUIs. Very convenient for simple queries. Awkward for complex queries. QBE an IBM trademark. But has influenced many projects

42. 42 ‘Example Tables’ in QBE Users specify a query by filling in example tables, orskeletons; we will use these skeletons in our examples.

43. 43 To print names and ages of all sailors: Print all fields for sailors with rating > 8, in ascending order by (rating, age): QBE puts unique new variables in blank columns. Above query in DRC (no ordering): { | ∈ Sailors ∧ T>7} Basics

44. 44 _ Names of sailors younger than 30 or older than 20: _ Names of sailors younger than 30 and older than 20: _ Names of sailors younger than 30 and rating > 4: And/Or Queries

45. 45 _ Single row with P: Duplicates not eliminated by default; can force elimination by using UNQ. _ Multiple rows with P: Duplicates eliminated by default! Can avoid elimination by using ALL. Duplicates

46. 46 Join Queries _ Names of sailors who’ve reserved a boat for 8/24/96 and are older than 25 (note that dates and strings with blanks/special chars are quoted): _ Joins accomplished by repeating variables.

47. 47 Join Queries (Contd.). _ Colors of boats reserved by sailors who’ve reserved a boat for 8/24/96 and are older than 25 :

48. 48 Join Queries (Contd.) _ Names and ages of sailors who’ve reserved some boat that is also reserved by the sailor with sid = 22:

49. 49 Unnamed Columns Useful if we want to print the result of an expression, or print fields from 2 or more relations. QBE allows P. to appear in at most one table!

50. 50 “Negative Tables”. _ Can place a negation marker in the relation column: _ Variables appearing in a negated table must also appear in a positive table!

51. 51 Aggregates QBE supports AVG, COUNT, MIN, MAX, SUM None of these eliminate duplicates, except COUNT Also have AVG.UNQ. etc. to force duplicate elimination The columns with G. are the group-by fields; all tuples in a group have the same values in these fields. The (optional) use of.AO orders the answers. Every column with P. must include G. or an aggregate operator..

52. 52 _ Used to express conditions involving 2 or more columns, e.g., _R/_A > 0.2. _ Can express a condition that involves a group, similar to the HAVING clause in SQL: _ Express conditions involving AND and OR: Conditions Box

53. 53 Find sailors who’ve reserved all boats _ A division query; need aggregates (or update operations, as we will see later) to do this in QBE. _ How can we modify this query to print the names of sailors who’ve reserved all boats?

54. 54 _ Single-tuple insertion: _ Inserting multiple tuples (rating is null in tuples inserted below): Inserting Tuples

55. 55 _ Delete all reservations for sailors with rating < 4 _ Increment the age of the sailor with sid = 74 Delete and Update

56. 56 Restrictions on Update Commands Cannot mix I., D. and U. in a single example table, or combine them with P. or G. Cannot insert, update or modify tuples using values from fields of other tuples in the same table. Example of an update that violates this rule: Should we update every Joe’s age? Which John’s age should we use?

57. 57 Find sailors who’ve reserved all boats (Again!) _ We want to find sailors _Id such that there is no boat _B that is not reserved by _Id: _ Illegal query! Variable _B does not appear in a positive row. In what order should the two negative rows be considered? (Meaning changes)

58. 58 _ Find sailors who’ve not reserved some boat _B: _ Next, find sailors not in this `bad’ set: A Solution Using Views

59. 59 Summary QBE is an elegant, user-friendly query language based on DRC. It is quite expressive (relationally complete, if the update features are taken into account). Simple queries are especially easy to write in QBE, and there is a minimum of syntax to learn. Has influenced the graphical query facilities offered in many products