1. Database Management Systems Chapter 5 The Relational Algebra Instructor: Li Ma Department of Computer Science Texas Southern University, Houston October, 2006

2. Relational Algebra Operators Expression Trees Bag Model of Data

3. Jeffrey Ullman3 What is an “Algebra” uMathematical system consisting of: wOperands --- variables or values from which new values can be constructed. wOperators --- symbols denoting procedures that construct new values from given values.

4. Jeffrey Ullman4 What is Relational Algebra? uAn algebra whose operands are relations or variables that represent relations. uOperators are designed to do the most common things that we need to do with relations in a database. wThe result is an algebra that can be used as a query language for relations.

5. Jeffrey Ullman5 Roadmap uThere is a core relational algebra that has traditionally been thought of as the relational algebra. uBut there are several other operators we shall add to the core in order to model better the language SQL --- the principal language used in relational database systems.

6. Jeffrey Ullman6 Core Relational Algebra uUnion, intersection, and difference. wUsual set operations, but require both operands have the same relation schema. uSelection: picking certain rows. uProjection: picking certain columns. uProducts and joins: compositions of relations. uRenaming of relations and attributes.

7. Jeffrey Ullman7 Selection uR1 := SELECT C (R2) wC is a condition (as in “if” statements) that refers to attributes of R2. wR1 is all those tuples of R2 that satisfy C.

8. Jeffrey Ullman8 Example Relation Sells: barbeerprice Joe’sBud2.50 Joe’sMiller2.75 Sue’sBud2.50 Sue’sMiller3.00 JoeMenu := SELECT bar=“Joe’s” (Sells): barbeerprice Joe’sBud2.50 Joe’sMiller2.75

9. Jeffrey Ullman9 Projection uR1 := PROJ L (R2) wL is a list of attributes from the schema of R2. wR1 is constructed by looking at each tuple of R2, extracting the attributes on list L, in the order specified, and creating from those components a tuple for R1. wEliminate duplicate tuples, if any.

10. Jeffrey Ullman10 Example Relation Sells: barbeerprice Joe’sBud2.50 Joe’sMiller2.75 Sue’sBud2.50 Sue’sMiller3.00 Prices := PROJ beer,price (Sells): beerprice Bud2.50 Miller2.75 Miller3.00

11. Jeffrey Ullman11 Product uR3 := R1 * R2 wPair each tuple t1 of R1 with each tuple t2 of R2. wConcatenation t1t2 is a tuple of R3. wSchema of R3 is the attributes of R1 and then R2, in order. wBut beware attribute A of the same name in R1 and R2: use R1.A and R2.A.

12. Jeffrey Ullman12 Example: R3 := R1 * R2 R1(A,B ) 12 34 R2(B,C ) 56 78 910 R3(A,R1.B,R2.B,C ) 1256 1278 12910 3456 3478 34910

13. Jeffrey Ullman13 Theta-Join uR3 := R1 JOIN C R2 wTake the product R1 * R2. wThen apply SELECT C to the result. uAs for SELECT, C can be any boolean- valued condition. wHistoric versions of this operator allowed only A  B, where  is =, <, etc.; hence the name “theta-join.”

14. Jeffrey Ullman14 Example Sells(bar,beer,price )Bars(name,addr ) Joe’sBud2.50Joe’sMaple St. Joe’sMiller2.75Sue’sRiver Rd. Sue’sBud2.50 Sue’sCoors3.00 BarInfo := Sells JOIN Sells.bar = Bars.name Bars BarInfo(bar,beer,price,name,addr ) Joe’sBud2.50Joe’sMaple St. Joe’sMiller2.75Joe’sMaple St. Sue’sBud2.50Sue’sRiver Rd. Sue’sCoors3.00Sue’sRiver Rd.

15. Jeffrey Ullman15 Natural Join uA frequent type of join connects two relations by: wEquating attributes of the same name, and wProjecting out one copy of each pair of equated attributes. uCalled natural join. uDenoted R3 := R1 JOIN R2.

16. Jeffrey Ullman16 Example Sells(bar,beer,price )Bars(bar,addr ) Joe’sBud2.50Joe’sMaple St. Joe’sMiller2.75Sue’sRiver Rd. Sue’sBud2.50 Sue’sCoors3.00 BarInfo := Sells JOIN Bars Note Bars.name has become Bars.bar to make the natural join “work.” BarInfo(bar,beer,price,addr ) Joe’sBud2.50Maple St. Joe’sMilller2.75Maple St. Sue’sBud2.50River Rd. Sue’sCoors3.00River Rd.

17. Jeffrey Ullman17 Renaming uThe RENAME operator gives a new schema to a relation. uR1 := RENAME R1(A1,…,An) (R2) makes R1 be a relation with attributes A1,…,An and the same tuples as R2. uSimplified notation: R1(A1,…,An) := R2.

18. Jeffrey Ullman18 Example Bars(name, addr ) Joe’sMaple St. Sue’sRiver Rd. R(bar, addr ) Joe’sMaple St. Sue’sRiver Rd. R(bar, addr) := Bars

19. Jeffrey Ullman19 Building Complex Expressions uCombine operators with parentheses and precedence rules. uThree notations, just as in arithmetic: 1.Sequences of assignment statements. 2.Expressions with several operators. 3.Expression trees.

20. Jeffrey Ullman20 Sequences of Assignments uCreate temporary relation names. uRenaming can be implied by giving relations a list of attributes. uExample: R3 := R1 JOIN C R2 can be written: R4 := R1 * R2 R3 := SELECT C (R4)

21. Jeffrey Ullman21 Expressions in a Single Assignment uExample: the theta-join R3 := R1 JOIN C R2 can be written: R3 := SELECT C (R1 * R2) uPrecedence of relational operators: 1.[SELECT, PROJECT, RENAME] (highest). 2.[PRODUCT, JOIN]. 3.INTERSECTION. 4.[UNION, --]

22. Jeffrey Ullman22 Expression Trees uLeaves are operands --- either variables standing for relations or particular, constant relations. uInterior nodes are operators, applied to their child or children.

23. Jeffrey Ullman23 Example uUsing the relations Bars(name, addr) and Sells(bar, beer, price), find the names of all the bars that are either on Maple St. or sell Bud for less than $3.

24. Jeffrey Ullman24 As a Tree: BarsSells SELECT addr = “Maple St.” SELECT price<3 AND beer=“Bud” PROJECT name RENAME R(name) PROJECT bar UNION

25. Jeffrey Ullman25 Example uUsing Sells(bar, beer, price), find the bars that sell two different beers at the same price. uStrategy: by renaming, define a copy of Sells, called S(bar, beer1, price). The natural join of Sells and S consists of quadruples (bar, beer, beer1, price) such that the bar sells both beers at this price.

26. Jeffrey Ullman26 The Tree Sells RENAME S(bar, beer1, price) JOIN PROJECT bar SELECT beer != beer1

27. Jeffrey Ullman27 Schemas for Results uUnion, intersection, and difference: the schemas of the two operands must be the same, so use that schema for the result. uSelection: schema of the result is the same as the schema of the operand. uProjection: list of attributes tells us the schema.

28. Jeffrey Ullman28 Schemas for Results --- (2) uProduct: schema is the attributes of both relations. wUse R.A, etc., to distinguish two attributes named A. uTheta-join: same as product. uNatural join: union of the attributes of the two relations. uRenaming: the operator tells the schema.

29. Jeffrey Ullman29 Relational Algebra on Bags uA bag (or multiset ) is like a set, but an element may appear more than once. uExample: {1,2,1,3} is a bag. uExample: {1,2,3} is also a bag that happens to be a set.

30. Jeffrey Ullman30 Why Bags? uSQL, the most important query language for relational databases, is actually a bag language. uSome operations, like projection, are much more efficient on bags than sets.

31. Jeffrey Ullman31 Operations on Bags uSelection applies to each tuple, so its effect on bags is like its effect on sets. uProjection also applies to each tuple, but as a bag operator, we do not eliminate duplicates. uProducts and joins are done on each pair of tuples, so duplicates in bags have no effect on how we operate.

32. Jeffrey Ullman32 Example: Bag Selection R(A,B ) 12 56 12 SELECT A+B<5 (R) =AB 12

33. Jeffrey Ullman33 Example: Bag Projection R(A,B ) 12 56 12 PROJECT A (R) =A 1 5 1

34. Jeffrey Ullman34 Example: Bag Product R(A,B )S(B,C ) 1234 5678 12 R * S =AR.BS.BC 1234 1278 5634 5678 1234 1278

35. Jeffrey Ullman35 Example: Bag Theta-Join R(A,B )S(B,C ) 1234 5678 12 R JOIN R.B<S.B S =AR.BS.BC 1234 1278 5678 1234 1278

36. Jeffrey Ullman36 Bag Union uAn element appears in the union of two bags the sum of the number of times it appears in each bag. uExample: {1,2,1} UNION {1,1,2,3,1} = {1,1,1,1,1,2,2,3}

37. Jeffrey Ullman37 Bag Intersection uAn element appears in the intersection of two bags the minimum of the number of times it appears in either. uExample: {1,2,1,1} INTER {1,2,1,3} = {1,1,2}.

38. Jeffrey Ullman38 Bag Difference uAn element appears in the difference A – B of bags as many times as it appears in A, minus the number of times it appears in B. wBut never less than 0 times. uExample: {1,2,1,1} – {1,2,3} = {1,1}.

39. Jeffrey Ullman39 Beware: Bag Laws != Set Laws uSome, but not all, algebraic laws that hold for sets also hold for bags. uExample: the commutative law for union (R UNION S = S UNION R ) does hold for bags. wSince addition is commutative, adding the number of times x appears in R and S doesn’t depend on the order of R and S.

40. Jeffrey Ullman40 Example of the Difference uSet union is idempotent, meaning that S UNION S = S. uHowever, for bags, if x appears n times in S, then it appears 2n times in S UNION S. uThus S UNION S != S in general.

41. Jeffrey Ullman41 The Extended Algebra 1.DELTA = eliminate duplicates from bags. 2.TAU = sort tuples. 3.Extended projection : arithmetic, duplication of columns. 4.GAMMA = grouping and aggregation. 5.Outerjoin : avoids “dangling tuples” = tuples that do not join with anything.

42. Jeffrey Ullman42 Duplicate Elimination uR1 := DELTA(R2). uR1 consists of one copy of each tuple that appears in R2 one or more times.

43. Jeffrey Ullman43 Example: Duplicate Elimination R = (AB ) 12 34 12 DELTA(R) =AB 12 34

44. Jeffrey Ullman44 Sorting uR1 := TAU L (R2). wL is a list of some of the attributes of R2. uR1 is the list of tuples of R2 sorted first on the value of the first attribute on L, then on the second attribute of L, and so on. wBreak ties arbitrarily. uTAU is the only operator whose result is neither a set nor a bag.

45. Jeffrey Ullman45 Example: Sorting R = ( AB ) 12 34 52 TAU B (R) =[(5,2), (1,2), (3,4)]

46. Jeffrey Ullman46 Extended Projection uUsing the same PROJ L operator, we allow the list L to contain arbitrary expressions involving attributes, for example: 1.Arithmetic on attributes, e.g., A+B. 2.Duplicate occurrences of the same attribute.

47. Jeffrey Ullman47 Example: Extended Projection R = ( AB ) 12 34 PROJ A+B,A,A (R) =A+BA1A2 311 733

48. Jeffrey Ullman48 Aggregation Operators uAggregation operators are not operators of relational algebra. uRather, they apply to entire columns of a table and produce a single result. uThe most important examples: SUM, AVG, COUNT, MIN, and MAX.

49. Jeffrey Ullman49 Example: Aggregation R = ( AB ) 13 34 32 SUM(A) = 7 COUNT(A) = 3 MAX(B) = 4 AVG(B) = 3

50. Jeffrey Ullman50 Grouping Operator uR1 := GAMMA L (R2). L is a list of elements that are either: 1.Individual (grouping ) attributes. 2.AGG(A ), where AGG is one of the aggregation operators and A is an attribute.

51. Jeffrey Ullman51 Applying GAMMA L (R) uGroup R according to all the grouping attributes on list L. wThat is: form one group for each distinct list of values for those attributes in R. uWithin each group, compute AGG(A ) for each aggregation on list L. uResult has one tuple for each group: 1.The grouping attributes and 2. Their group’s aggregations.

52. Jeffrey Ullman52 Example: Grouping/Aggregation R = ( ABC ) 123 456 125 GAMMA A,B,AVG(C) (R) = ?? First, group R by A and B : ABC 123 125 456 Then, average C within groups: ABAVG(C) 12 4 45 6

53. Jeffrey Ullman53 Outerjoin uSuppose we join R JOIN C S. uA tuple of R that has no tuple of S with which it joins is said to be dangling. wSimilarly for a tuple of S. uOuterjoin preserves dangling tuples by padding them with a special NULL symbol in the result.

54. Jeffrey Ullman54 Example: Outerjoin R = ( AB )S = ( BC ) 1223 4567 (1,2) joins with (2,3), but the other two tuples are dangling. R OUTERJOIN S =ABC 123 45NULL NULL67

55. Jeffrey Ullman55 Constraint Language uConstraints are very important in database programming uRelational algebra provides a means to express common constraints uIf R and S are expressions of relational algebra, two ways to express constraints wR = 0 means “The value of R must be empty”. w“R is a subset of S” means “Every tuple in the result of R must also in the result of S”.

56. Jeffrey Ullman56 Constraint Language -- (2) uThose constraints also hold if R and S are bags w“R ≤ S” means “Each tuple appears in S at least as many times as it appears in R”. uThe first style (equal-to-empty-set) is most commonly used in SQL programming

57. Jeffrey Ullman57 Example uTwo relations: wBars (Name, Drinker, Beer) wBeers (Name, Manf) uConstrains: All beers sold in every bar should appear in relation Beers wPROJ Beer (Bars) is a subset of PROJ Name (Beers) wPROJ Beer (Bars) - PROJ Name (Beers) = 0

58. Jeffrey Ullman58 Example -- (2) uRelation wR (A, B, C) with FD A -> C uConstrains: for all pairs of R’s tuples (t1, t2), we must not find a pair that agree in A component, but disagree in C component wRENAME S(A, B, C) (R) wSELECT (R.A=S.A) AND (R.C!=S.C) (RxS) = 0