1. S KYLINE Q UERY P ROCESSING OVER J OINS. Akrivi Vlachou1, Christos Doulkeridis1, Neoklis Polyzotis SIGMOD 2011

2. OUTLINE Introduction Preliminaries Early Termination The SFSJ Algorithm Experimental Evaluation Conclusions 2

3. I NTRODUCTION 3

4. ( CONT.) Propose a novel algorithm for efficiently computing the skyline set of a join without generating all the join tuples and without accessing all tuples of and. 4

5. P RELIMINARIES R: relation. : a set of numerical attributes in the schema of R. :tuples in R. with respect to : 5

6. (CONT.) == {Price,Rating} and = {Distance,Quality} Assum any attribute is the inteval [0,1] 6

7. (CONT.) x=A, group skyline: R2 x=B, group skyline: R1,R3 skyline:R2 7 RIDDistance1/QualityLocation R11001B R2100¼A R3200½B R42001A

8. (CONT.) 8 PIDPriceJoin Attr. P1100B P2500A P3400B P4500A QIDQualityJoin Attr. Q11B Q24A Q32B Q41A

9. E ARLY T ERMINATION Assume each relation is accessed one tuple at a time, in an ascending order according to the following function: Check Inadequacy of Existing Techniques: have to join all possible tuples. 9

10. (C ONT.) 10 Join,threshold x=0.3, pruned tuple fmin>=0.3

11. (C ONT.) 0.10.3 0.10.8 0.350.2 0.60.2 11 SaLSa need to join all tuple but it may be not skyline.

12. (C ONT.) Condition for Early Te:rmination: 12

13. (C ONT.) 13 =0.3

14. (C ONT.) 14

15. (C ONT.) 15

16. (C ONT ) 16

17. (C ONT.) exist join value=B in = SKY( ) ={ (Join Value=A), (Join Value = B)} exist join value=A in = exist join value=B in = 17

18. (C ONT.) =( 0.1, 0.1, 0.2, 0.2 ) =( 0.2, 0.3, 0.1, 0.5 ), } 18

19. T HE SFSJ A LGORITHM SFSJ( Sort-First-Skyline-Join) Algorithm 19

20. (C ONT.) 20

21. (C ONT.) i=1,j=2 insert Add to, 21 Iteration 1

22. (C ONT.) i=1,j=2 insert Add to, 22 Iteration 1

23. (C ONT.) i=2,j=1 insert Add to, 23 Iteration 2

24. (C ONT.) i=2,j=1 insert Add to, 24 Iteration 2

25. (C ONT.) i=1,j=2 insert 25 Iteration 3

26. (C ONT.) i=1,j=2 insert add to 26 Iteration 3

27. (C ONT.) i=1,j=2 insert add to 27 Iteration 3

28. (C ONT.) i=1,j=2 insert add to 28 Iteration 3

29. (C ONT.) i=1,j=2 insert halt :false ( no SKY( ) join ) 29 Iteration 3

30. (C ONT.) i=1,j=2 insert add to, 30 Iteration 3

31. (C ONT.) i=1,j=2 insert add to, 31 Iteration 3

32. (C ONT.) i=2,j=1 insert Add to 32 Iteration 4

33. (C ONT.) i=2,j=1 insert Add to 33 Iteration 4

34. (C ONT.) i=2,j=1 insert Add to, 34 Iteration 4

35. (C ONT.) i=2,j=1 insert Add to, 35 Iteration 4

36. (C ONT.) i=1,j=2 insert Add to 36 Iteration 5

37. (C ONT.) i=1,j=2 insert Add to 37 Iteration 5

38. (C ONT.) i=2,j=1 insert Add to 38 Iteration 6

39. (C ONT.) i=2,j=1 insert Add to 39 Iteration 6

40. (C ONT.) i=2,j=1 insert 40 Iteration 6

41. (C ONT.) i=2,j=1 insert 41 Iteration 6

42. (C ONT.) i=2,j=1 insert, add to O. 42 Iteration 6

43. (C ONT.) i=2,j=1 insert, add to O. 43 Iteration 6

44. (C ONT.) i=2,j=1 insert Add to 44 Iteration 6

45. (C ONT.) i=2,j=1 insert Add to 45 Iteration 6

46. (C ONT.) i=2,j=1 insert Add to 46 Iteration 6

47. (C ONT.) i=2,j=1 insert Add to 47 Iteration 6

48. (C ONT.) i=2,j=1 insert halt: true ( join SKY( )) Return O, =O 48 Iteration 6

49. E XPERIMENTAL E VALUATION 49

50. ( CONT.) 50

51. C ONCLUSIONS SFSJ is better than other method like PROGXE SFSJ-SC is better than SFSJ-RR 51