s kyline q uery p rocessing over j oins. akrivi vlachou1, christos doulkeridis1, neoklis polyzotis...

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SKYLINE QUERY PROCESSING OVER JOINS. Akrivi Vlachou1, Christos Doulkeridis1, Neoklis Polyzotis SIGMOD 2011

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SKYLINE QUERY PROCESSING OVER JOINS.Akrivi Vlachou1, Christos Doulkeridis1, Neoklis PolyzotisSIGMOD 2011

OUTLINE

Introduction Preliminaries Early Termination The SFSJ Algorithm Experimental Evaluation Conclusions

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INTRODUCTION

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(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 .

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PRELIMINARIES

R: relation. : a set of numerical attributes in the

schema of R. :tuples in R. with respect to :

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(CONT.)

== {Price,Rating} and = {Distance,Quality}

Assum any attribute is the inteval [0,1]

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(CONT.)

x=A, group skyline: R2x=B, group skyline: R1,R3skyline:R2 7

RID Distance 1/Quality LocationR1 100 1 BR2 100 ¼ AR3 200 ½ BR4 200 1 A

(CONT.)

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PID Price Join Attr.P1 100 BP2 500 AP3 400 BP4 500 A

QID Quality Join Attr.Q1 1 BQ2 4 AQ3 2 BQ4 1 A

EARLY TERMINATION

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.

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(CONT.)

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Join,threshold x=0.3, pruned tuple fmin>=0.3

(CONT.)

0.1 0.30.1 0.80.35 0.20.6 0.2

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SaLSa need to join all tuple but it may be not skyline.

(CONT.)

Condition for Early Te:rmination:

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(CONT.)

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=0.3

(CONT.)

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(CONT.)

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(CONT)

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(CONT.)

exist join value=B in =

SKY( ) ={ (Join Value=A), (Join Value = B)}

exist join value=A in =

exist join value=B in =

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(CONT.)

=( 0.1 , 0.1 , 0.2 , 0.2 ) =( 0.2 , 0.3 , 0.1 , 0.5 ) , }

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THE SFSJ ALGORITHM

SFSJ(Sort-First-Skyline-Join) Algorithm

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(CONT.)

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(CONT.)

i=1,j=2 insert Add to ,

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Iteration 1

(CONT.)

i=1,j=2 insert Add to ,

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Iteration 1

(CONT.)

i=2,j=1 insert Add to ,

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Iteration 2

(CONT.)

i=2,j=1 insert Add to ,

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Iteration 2

(CONT.)

i=1,j=2 insert

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Iteration 3

(CONT.)

i=1,j=2 insert

add to 26

Iteration 3

(CONT.)

i=1,j=2 insert

add to 27

Iteration 3

(CONT.)

i=1,j=2 insert

add to 28

Iteration 3

(CONT.)

i=1,j=2 insert halt :false ( no SKY( ) join

)

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Iteration 3

(CONT.)

i=1,j=2 insert add to ,

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Iteration 3

(CONT.)

i=1,j=2 insert add to ,

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Iteration 3

(CONT.)

i=2,j=1 insert

Add to 32

Iteration 4

(CONT.)

i=2,j=1 insert

Add to 33

Iteration 4

(CONT.)

i=2,j=1 insert Add to ,

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Iteration 4

(CONT.)

i=2,j=1 insert Add to ,

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Iteration 4

(CONT.)

i=1,j=2 insert Add to

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Iteration 5

(CONT.)

i=1,j=2 insert Add to

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Iteration 5

(CONT.)

i=2,j=1 insert

Add to 38

Iteration 6

(CONT.)

i=2,j=1 insert

Add to 39

Iteration 6

(CONT.)

i=2,j=1 insert

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Iteration 6

(CONT.)

i=2,j=1 insert

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Iteration 6

(CONT.)

i=2,j=1 insert

, add to O.

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Iteration 6

(CONT.)

i=2,j=1 insert

, add to O.

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Iteration 6

(CONT.)

i=2,j=1 insert

Add to 44

Iteration 6

(CONT.)

i=2,j=1 insert

Add to 45

Iteration 6

(CONT.)

i=2,j=1 insert

Add to 46

Iteration 6

(CONT.)

i=2,j=1 insert

Add to 47

Iteration 6

(CONT.)

i=2,j=1 insert halt: true ( join SKY(

)) Return O , =O

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Iteration 6

EXPERIMENTAL EVALUATION

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(CONT.)

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CONCLUSIONS

SFSJ is better than other method like PROGXE SFSJ-SC is better than SFSJ-RR

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