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Parallel Skyline Computation on Multicore Architectures. ICDE`09. Outline. Introduction Preliminary Parallel BBS(branch-and-bound algorithm) Parallel Skyline Algorithm ( Pskyline ) Experiments Conclusion. Introduction. (cont.). The advantage of the skyline Skyline algorithm Sequential

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Parallel Skyline Computation on Multicore Architectures

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## Parallel Skyline Computation on Multicore Architectures

ICDE`09

### Outline

• Introduction

• Preliminary

• Parallel BBS(branch-and-bound algorithm)

• Parallel Skyline Algorithm (Pskyline)

• Experiments

• Conclusion

### (cont.)

• The advantage of the skyline

• Skyline algorithm

• Sequential

• No index structure

• BNL、SFS 、LESS

• Index structure

• NN 、BBS 、ZSHARE

• Parallel

• Many in Distributed environment, but no algorithm for multi-core environment

### Prrliminary

• A. Skyline computation

• For a d-dimensional dataset D.

• skyline set :

• Incomparable :

• Transitivity :

• Incomparability :

• Distributivity :

### (cont.)

• B.Skeletal parallel programming

• A programming model

• Need two component :

• Data structure

• List :

• Parallel skeletons

• not

• For developing parallel skyline algorithm

• Parallel map and Parallel reduce

### (cont.)

• Pmap (parallel map)

A

B

C

D

E

F

G

H

A’

B’

C’

D’

E’

F’

G’

H’

### (cont.)

• Preduce (parallel reduce)

A

B

C

D

E

F

G

H

A’

B’

C’

D’

……

R

### Parallel BBS

• A. branch-and-bound algorithm

• Use R-tree as its index structure

### (cont.)

• B.Parallelizing BBS

### Parallel skyline algorithm (Pskyline)

• Overall design

• Pskyline D = S(D)

• PskylineD = sreducepmerge (pmapsskyline L)

• L = [D1,…,Db] D = D1++…++Db

• Sreduce

• Pmerge

• Sskyline

### Conclusion

• Muliti-core architecture for database operations.