kyriakos mouratidis, spiridon bakiras, dimitris papadias sigmod 2006 1
TRANSCRIPT
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Continuous Monitoring of Top-k Queries over SlidingWindows
Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Papadias
SIGMOD 2006
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Motivation
Preliminaries
Method◦ TMA(Top-k Monitoring Algorithm)◦ SMA(Skyband Monitoring Algorithm)
Experimental evaluation
Conclusion
Outline
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The existing methods are inapplicable to highly dynamic environments involving numerous longrunning queries.
This paper studies continuous monitoring of top-k queries over a fixed-size window W of the most recent data.
Motivation
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f(X1,X2)=X1+2*X2
Preliminaries
(0.2,1)
(1,0.7)
(0.6,0.8)
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Cont.K-skyband :Returns those objects that are dominated by at most K-1 other objects.
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TMA(Top-k Monitoring Algorithm)
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f(X1,X2)=X1+2*X2
Top-1
Computation Module
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F(X1,X2)=X1-X2
Top-2
Cont.
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P1,P2 expire P3,P4 arriveSearch influence list-> P3 has maxscoreP3 become the result of top-1 query
Maintenance Module
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P3 expire P5 arrive invokes the top-k computation module
Cont.
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SMA applies the reduction from top-k to k-skyband queries in order to avoid computation from scratch when some results expire.
SMA(Skyband Monitoring Algorithm)
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DC(dominance counter)
2-skybandWhen DC reach 2,then delete.
Cont.
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P9 arrive
Cont.
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P9 arrive
Cont.
(2)
(1)
(2)
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P9 arrive
Cont.
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SMA is expected to be faster than TMA, since it involves less frequent calls to the top-k computation module.
Cont.
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Experimental evaluation
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TMA re-computes the result from scratch, whereas SMA maintains a superset of the current answer in the form of a k-skyband, in order to avoid frequent recomputations.
Conclusion