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Creating Competitive Products

Creating Competitive Products. Qian Wan [1] , Raymond Chi-Wing Wong [1] , Ihab F. Ilyas [2] , M. Tamer Ozsu [2] , Yu Peng [1] [1] Hong Kong University of Science and Technology [2] University of Waterloo Presented by Qian Wan Prepared by Qian Wan. Outline. Background

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Creating Competitive Products

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  1. Creating Competitive Products Qian Wan[1], Raymond Chi-Wing Wong[1], Ihab F. Ilyas[2], M. Tamer Ozsu[2], Yu Peng[1] [1] Hong Kong University of Science and Technology [2] University of Waterloo Presented by Qian Wan Prepared by Qian Wan

  2. Outline • Background • Skyline, Related Work • Motivation • Example,Problem Definition • Algorithm • Framework, Grouping, Pruning • Experiments • Synthetic, Real data • 6 factors, 4 measurements • Conclusions Creating Competitive Products | VLDB '09

  3. Skyline • Definition • Skyline contains the points which are not dominated by others • Hotel searching problem • Distance to beach VS Price • Dominance • Skyline H1 H2 Dist Dist H3 H4 H6 H5 H7 H8 H2 H9 H1 Price Price Creating Competitive Products | VLDB '09

  4. Related Work • Skyline Queries in DBMS [S.Borzsonyi, 2001] • Single Table Skyline Queries • Bitmaps[K.L. Tan,2001], Nearest Neighbor[D.Kossomann, 2002], Branch and Bound Skylines[D.Papadias, 2005] • Multi-Table Skyline Queries • Natural Join [W.Jin, 2007][D.Sun, 2008] • Our Work • Join different source tables via a “Cartesian product” like procedure. Creating Competitive Products | VLDB '09

  5. Outline • Background • Skyline, Related Work • Motivation • Example,Problem Definition • Algorithm • Framework, Grouping, Pruning • Experiments • Synthetic, Real data • 6 factors, 4 measurements • Conclusions Creating Competitive Products | VLDB '09

  6. A Travel Agency’s Database Existing Vacation Packages Newly Created Vacation Packages Skyline tuples Direct attributes Indirect attributes One indirect attribute characteristic e.g. Travel Agency (Price), PC Manufacture(Price) Source Tables Creating Competitive Products | VLDB '09

  7. Finding Competitive Products • Given a set of source tables • Market packages • New packages • Then, a tuple q in TQ is said to be competitive product if q is in Skyline with respect to Creating Competitive Products | VLDB '09

  8. Naïve Solution Intra-dominance checking Inter-dominance checking Existing Vacation Packages Newly Created Vacation Packages Competitive Products Creating Competitive Products | VLDB '09 Source Tables

  9. Outline • Background • Skyline, Related Work • Motivation • Example,Problem Definition • Algorithm • Framework, Grouping, Pruning • Experiments • Synthetic, Real data • 6 factors, 4 measurements • Conclusions Creating Competitive Products | VLDB '09

  10. Algorithm Overview • Intra-dominance checking • To Find Skyline in Source Tables • Inter-dominance checking • Skyline in Existing Market Packages • R* Tree Indies in Existing Market Packages • Full Pruning • Partial Pruning • Post-processing Creating Competitive Products | VLDB '09

  11. Intra-dominance Checking NO intra-dominance checking (one indirect attribute) NO competitive products are missed Conceptual Competitive Products Newly Created Vacation Packages (conceptual) Skyline Tuples of Source Tables Creating Competitive Products | VLDB '09

  12. Algorithm Overview • Intra-dominance checking (Framework) • To Find Skyline in Source Tables • Inter-dominance checking • Skyline in Existing Market Packages • R* Tree Indies in Existing Market Packages • Full Pruning • Partial Pruning • Post-processing Creating Competitive Products | VLDB '09

  13. Inter-dominance Checking Inter-dominance Checking  Range query Existing Vacation Packages Skyline in Existing Vacation Packages Spatial Index No Competitive Products are missed R* Tree will speedup the inter-dominance checking Creating Competitive Products | VLDB '09

  14. Algorithm Overview • Intra-dominance checking (Framework) • To Find Skyline in Source Tables • Inter-dominance checking • Skyline in Existing Market Packages • R* Tree Indies in Existing Market Packages • Full Pruning • Partial Pruning • Post-processing Creating Competitive Products | VLDB '09

  15. Full Pruning Full Pruning Existing Vacation Packages A1 C1={A1, B1} A2 C4={A2, B2} B1 B2 Newly Created Vacation Packages (Conceptual) Skyline Tuples of Source Tables Competitive Products Creating Competitive Products | VLDB '09

  16. Full Pruning Best Representative Quality of Best Representative(tightness of each group): (Clustering, e.g. KMeans) Creating Competitive Products | VLDB '09

  17. Algorithm Overview • Intra-dominance checking (Framework) • To Find Skyline in Source Tables • Inter-dominance checking • Skyline in Existing Market Packages • R* Tree Indies in Existing Market Packages • Full Pruning • Partial Pruning • Post-processing Creating Competitive Products | VLDB '09

  18. Partial Pruning • Full pruning prunes all members in the group • Partial pruning prunes some members in the group • Direct attribute does not change • Estimate the best possible value for indirect attributes • Using tuples in TE’ to conduct Range Query in each Source Table • Eliminate dominated combinations, if • They are dominated on all direct attributes • They are dominated on all indirect attributes according to their best estimation • Partial pruning is used when full pruning cannot be applied Creating Competitive Products | VLDB '09

  19. Partial Pruning Full Pruning Existing Vacation Packages C1={A1, B1} A1 B1 Newly Created Vacation Packages Skyline Tuples of Source Tables Competitive Products Creating Competitive Products | VLDB '09

  20. Meta Transformation A1 B1 Meta-Flight Meta-Hotel • No inter-dominance checking for {F2} X{H2} Creating Competitive Products | VLDB '09

  21. Algorithm Overview • Framework • Intra-dominance checking • To Find Skyline in Source Tables • Inter-dominance checking • Skyline in Existing Market Packages • R* Tree Indies in Existing Market Packages • Full Pruning • Partial Pruning • Post-processing Creating Competitive Products | VLDB '09

  22. Post-processing • More than one indirect attributes • Calculation • Previous algorithm  Intra-dominance checking • Any existing Skyline algorithm • Post-processing cost depends on the size of Competitive Products Creating Competitive Products | VLDB '09

  23. Outline • Background • Skyline, Related Work • Motivation • Example,Problem Definition • Algorithm • Framework, Grouping, Pruning • Experiments • Synthetic, Real data • 6 factors, 4 measurements • Conclusions Creating Competitive Products | VLDB '09

  24. Experiments • Pentium IV 2.4GHz PC with 4GB memory, Linux platform, C++ • Synthetic anti-correlated datasets • Real datasets, Travel Agency A and Travel Agency B • A, 296 packages, 1014 hotels and 4394 flights • B, 149 packages, 995 hotels and 866 flights • Implementation • Algorithm for Creating Competitive Products (ACCP) • Baseline algorithm • Naïve algorithm Creating Competitive Products | VLDB '09

  25. Synthetic Datasets • Schema is similar to our example • Anti-correlated • 6 factors • Measurement • Execution time • Pruning Power • Ratio of Competitive Products out of all combinations • Memory Usage Creating Competitive Products | VLDB '09

  26. Experiments TQ, TQ’, TR SKY From 100k to 500k Full pruning & partial pruning Pruning Power slightly increases Creating Competitive Products | VLDB '09

  27. Experiments From 2.5M to 10M More competitive Slightly decreases Creating Competitive Products | VLDB '09

  28. Experiments DOM SKY • A, 296 packages, 1014 hotels and 4394 flights . B, 149 packages, 995 hotels and 866 flights • Source tables from B, and Package from A • Vary discount from 0 to 0.50 • Efficiency • ACCP(44.74s) and Baseline (84.47s) • |SKY|/|TQ| • |DOM|/|TE| Travel Agency A Package Generation Set Creating Competitive Products | VLDB '09

  29. Outline • Background • Skyline, Related Work • Motivation • Example,Problem Definition • Algorithm • Framework, Grouping, Pruning • Experiments • Synthetic, Real data • 6 factors, 4 measurements • Conclusions Creating Competitive Products | VLDB '09

  30. Conclusions • Creating Competitive Products • Example • Problem Definition • Algorithms • Framework • Intra-dominance checking • Inter-dominance checking • Post-processing • Experiments • Synthetic anti-correlated datasets • Real datasets Creating Competitive Products | VLDB '09

  31. Q&A Thank You ! Creating Competitive Products | VLDB '09

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