Maximal Vector Computation in Large Data Sets Parke Godfrey 1 Ryan - PowerPoint PPT Presentation

Maximal Vector Computation in Large Data Sets Parke Godfrey 1 Ryan Shipley 2 Jarek Gryz 1 1 York University 2 College of William and Mary Toronto, C ANADA Williamsburg, USA 30 August 2005 VLDB Trondheim, Norway Maximal Vector—Godfrey, Shipley, & Gryz – p. 1/29

I. Introduction What is Skyline? • an extension to select . . . SQL from . . . where . . . • filtering for the group by . . . Pareto-optimal skyline of D 1 [min | max | diff], . . . , tuples D k [min | Max | diff] • a way to express having . . . “best-match” & preference queries [Börzsönyi, Kossmann, & Stocker 2001 (ICDE)] Maximal Vector—Godfrey, Shipley, & Gryz – p. 2/29

I. Introduction What is Skyline? • an extension to select . . . SQL from . . . where . . . • filtering for the group by . . . Pareto-optimal skyline of D 1 [min | max | diff], . . . , tuples D k [min | Max | diff] • a way to express having . . . “best-match” & preference queries [Börzsönyi, Kossmann, & Stocker 2001 (ICDE)] • Have been ∼ 30 skyline-related papers in DB-related journals, conferences, & workshops since. • Next two talks are on skyline, & one at PhD Workshop. Maximal Vector—Godfrey, Shipley, & Gryz – p. 2/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . select name, address from Hotel skyline of stars max, dist min, price min Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 ⋆⋆ 0 . 5 Uma 980 Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29

A Skyline Example Consider a Hotel table with columns name , address , dist (distance to the beach), stars (quality rating), & price . name stars dist price select name, address from Hotel ⋆⋆ 0 . 7 Aga 1,175 skyline of stars max, ⋆ 1 . 2 Fol 1,237 dist min, ⋆ 0 . 2 Kaz 750 price min ⋆ ⋆ ⋆ 0 . 2 Neo 2,250 X currently considering ⋆ ⋆ ⋆ 0 . 5 Tor 2,550 X “trumps” current ⋆⋆ 0 . 5 Uma 980 X skyline X not skyline Maximal Vector—Godfrey, Shipley, & Gryz – p. 3/29