## Refreshing the sky: the compressed skycube with efficient support for frequent updates (2006)

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Venue: | In SIGMOD |

Citations: | 34 - 0 self |

### BibTeX

@INPROCEEDINGS{Xia06refreshingthe,

author = {Tian Xia},

title = {Refreshing the sky: the compressed skycube with efficient support for frequent updates},

booktitle = {In SIGMOD},

year = {2006},

pages = {491--502}

}

### Years of Citing Articles

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### Abstract

The skyline query is important in many applications such as multi-criteria decision making, data mining, and userpreference queries. Given a set of d-dimensional objects, the skyline query finds the objects that are not dominated by others. In practice, different users may be interested in different dimensions of the data, and issue queries on any subset of d dimensions. This paper focuses on supporting concurrent and unpredictable subspace skyline queries in frequent updated databases. Simply to compute and store the skyline objects of every subspace in a skycube will incur expensive update cost. In this paper, we investigate the important issue of updating the skycube in a dynamic environment. To balance the query cost and update cost, we propose a new structure, the compressed skycube, which concisely represents the complete skycube. We thoroughly explore the properties of the compressed skycube and provide an efficient object-aware update scheme. Experimental results show that the compressed skycube is both query and update efficient. 1.

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Citation Context ...skyline is called the Pareto set, and the skyline objects are called admissible points [4] or maximal vectors [6]. The corresponding problem in the theory field is known as the maximal vector problem =-=[14, 18]-=-. Several main-memory algorithms [14, 6, 5] have been proposed to solve the maximal vector problem. However, in the database context, those main-memory algorithms are inefficient for the skyline query... |

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Citation Context ...Boston, MA 02115 Donghui Zhang ∗ donghui@ccs.neu.edu Price t3 1 t4 t6 t t2 t5 t8 t7 Distance to the beach Figure 1: A classic example of the skyline query. Since it was introduced by Börzsönyi et al. =-=[7]-=-, the skyline query has attracted considerable attention, largely due to its importance in multi-criteria decision making, data mining [12], and user-preference queries [11]. Traditional skyline compu... |

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Citation Context ...aces of users’ interests are unpredictable, Yuan et al. [21] proposed the concept of Skycube, which is the complete computation of all possible subspace skylines. Similar to the idea of the data cube =-=[1]-=- in the data warehouse, the skycube consists of the skylines of all possible subspaces. [21] provided bottom-up and topdown methods for the initial computation of skycube. However, the previous work o... |

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Citation Context ...kyline query has attracted considerable attention, largely due to its importance in multi-criteria decision making, data mining [12], and user-preference queries [11]. Traditional skyline computation =-=[2, 3, 8, 9, 10, 13, 15, 16, 19]-=- is restricted to a fixed set of dimensions that are interesting to the skyline queries. Based on the a-priori information, indices can be used or data can be pre-sorted on the query dimensions to exp... |

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Citation Context ...skyline is called the Pareto set, and the skyline objects are called admissible points [4] or maximal vectors [6]. The corresponding problem in the theory field is known as the maximal vector problem =-=[14, 18]-=-. Several main-memory algorithms [14, 6, 5] have been proposed to solve the maximal vector problem. However, in the database context, those main-memory algorithms are inefficient for the skyline query... |

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Citation Context ...kyline query has attracted considerable attention, largely due to its importance in multi-criteria decision making, data mining [12], and user-preference queries [11]. Traditional skyline computation =-=[2, 3, 8, 9, 10, 13, 15, 16, 19]-=- is restricted to a fixed set of dimensions that are interesting to the skyline queries. Based on the a-priori information, indices can be used or data can be pre-sorted on the query dimensions to exp... |

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Citation Context ...kyline query has attracted considerable attention, largely due to its importance in multi-criteria decision making, data mining [12], and user-preference queries [11]. Traditional skyline computation =-=[2, 3, 8, 9, 10, 13, 15, 16, 19]-=- is restricted to a fixed set of dimensions that are interesting to the skyline queries. Based on the a-priori information, indices can be used or data can be pre-sorted on the query dimensions to exp... |

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Citation Context ...roduced by Börzsönyi et al. [7], the skyline query has attracted considerable attention, largely due to its importance in multi-criteria decision making, data mining [12], and user-preference queries =-=[11]-=-. Traditional skyline computation [2, 3, 8, 9, 10, 13, 15, 16, 19] is restricted to a fixed set of dimensions that are interesting to the skyline queries. Based on the a-priori information, indices ca... |

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Citation Context ...LATED WORK The skyline query can be traced back from 1960s in the theory field, where the skyline is called the Pareto set, and the skyline objects are called admissible points [4] or maximal vectors =-=[6]-=-. The corresponding problem in the theory field is known as the maximal vector problem [14, 18]. Several main-memory algorithms [14, 6, 5] have been proposed to solve the maximal vector problem. Howev... |

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Citation Context |

68 | Catching the Best Views of Skyline: A Semantic Approach Based on Decisive Subspaces
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Citation Context ...t are interesting to the skyline queries. Based on the a-priori information, indices can be used or data can be pre-sorted on the query dimensions to expedite the query processing. Recently, research =-=[17, 21, 20]-=- on the skyline query has shifted to the subspace skyline computation, which do not assume the knowledge of the query dimensions. Given a set of objects with d dimensions, different users may be inter... |

56 | Stratified computation of skylines with partially-ordered domains
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42 |
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Citation Context ... skyline objects are called admissible points [4] or maximal vectors [6]. The corresponding problem in the theory field is known as the maximal vector problem [14, 18]. Several main-memory algorithms =-=[14, 6, 5]-=- have been proposed to solve the maximal vector problem. However, in the database context, those main-memory algorithms are inefficient for the skyline query, due to the large sizes of data sets. In S... |

38 |
On the distribution of the number of admissible points in a vector random sample, Theory of Probability and its
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(Show Context)
Citation Context ...ludes this paper. 2. RELATED WORK The skyline query can be traced back from 1960s in the theory field, where the skyline is called the Pareto set, and the skyline objects are called admissible points =-=[4]-=- or maximal vectors [6]. The corresponding problem in the theory field is known as the maximal vector problem [14, 18]. Several main-memory algorithms [14, 6, 5] have been proposed to solve the maxima... |

16 | Mining thick skylines over large databases
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(Show Context)
Citation Context ...he skyline query. Since it was introduced by Börzsönyi et al. [7], the skyline query has attracted considerable attention, largely due to its importance in multi-criteria decision making, data mining =-=[12]-=-, and user-preference queries [11]. Traditional skyline computation [2, 3, 8, 9, 10, 13, 15, 16, 19] is restricted to a fixed set of dimensions that are interesting to the skyline queries. Based on th... |