skip to main content
10.1145/2661829.2661891acmconferencesArticle/Chapter ViewAbstractPublication PagescikmConference Proceedingsconference-collections
poster

Hashcube: A Data Structure for Space- and Query-Efficient Skycube Compression

Published: 03 November 2014 Publication History

Abstract

The skyline operator returns records in a dataset that provide optimal trade-offs of multiple dimensions. It is an expensive operator whose query performance can greatly benefit from materialization. However, a skyline can be executed over any subspace of dimensions, and the materialization of all subspace skylines, called the skycube, dramatically multiplies data size. Existing methods for skycube compression sacrifice too much query performance; so, we present a novel hashing- and bitstring-based compressed data structure that supports orders of magnitude faster query performance.

References

[1]
S. Börzsönyi et al. The skyline operator. In Proc. ICDE, pages 421--430, 2001.
[2]
S. Chester et al. On the suitability of skyline queries for data exploration. In Proc. ExploreDB, pages 6:1--6, 2014.
[3]
J. Chomicki et al. Skyline with presorting. In Proc. ICDE, pages 717--719, 2003.
[4]
J. Lee and S.-w. Hwang. Scalable skyline computation using a balanced pivot selection technique. Inf. Syst., 39:1--24, 2014.
[5]
J. Lee and S.-w. Hwang. Toward efficient multidimensional subspace skyline computation. VLDB J, 23(1):129--145, 2014.
[6]
J. Pei et al. Catching the best views of the skyline: a semantic approach based on decisive subspaces. In Proc. VLDB, pages 253--264, 2005.
[7]
J. Pei et al. Towards multidimensional subspace skyline analysis. TODS, 31(4):1335--1381, 2006.
[8]
C. Raïssi et al. Computing closed skycubes. PVLDB, 3(1):838--847, 2010.
[9]
A. Vlachou et al. Skypeer: Efficient subspace skyline computation over distributed data. In Proc. ICDE, pages 416--425, 2007.
[10]
T. Xia et al. Online subspace skyline query processing using the compressed skycube. TODS, 37(2), 2012.
[11]
Y. Yuan et al. Efficient computation of the skyline cube. In Proc. VLDB, pages 241--252, 2005.
[12]
S. Zhang et al. Scalable skyline computation using object-based space partitioning. In Proc. SIGMOD, pages 483--494, 2009.

Cited By

View all
  • (2024)Efficient Skyline Keyword-Based Tree Retrieval on Attributed GraphsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.338898836:11(6056-6070)Online publication date: 1-Nov-2024
  • (2020)Accelerating Skycube Computation with Partial and Parallel Processing for Service SelectionIEEE Transactions on Services Computing10.1109/TSC.2017.276268113:6(969-984)Online publication date: 1-Nov-2020
  • (2020)The negative skycubeInformation Systems10.1016/j.is.2019.10144388:COnline publication date: 1-Feb-2020
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge Management
November 2014
2152 pages
ISBN:9781450325981
DOI:10.1145/2661829
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 November 2014

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. compression
  2. data structure
  3. hashmap
  4. skycube

Qualifiers

  • Poster

Funding Sources

Conference

CIKM '14
Sponsor:

Acceptance Rates

CIKM '14 Paper Acceptance Rate 175 of 838 submissions, 21%;
Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

Upcoming Conference

CIKM '25

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)1
  • Downloads (Last 6 weeks)0
Reflects downloads up to 06 Jan 2025

Other Metrics

Citations

Cited By

View all
  • (2024)Efficient Skyline Keyword-Based Tree Retrieval on Attributed GraphsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2024.338898836:11(6056-6070)Online publication date: 1-Nov-2024
  • (2020)Accelerating Skycube Computation with Partial and Parallel Processing for Service SelectionIEEE Transactions on Services Computing10.1109/TSC.2017.276268113:6(969-984)Online publication date: 1-Nov-2020
  • (2020)The negative skycubeInformation Systems10.1016/j.is.2019.10144388:COnline publication date: 1-Feb-2020
  • (2020)A framework for multidimensional skyline queries over streaming dataData & Knowledge Engineering10.1016/j.datak.2020.101792127(101792)Online publication date: May-2020
  • (2019)Compressing and Querying Skypattern CubesAdvances and Trends in Artificial Intelligence. From Theory to Practice10.1007/978-3-030-22999-3_36(406-421)Online publication date: 9-Jul-2019
  • (2017)Template Skycube Algorithms for Heterogeneous Parallelism on Multicore and GPU ArchitecturesProceedings of the 2017 ACM International Conference on Management of Data10.1145/3035918.3035962(447-462)Online publication date: 9-May-2017
  • (2016)Computing and Summarizing the Negative SkycubeProceedings of the 25th ACM International on Conference on Information and Knowledge Management10.1145/2983323.2983759(1733-1742)Online publication date: 24-Oct-2016
  • (2016)Skycube Materialization Using the Topmost Skyline or Functional DependenciesACM Transactions on Database Systems10.1145/295509241:4(1-40)Online publication date: 2-Nov-2016
  • (2015)Efficient continuous skyline computation on multi-core processors based on Manhattan distanceProceedings of the 2015 ACM/IEEE International Conference on Formal Methods and Models for Codesign10.1109/MEMCOD.2015.7340469(56-59)Online publication date: 1-Sep-2015

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media