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

Research output: Research - peer-reviewArticle in proceedings

  • Kenneth Sejdenfaden Bøgh
    Kenneth Sejdenfaden BøghDenmark
  • Sean Chester
  • Darius Sidlauskas
    Darius SidlauskasDenmark
  • Ira Assent
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.
Original languageEnglish
Title of host publicationProceedings of The 23rd ACM International Conference on Information and Knowledge Management (CIKM 2014)
EditorsJianzhong Li , X. Sean Wang
Number of pages4
PublisherAssociation for Computing Machinery
Publication yearNov 2014
Pages1767-1770
ISBN (Print)978-1-4503-2598-1
DOIs
StatePublished - Nov 2014
EventACM International Conference on Conference on Information and Knowledge Management - Shanghai, China
Duration: 3 Nov 20147 Nov 2014
Conference number: 23

Conference

ConferenceACM International Conference on Conference on Information and Knowledge Management
Nummer23
LandChina
ByShanghai
Periode03/11/201407/11/2014

    Research areas

  • skyline, Compression, Data Structures

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