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

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

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
ISBN (print)978-1-4503-2598-1
Publication statusPublished - Nov 2014
EventACM International Conference on Conference on Information and Knowledge Management - Shanghai, China
Duration: 3 Nov 20147 Nov 2014
Conference number: 23


ConferenceACM International Conference on Conference on Information and Knowledge Management

    Research areas

  • skyline, Compression, Data Structures

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