Query optimization over cloud data market

Yu Li, Eric Lo, Man Lung Yiu, Wenjian Xu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

7 Citations (Scopus)

Abstract

Data market is an emerging type of cloud service that enables a data owner to sell their data sets in a public cloud. Buyers who are interested in a certain dataset can access the data in the market via a RESTful API. Accessing data in the data market may not be free. For example, it costs USD 12 per month to obtain 100 "transactions" from the WorldWide Historical Weather dataset in Windows Azure Data Marketplace, where a transaction is a unit of result size (e.g., a query result of 4400 records would consume 44 transactions as Windows Azure Data Marketplace confines one transaction to 100 records). Therefore, in this paper, we present PayLess, a system that helps data buyers to optimize their queries so that they can obtain the query results by paying less to the data sellers. Experiments over synthetic data and real data sets in Windows Azure Marketplace show that PayLess can cost-effectively handle SQL query processing over data markets.
Original languageEnglish
Title of host publicationEDBT 2015 - 18th International Conference on Extending Database Technology, Proceedings
PublisherOpenProceedings.org, University of Konstanz, University Library
Pages229-240
Number of pages12
ISBN (Electronic)9783893180677
DOIs
Publication statusPublished - 1 Jan 2015
Event18th International Conference on Extending Database Technology, EDBT 2015 - Brussels, Belgium
Duration: 23 Mar 201527 Mar 2015

Conference

Conference18th International Conference on Extending Database Technology, EDBT 2015
CountryBelgium
CityBrussels
Period23/03/1527/03/15

ASJC Scopus subject areas

  • Information Systems
  • Software

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