Optimized Processing of a Batch of Aggregate Queries over Hidden Databases

Eman Rezk, Aboubakr Aqle, Ali Jaoua, Gautam Das, Nan Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A tremendous amount of data is concealed behind form-based interfaces that communicate any user query to their data store to deliver query answer. These interfaces limit the number of retrieved search results to the top-k matching tuples that are sorted using a proprietary ranking function; the database owner may also impose constraints on the type of the processed queries. These limitations make it difficult to process a batch of queries, in this paper; we tackle the problem of processing a batch of aggregate queries with the minimal number of queries sent to the hidden database to overcome the interface limitations. We are proposing a novel technique that makes use of the results of the fired queries to answer new aggregate queries without any additional cost. The proposed method is compared with the classical techniques of processing aggregate queries; it is evaluated through the estimation relative error and query cost. The results show that our method is more efficient than other methods in terms of query cost, so we can process a batch of queries with the minimal cost.

Original languageEnglish (US)
Title of host publication2017 International Conference on Computer and Applications, ICCA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages317-324
Number of pages8
ISBN (Electronic)9781538627525
DOIs
StatePublished - Oct 20 2017
Event2017 International Conference on Computer and Applications, ICCA 2017 - Doha, United Arab Emirates
Duration: Sep 6 2017Sep 7 2017

Publication series

Name2017 International Conference on Computer and Applications, ICCA 2017

Other

Other2017 International Conference on Computer and Applications, ICCA 2017
CountryUnited Arab Emirates
CityDoha
Period9/6/179/7/17

All Science Journal Classification (ASJC) codes

  • Software
  • Control and Optimization
  • Education
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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  • Cite this

    Rezk, E., Aqle, A., Jaoua, A., Das, G., & Zhang, N. (2017). Optimized Processing of a Batch of Aggregate Queries over Hidden Databases. In 2017 International Conference on Computer and Applications, ICCA 2017 (pp. 317-324). [8079754] (2017 International Conference on Computer and Applications, ICCA 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/COMAPP.2017.8079754