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Running Time Prediction for Web Search Queries

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Parallel Processing and Applied Mathematics

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9574))

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Abstract

Large scale Web search engines have to process thousands of queries per second and each query has to be solved within a fraction of a second. To achieve this goal, search engines rely on sophisticated services capable of processing large amounts of data. One of these services is the search service (or index service) which is in charge of computing the top-k document results for user queries. Predicting in advance the response time of queries has practical applications in efficient administration of hardware resources assigned to query processing. In this paper, we propose and evaluate a query running time prediction algorithm that is based on a discrete Fourier transform which models the index as a collection of signals to obtain patterns. Results show that our approach performs at least as effectively as well-known prediction algorithms in the literature, while significantly improving computational efficiency.

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Notes

  1. 1.

    http://www.lemurproject.org/clueweb09.php/.

  2. 2.

    http://terrier.org/.

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Acknowledgments

This research was partially funded by Basal funds FB0001, Conicyt, Chile; PMI USA 1204 and PICT 2014-1146.

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Authors and Affiliations

  1. CITIAPS, DIINF, University of Santiago, Santiago, Chile

    Oscar Rojas, Veronica Gil-Costa & Mauricio Marin

  2. Center for Biotechnology and Bioengineering, Santiago, Chile

    Oscar Rojas, Veronica Gil-Costa & Mauricio Marin

Authors
  1. Oscar Rojas
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  2. Veronica Gil-Costa
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  3. Mauricio Marin
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Corresponding author

Correspondence to Veronica Gil-Costa .

Editor information

Editors and Affiliations

  1. Czestochowa University of Technolog, Czestochowa, Poland

    Roman Wyrzykowski

  2. Department of Computer Science, University of Southern California, Marina Del Rey, California, USA

    Ewa Deelman

  3. Electrical Engineering & Comput. Science, University of Tennessee, Knoxville, Tennessee, USA

    Jack Dongarra

  4. Czestochowa University of Technology, Institute of Computer & Information Sci., Czestochowa, Poland

    Konrad Karczewski

  5. Department of Computer Science, AGH University of Science and Technology, Krakow, Poland

    Jacek Kitowski

  6. Systèmes d’informations, Big Data et Rec, AGH University of Science and Technology, Krakow, Poland

    Kazimierz Wiatr

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© 2016 Springer International Publishing Switzerland

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Rojas, O., Gil-Costa, V., Marin, M. (2016). Running Time Prediction for Web Search Queries. In: Wyrzykowski, R., Deelman, E., Dongarra, J., Karczewski, K., Kitowski, J., Wiatr, K. (eds) Parallel Processing and Applied Mathematics. Lecture Notes in Computer Science(), vol 9574. Springer, Cham. https://doi.org/10.1007/978-3-319-32152-3_20

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  • DOI: https://doi.org/10.1007/978-3-319-32152-3_20

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-32151-6

  • Online ISBN: 978-3-319-32152-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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