Running time prediction for web search queries

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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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Rojas, O., Gil-Costa, V., & Marin, M. (2016). Running time prediction for web search queries. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9574, pp. 210–220). Springer Verlag. https://doi.org/10.1007/978-3-319-32152-3_20

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