Run-time Optimization for Pipelined Systems

R. Abdel Kader, Maurice van Keulen, Peter Boncz, Stefan Manegold

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Traditional optimizers fail to pick good execution plans, when faced with increasingly complex queries and large data sets. This failure is even more acute in the context of XQuery, due to the structured nature of the XML language. To overcome the vulnerabilities of traditional optimizers, we have previously proposed ROX, a Run-time Optimizer for XQueries, which interleaves optimization and execution of full tables. ROX has proved to be robust, even in the presence of strong correlations, but it has one limitation: it uses full materialization of intermediate results making it unsuitable for pipelined systems. Therefore, this paper proposes ROX-sampled, a variant of ROX, which executes small data samples, thus generating smaller intermediates. We conduct extensive experiments which proved that ROX-sampled is comparable to ROX in performance, and that it is still robust against correlations. The main benefit of ROX-sampled is that it allows the large number of pipelined databases to import the ROX idea into their optimization paradigm.
Original languageUndefined
Title of host publicationProceedings of the IV Alberto Mendelzon Workshop on Foundations of Data Management (AMW2010)
Place of PublicationAachen, Germany
Number of pages12
Publication statusPublished - 19 May 2010

Publication series

NameCEUR Workshop Proceedings
ISSN (Print)1613-0073


  • IR-70842
  • EWI-17779
  • METIS-270783

Cite this

Abdel Kader, R., van Keulen, M., Boncz, P., & Manegold, S. (2010). Run-time Optimization for Pipelined Systems. In Proceedings of the IV Alberto Mendelzon Workshop on Foundations of Data Management (AMW2010) (pp. 15.1-15.12). (CEUR Workshop Proceedings; Vol. 619). Aachen, Germany: CEUR.