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Multi-Step Query Processing

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Filter/refinement query processing

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A query on a database reports those objects which fulfill a given query predicate. A query processor has to evaluate the query predicate for each object in the database which is a candidate for the result set. Multi-step query processing (filter/refinement query processing) is a technique to speed up queries specifying query predicates that are complex and costly to evaluate. The idea is to save the costs of the evaluation of the complex query predicate by reducing the candidate set for which the query predicate has to be evaluated applying one or more filter steps. The aim of each filter step is to identify as many true hits (objects that truly fulfill the complex query predicate) and as many true drops (objects that truly do not fulfill the query predicate) as possible by applying a less costly query predicate. The remaining candidates that are not pruned as drops or reported as hits in one of the filter steps need to be tested...

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Recommended Reading

  1. Agrawal R., Faloutsos C., and Swami A. Efficient similarity search in sequence databases. In Proc. 4th Int. Conf. on Foundations of Data Organization and Algorithms, 1993, pp. 69–80.

    Google Scholar 

  2. Brinkhoff T., Horn H., Kriegel H.-P., and Schneider R. A storage and access architecture for efficient query processing in spatial database systems. In Proc. 3rd Int. Symp. Advances in Spatial Databases, 1993, pp. 357–376.

    Google Scholar 

  3. Faloutsos C., Ranganathan M., and Manolopoulos Y. Fast subsequence matching in time series database. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1994, pp.419.

    Google Scholar 

  4. Korn F., Sidiropoulos N., Faloutsos C., Siegel E., and Protopapas Z. Fast nearest neighbor search in medical image databases. In Proc. 22th Int. Conf. on Very Large Data Bases, 1996, pp. 215–226.

    Google Scholar 

  5. Kriegel H.-P., Kröger P., Kunath P., and Renz M. Generalizing the optimality of multi-step k-nearest neighbor query processing. In Proc. 10th Int. Symp. Advances in Spatial and Temporal Databases, 2007, pp. 75–9.

    Google Scholar 

  6. Orenstein J. and Manola F. Probe spatial data modelling and query processing in an image database application. IEEE Trans. Softw. Eng., 14(5), 1988.

    Google Scholar 

  7. Seidl T. and Kriegel H.-P. Optimal multi-step k-nearest neighbor search. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 1998, pp. 154–16.

    Google Scholar 

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Kröger, P., Renz, M. (2009). Multi-Step Query Processing. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_227

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