Abstract
High-level queries can be used for describing scenarios of complicated analytical processing in environments of distributed heterogeneous information resources. Simultaneous abrupt increase in volume and variety of data types available for mass processing in information networks and toughening of requirements on time spent for analyzing them resulted in the need of revising the known query execution and optimization methods. In this survey, approaches to the execution and optimization of high-level precise and approximate queries are considered; unresolved problems and possible ways to solve them are also discussed.
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Gray, J., The next database revolution, Proceedings of the ACM SIGMOD Int. Conf. on Management of Data (Paris, 2004), Weikum, G., König, A.C., and Deßloch, S., Eds., ACM, 2004, pp. 1–4.
Graefe, G., Query evaluation techniques for large databases, ACM Comput. Surv., 1993, vol. 25, no. 2, pp. 73–170.
Codd, E.F., A relational model of data for large shared data banks, Commun. ACM, 1970, vol. 13, no. 6, pp. 377–387.
Darwen, H. and Date, C.J., The third manifesto, SIGMOD Record, 1995, vol. 24, no. 1, pp. 39–49.
Ioannidis, Y.E., Query optimization, ACM Comput. Surv., 1996, vol. 28, no. 1, pp. 121–123.
Steinbrunn, M., Moerkotte, G., and Kemper, A., Heuristic and randomized optimization for the join ordering problem, VLDBJ, 1997, vol. 6, no. 3, pp. 191–208.
Ioannidis, Y.E., The history of histograms (abridged), VLDB, 2003, pp. 19–30.
Kossmann, D. and Stocker, K., Iterative dynamic programming: a new class of query optimization algorithms, ACM Trans. Database Syst., 2000, vol. 25, no. 1, pp. 43–82.
Chaudhuri, S., Ramakrishnan, R., and Weikum, G., Integrating db and ir technologies: What is the sound of one hand clapping, CIDR, 2005, pp. 1–12.
Adali, S., Bonatti, P., Sapino, M.L., and Subrahmanian, V.S., A multi-similarity algebra, Proc. of the 1998 ACM SIGMOD Int. Conf. on management of data, SIGMOD’98, 1998, pp. 402–413, New York, 1998.
Montesi, D., Trombettam, A., and Dearnley, P.A., A similarity based relational algebra for web and multimedia data, Inf. Process. Manag., 2003, vol. 39, no. 2, pp. 307–322.
Ciaccia, P., Montesi, D., Penzo, W., and Trombettam, A., Imprecision and user preferences in multimedia queries: A generic algebraic approach, Proc. of the-First Int. Symposium on Foundations of Information and Knowledge Systems, FoIKS’00, London, 2000, pp. 50–71.
Schmitt, I. and Schulz, N., Similarity relational calculus and its reduction to a similarity algebra, Lecture Notes in Computer Science, 2004, vol. 2942, pp. 252–272.
Atnafu, S., Brunie, L., and Kosch, H., Similarity-based algebra for multimedia database systems, Proc of ADC, 2001, pp. 115–122.
Budíková, P., Batko, M., and Zezula, P., Query language for complex similarity queries, Lecture Notes in Computer Science, 2012, vol. 7503, pp. 85–98.
Li, C., Chen-Chuan Chang, K., Ilyas, I.F., and Song, S., Ranksql: Query algebra and optimization for relational top-k queries, Proc. of SIGMOD Conf., 2005, pp. 131–142.
Fagin, R., Fuzzy queries in multimedia database systems. Proc. of the seventeenth ACM SIGACT-SIGMODSIGART Symposium on Principles of database systems, PODS’98, New York, 1998, pp. 1–10.
Fagin, R. and Wimmers, E.L., A formula for incorporating weights into scoring rules, Theor. Comput. Sci., 2000, vol. 239, no. 2, pp. 309–338.
Hu, Y., Sundara, S., and Srinivasan, J., Supporting time-constrained sql queries in Oracle, Proc. of the 33d Int. Conf. on Very Large Data Bases, VLDB’07, Endowment, 2007, pp. 1207–1218.
Babcock, B., Chaudhuri, S., and Das, G., Dynamic sample selection for approximate query processing, Proc. of the 2003 ACM SIGMOD Int. Conf. on Management of Data, SIGMOD’03, New York, 2003, pp. 539–550.
Dell’Aquila, C., DiTria, F., Lefons, E., and Tangorra, F., Accuracy estimation in approximate query processing, Proc. of the 14th WSEAS Int. Conf. on Computers: Part of the 14th WSEAS CSCC Multiconference, ICCOMP’10, Stevens Point, Wisconsin, 2010, vol. II, pp. 452–458.
Chaudhuri, S., Das, G., and Narasayya, V., Optimized stratified sampling for approximate query processing, ACM Trans. Database Syst., 2007, vol. 32.
Jermaine, C., Arumugam, S., Pol, A., and Dobra, A., Scalable approximate query processing with the dbo engine, ACM Trans. Database Syst., 2008, vol. 33, pp. 1–23.
Fagin, R., Lotem, A., and Naor, M., Optimal aggregation algorithms for middleware, J. Comput. Syst. Sci., 2003, vol. 66, no. 4, pp. 614–656.
Theobald, M., Weikum, G., and Schenkel, R., Top-k query evaluation with probabilistic guarantees, VLDB, Nascimento, M.A., Ozsu, M.T., Kossmann, D., Miller, R.J., Blakeley, J.A., and Schiefer, K.B., Eds., Morgan Kaufmann, 2004, pp. 648–659.
Arai, B., Das, G., Gunopulos, D., and Koudas, N., Anytime measures for top-k algorithms, VLDB, Koch, C., Gehrke, J., Garofalakis, M.N., Srivastava, D., Aberer, K., Deshpande, A., Florescu, D., Chan, C.Y., Ganti, V., Kanne, C.-C., Klas, W., and Neuhold, E.J., Eds., ACM, 2007, pp. 914–925.
Braga, D., Campi, A., Ceri, S., and Raffio, A., Joining the results of heterogeneous search engines, Inf. Syst., 2008., vol. 33, nos. 7–8, pp. 658–680.
Deshpande, A., Ives, Z.G., and Raman, V., Adaptive query processing, Foundations Trends Databases, 2007, vol. 1, no. 1, pp. 1–140.
Babu, S., Bizarro, P., and DeWitt, D., Proactive reoptimization, Proc. of the 2005 ACM SIGMOD Int. Conf. on Management of Data, SIGMOD’05, New York, 2005, pp. 107–118.
Eurviriyanukul, K., Paton, N.W., Fernandes, A.A.A., and Lynden, S.J., Adaptive join processing in pipelined plans, Proc. of the 13th Int. Conf. on Extending Database Technology, EDBT’10, New York, 2010, pp. 183–194.
Markl, V., Raman, V., Simmen, D., Lohman, G., Pirahesh, H., and Cilimdzic, M., Robust query processing through progressive optimization, Proc. of the 2004 ACM SIGMOD Int. Conf. on Management of data, SIGMOD’04, New York, 2004, pp. 659–670.
Graefe, G., New algorithms for join and grouping operations, Comput. Sci., 2012, vol. 27, no. 1, pp. 3–27.
Lengu, R., Missier, P., Fernandes, A.A.A., Guerrini, G., and Mesiti, M., Time-completeness trade-offs in record linkage using adaptive query processing, Proceedings of the 12th Int. Conf. on Extending Database Technology, EDBT2009 (Saint Petersburg, 2009), Kersten, M.L., Novikov, B., Teubner, J., Polutin, V., and Manegold, S., Eds., ACM, 2009, pp. 851–861.
Ilyas, I.F., Aref, W.G., Elmagarmid, A.K., Elmongui, H.G., Shah, R., and Vitter, J.S., Adaptive rankaware query optimization in relational databases, ACM Trans. Database Syst., 2006, vol. 31, no. 4, pp. 1257–1304.
Farag, F., Hammad, M.A., and Alhajj, R., Adaptive query processing in data stream management systems under limited memory resources, PIKM, Nica, A. and Varde, A.S., Eds., ACM, 2010, pp. 9–16.
Proceedings of the 12th Int. Conf. on Extending Database Technology, EDBT2009 (Saint Petersburg, 2009), Kersten, M.L., Novikov, B., Teubner, J., Polutin, V., and Manegold, S., Eds., ACM, 2009.
Ilyas, I.F., Shah, R., Aref, W.G., Vitter, J.S., and Elmagarmid, A.K., Rank-aware query optimization, Proceedings of the ACM SIGMOD Int. Conf. on Management of Data (Paris, 2004), Weikum, G., König, A.C., and Deßloch, S., Eds., ACM, 2004, pp. 203–214.
Proceedings of the ACM SIGMOD Int. Conf. on Management of Data (Paris, 2004), Weikum, G., König, A.C., and Deßloch, S., Eds., ACM, 2004.
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Original Russian Text © A. Yarygina, 2013, published in Programmirovanie, 2013, Vol. 39, No. 6.
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Yarygina, A. Execution and optimization techniques for approximate queries in heterogeneous systems. Program Comput Soft 39, 309–317 (2013). https://doi.org/10.1134/S0361768813060066
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DOI: https://doi.org/10.1134/S0361768813060066