Synonyms
Top-k Query Processing
Definition
Rank-aware query processing refers to the efficient processing of a top-k query taking into account the ranking requirements on output results. A naïve way to process a top-k query is to calculate the full set of results and then sort them based on the ranking function; the top-k results are presented as the final query answers. Such a naïve materialize-then-sort scheme can be prohibitively expensive. Integrating top-k queries in SQL query engines requires addressing the challenge of making an RDBMS rank-aware. This requires introducing new constructs in the whole system including the data model, algebra, query operators, and query optimization techniques.
Historical Background
The need for rank-aware query processing arose since the introduction of top-k queries with score aggregation and rank joins to the database community. Fagin et al. [1] first introduced the problem of ranking a database of objects, given several rankings of the...
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Fagin R. Combining fuzzy information: an overview. ACM SIGMOD Rec. 2002;31(2):109–18.
Fagin R, Lotem A, Naor M. Optimal aggregation algorithms for middleware. J Comput Syst Sci. 2003;66(4):614–56.
Finger J, Polyzotis N. Robust and efficient algorithms for rank join evaluation. In: Proceedings of the 2009 ACM SIGMOD International Conference on Management of Data; 2009. p. 415–28.
Ilyas IF, Aref WG, Elmagarmid AK. Joining ranked inputs in practice. In: Proceedings of the 28th International Conference on Very Large Data Bases; 2002. p. 950–61.
Ilyas IF, Aref WG, Elmagarmid AK. Supporting top-k join queries in relational databases. VLDB J – Int J Very Large Data Bases. 2004;13(3):207–21.
Li C, Chang KC-C, Ilyas IF, Song S. Ranksql: query algebra and optimization for relational top-k queries. In: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data; 2005. p. 131–42.
Li C, Soliman MA, Chang KC-C, Ilyas IF. Ranksql: supporting ranking queries in relational database management systems. In: Proceedings of the 31st International Conference on Very Large Data Bases; 2005. p. 1342–45.
Natsev A, chi Chang Y, Smith JR, Li C-S, Vitter JS. Supporting incremental join queries on ranked inputs. In: Proceedings of the 27th International Conference on Very Large Data Bases; 2001.
Roth MT, Arya M, Haas LM, Carey MJ, Cody W, Fagin R, Schwarz PM, Thomas J, Wimmers EL. The garlic project. Sigmod Rec. 1996;25(2):557.
Schnaitter K, Polyzotis N. Evaluating rank joins with optimal cost. In: Proceedings of the 27th ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems; 2008. p. 43–52.
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Ilyas, I.F. (2018). Rank-Aware Query Processing. In: Liu, L., Özsu, M.T. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-8265-9_80680
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DOI: https://doi.org/10.1007/978-1-4614-8265-9_80680
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