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dc.contributor.authorFan, Wenfei-
dc.contributor.authorGEERTS, Floris-
dc.contributor.authorNEVEN, Frank-
dc.identifier.citationProceedings of the VLDB Endowment, 6 (1), p. 685-696-
dc.description.abstractA query class is traditionally considered tractable if there exists a polynomial-time (PTIME) algorithm to answer its queries. When it comes to big data, however, PTIME al- gorithms often become infeasible in practice. A traditional and e ective approach to coping with this is to preprocess data o -line, so that queries in the class can be subsequently evaluated on the data e ciently. This paper aims to pro- vide a formal foundation for this approach in terms of com- putational complexity. (1) We propose a set of -tractable queries, denoted by T0 Q, to characterize classes of queries that can be answered in parallel poly-logarithmic time (NC) after PTIME preprocessing. (2) We show that several natu- ral query classes are -tractable and are feasible on big data. (3) We also study a set TQ of query classes that can be ef- fectively converted to -tractable queries by re-factorizing its data and queries for preprocessing. We introduce a form of NC reductions to characterize such conversions. (4) We show that a natural query class is complete for TQ. (5) We also show that T0 Q P unless P = NC, i.e., the set T0 Q of all -tractable queries is properly contained in the set P of all PTIME queries. Nonetheless, TQ = P, i.e., all PTIME query classes can be made -tractable via proper re- factorizations. This work is a step towards understanding the tractability of queries in the context of big data.-
dc.titleMaking Queries Tractable on Big Data with Preprocessing-
dc.typeJournal Contribution-
item.contributorFan, Wenfei-
item.contributorNEVEN, Frank-
item.contributorGEERTS, Floris-
item.fulltextNo Fulltext-
item.fullcitationFan, Wenfei; GEERTS, Floris & NEVEN, Frank (2013) Making Queries Tractable on Big Data with Preprocessing. In: Proceedings of the VLDB Endowment, 6 (1), p. 685-696.-
item.accessRightsClosed Access-
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