Long Beach, CA, USA
Mar. 1, 2010 to Mar. 6, 2010
Jun-Seok Heo , Department of Computer Science, KAIST, Korea
Junghoo Cho , Department of Computer Science, University of California, Los Angeles, USA
Kyu-Young Whang , Department of Computer Science, KAIST, Korea
In this paper, we propose the Hybrid-Layer Index (simply, the HL-index) that is designed to answer top-k queries efficiently when the queries are expressed on any arbitrary subset of attributes in the database. Compared to existing approaches, the HL-index significantly reduces the number of tuples accessed during query processing by pruning unnecessary tuples based on two criteria, i.e., it filters out tuples both (1) globally based on the combination of all attribute values of the tuples like in the layer-based approach (simply, layer-level filtering) and (2) based on individual attribute values used for ranking the tuples like in the list-based approach (simply, list-level filtering). Specifically, the HL-index exploits the synergic effect of integrating the layer-level filtering method and the list-level filtering method. Details and extensive experiments are available in the full paper .
Jun-Seok Heo, Junghoo Cho, Kyu-Young Whang, "The Hybrid-Layer Index: A synergic approach to answering top-k queries in arbitrary subspaces", ICDE, 2010, 2013 IEEE 29th International Conference on Data Engineering (ICDE), 2013 IEEE 29th International Conference on Data Engineering (ICDE) 2010, pp. 445-448, doi:10.1109/ICDE.2010.5447908