Issue No. 05 - May (2014 vol. 26)
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TKDE.2013.125
Yufei Tao , Chinese Univ. of Hong Kong, Hong Kong, China
Cheng Sheng , Google, Zürich, Switzerland
Chin-Wan Chung , Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea
Jong-Ryul Lee , Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea
In the classic range aggregation problem, we have a set S of objects such that, given an interval I, a query counts how many objects of S are covered by I. Besides COUNT, the problem can also be defined with other aggregate functions, e.g., SUM, MIN, MAX and AVERAGE. This paper studies a novel variant of range aggregation, where an object can belong to multiple sets. A query (at runtime) picks any two sets, and aggregates on their intersection. More formally, let S1,...,Sm be m sets of objects. Given distinct set ids i, j and an interval I, a query reports how many objects in Si ∩ Sj are covered by I. We call this problem range aggregation with set selection (RASS). Its hardness lies in that the pair (i, j) can have (2m) choices, rendering effective indexing a non-trivial task. 2 The RASS problem can also be defined with other aggregate functions, and generalized so that a query chooses more than 2 sets. We develop a system called RASS to power this type of queries. Our system has excellent efficiency in both theory and practice. Theoretically, it consumes linear space, and achieves nearly-optimal query time. Practically, it outperforms existing solutions on real datasets by a factor up to an order of magnitude. The paper also features a rigorous theoretical analysis on the hardness of the RASS problem, which reveals invaluable insight into its characteristics.
set theory, indexing, query processing, rendering (computer graphics)
Yufei Tao, Cheng Sheng, Chin-Wan Chung and Jong-Ryul Lee, "Range Aggregation With Set Selection," in IEEE Transactions on Knowledge & Data Engineering, vol. 26, no. 5, pp. 1240-1252, 2014.