Efficient Main-Memory Top-K Selection for Multicore Architectures
Efficient Main-Memory Top-K Selection For Multicore Architectures Vasileios Zois Vassilis J. Tsotras Walid A. Najjar University of California, University of California, University of California, Riverside Riverside Riverside vzois001@ucr.edu tsotras@cs.ucr.edu najjar@cs.ucr.edu ABSTRACT to, simple selection [15, 29, 18, 22], Top- k group-by aggre- Efficient Top- k query evaluation relies on practices that uti- gation [28], Top- k join [31, 23], as well as Top- k query varia- lize auxiliary data structures to enable early termination. tions on different applications (spatial, spatiotemporal, web Such techniques were designed to trade-off complex work in search, etc.) [7, 11, 8, 26, 1, 5]. All variants concentrate on the buffer pool against costly access to disk-resident data. minimizing the number of object evaluations while main- Parallel in-memory Top- k selection with support for early taining efficient data access. In relational database manage- termination presents a novel challenge because computa- ment systems (RDBMS), the most prominent solutions for tion shifts higher up in the memory hierarchy. In this en- Top- k selection fit into three categories: (i) using sorted- vironment, data scan methods using SIMD instructions and lists [15], (ii) utilizing materialized views [22], and (iii) ap- multithreading perform well despite requiring evaluation of plying layered-based methods (convex-hull [6], skyline [27]). the complete dataset. Early termination schemes that favor Efficient Top- k query processing entails minimizing object simplicity require random access to resolve score ambiguity evaluations through candidate pruning [29] and early termi- while those optimized for sequential access incur too many nation [15, 2].
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