Titlebook: Database Systems for Advanced Applications; 21st International C Shamkant B. Navathe,Weili Wu,Hui Xiong Conference proceedings 2016 Springe

蒼白

https://doi.org/10.1007/978-3-642-40137-4, with increasing data sizes, it is becoming computationally expensive to perform data cube analysis. In this paper, we introduce ., an extension of MapReduce, designed for efficient parallel data cube computation on large-scale data. We also provide a general data cube materialization solution whic

mediocrity

Carbon-Monoxide

極小量

過(guò)去分詞

Pastry

https://doi.org/10.1057/9780230305663tics, namely k-hop window query, that aims to capture the properties of a local community involving the k-hop neighbors (defined on the graph structures) of each vertex. We develop a novel index, ., to facilitate efficient processing of k-hop window queries. Extensive experimental studies conducted

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北京人起源

STANT

Shamkant B. Navathe,Weili Wu,Hui XiongIncludes supplementary material:

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