Multi-Cube Computation
نویسندگان
چکیده
Computing a -attribute datacube requires the computation of an aggregate function over all groups generated by interrelated GROUP-BYs. In this paper, we focus on multi-cube computation. We extend the algorithms for single datacube computation to process multiple datacubes simultaneously. The issue we intend to explore is the memory utilization. We propose two multi-cube algorithms, namely, a sort-based algorithm and a hash-based algorithm. Different data skews and sparsities are investigated. Results from our extensive performance studies are reported.
منابع مشابه
Stream Cube : An Architecture 1 for Multi - Dimensional Analysis of Data
Real-time surveillance systems, telecommunication systems, and other dynamic environments often 19 generate tremendous (potentially infinite) volume of stream data: the volume is too huge to be scanned multiple 20 times. Much of such data resides at rather low level of abstraction, whereas most analysts are interested in relatively 21 high-level dynamic changes (such as trends and outliers). To...
متن کاملA multi-layered planner for self-reconfiguration of a uniform group of I-Cube modules
In this paper, we present a multi-layered planner for the motion of modules in a uniform group of I-Cube selfreconfiguring modular robotic system. The planner uses metacubes, the high-level abstraction of 8C16L groups. It combines distributed approaches at the high-level with lowlevel trajectory computation for the actual modules which can be completed in O(n) steps where n is the number of the...
متن کاملEstimating the Performance of Multi- Microcomputer Networks
A new paradigm for parallel computation based on large numbers of interconnected microcomputer nodes has recently emerged. The absence of any memory shared among the nodes makes the selection of an interconnection network capable of efficiently supporting message passing critical. A network performance evaluation technique based on the asymptotic analysis of a closed queueing network is used to...
متن کاملMulti-Dimensional Analysis of Data Streams Using Stream Cubes
Large volumes of dynamic stream data pose great challenges to its analysis. Besides its dynamic and transient behavior, stream data has another important characteristic: multi-dimensionality. Much of stream data resides at a multidimensional space and at rather low level of abstraction, whereas most analysts are interested in relatively high-level dynamic changes in some combination of dimensio...
متن کاملMap Cube Model - a model for multi-scale data
In this paper, we develop a model for the structure of multi-scale data derived from a map series. First we present a model of a map. We give an ontology of map elements and assign them to the objects of the model.. Then we derive a model for a series of maps, connecting several of the map models with the help of tree structures. This model is called the map cube model, the horizontal axes deno...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2001