Y. Zhou, P. Deshpande, and J. Naughton. An array-based algorithm for simultaneous multidimensional aggregates. In Proceedings of the  Home/Search Document Not in Database Summary Related Articles Check |
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Computing and Querying Datacubes - Zaman (Correct)
....Color Year, Color Model Year Color Figure 1.1: The Datacube Lattice 1 Assuming certain properties of aggregate functions. We discuss di erent classes of aggregate functions in the next chapter. 9 There are a number of di erent algorithms for computing the datacube [AAD 96, GBLP96, RS97b, ZDN97, SLCJ98] We notice that the size of a datacube is often much larger than that of the base data itself. Datacube computation is very expensive and if the cube is going to be frequently queried it is inecient to compute the necessary datacube tuples from the base data for each query. In this ....
....to use the smallest parent optimization. This optimization proposes using the parent cuboid which is smallest in size. The data structure needed for this algorithm will often not t into memory for sparse relations even when R does. In this case, the algorithm does not apply. Zhou et al. ZDN97] have proposed an array based algorithm that computes the datacube using array chunking techniques. By managing the order in which chunks are processed, substantially less of the result array needs to be kept in memory at any one time than with the algorithm of Gray et al. Nevertheless, when the ....
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Y. Zhou, P. Deshpande, and J. Naughton. An array-based algorithm for simultaneous multidimensional aggregates. In Proceedings of the
Optimizing Selections over Datacubes - Ross, Zaman (1998) (1 citation) (Correct)
....times. We can make use of generalization by outputting a tuple as soon as we know that it will be meet the threshold. This saves us the cost of further aggregations made to that counter in memory, which might be significant if the aggregate function itself is expensive to compute. Zhou et al. [19] have proposed an array based algorithm that computes the datacube using array chunking techniques. By managing the order in which chunks are processed, substantially less of the result array needs to be kept in memory at any one time than with the algorithm of Gray et al. Nevertheless, when the ....
Y. Zhou et al. An array-based algorithm for simultaneous multidimensional aggregates. In Proceedings of the 1997 ACM SIGMOD Conference.
Optimizing Selections over Data Cubes - Ross, Zaman (1998) (1 citation) (Correct)
....times. We can make use of generalization by outputting a tuple as soon as we know that it will be meet the threshold. This saves us the cost of further aggregations made to that counter in memory, which might be significant if the aggregate function itself is expensive to compute. Zhou et al. [13] have proposed an array based algorithm that computes the datacube using array chunking techniques. By managing the order in which chunks are processed, substantially less of the result array needs to be kept in memory at any one time than with the algorithm of Gray et al. Nevertheless, when the ....
Y. Zhou, P. Deshpande, and J. Naughton. An array-based algorithm for simultaneous multidimensional aggregates. In Proceedings of the 1997 ACM SIGMOD Conference on Management of Data, pages 159--170, Tucson, Arizona, May 1997. Association for Computing Machinery.
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