MM-Cubing: computing Iceberg cubes by factorizing the lattice space
Zheng Shao, Jiawei Han, Dong Xin · 2004
The data cube and iceberg cube computation problem has been studied by many researchers. There are three major approaches developed in this direction: (1) top-down computation, represented by MultiWay array aggregation [22], which utilizes shared computation and performs well on dense data sets; (2) bottom-up computation, represented by BUC [6], which takes advantage of Apriori Pruning and performs well on sparse data sets; and (3) integrated top-down and bottom-up computation, represented by StarCubing [21], which takes advantages of both and has high performance in most cases. However, the performance of Star-Cubing degrades in very sparse data sets due to the additional cost introduced by the tree structure. None of the three approaches achieves uniformly high performance on all kinds of data sets.