There are four typical data cube computation methods Multiwa

There are four typical data cube computation methods: Multiway, BUC, H-cubing, and Star-cubing. Based on your implementation, discuss the following:

i. What challenging computation problems are encountered as the number of dimensions grows large?

ii. How can iceberg cubing solve the problems of part (a) for some data sets (and characterize such data sets)?

iii. Give one simple example to show that sometimes iceberg cubes cannot provide a good solution.

Solution

As number of dimension grow large in data cube number of cuboid also grow. And this growth will be exponantial. So to we need a lot of memory and time to compute all the cuboid of large dimension data cube. In iceberge cubing is done based on aggregation condition. So this method don\'t keep every cell. It identfy and calculated those values which may required for decision making using aggreagation condition.So number of cells in cube get reduced. Iceberge fails when aggreagation condtion provide too many candidates and cube has large number of dimension. So it cause memory issue