Cube

Title and Author of Paper An Array-Based Algorithm for Simultaneous Multidimensional Aggregates. Y. Zhao et al. Summary One of the core functions of an OLAP system is computing aggregations and group-by operations. This functionality has been characterized by the “Cube” operator, which computes group-by aggregations over all possible subsets of a specified dimension. As an example of the Cube operator, consider a model with the dimensions product, store, date, and the measured value sales. To compute the Cube for this data set requires computing sales for all subsets of the dimensions: sales by product, store, and date; sales by product and store; sales by product; etc. As a user, I want the system to prepare these results for me in response to ad-hoc queries or as part of a ETL job that prepares the data for analysis. Because there is a lot of data involved, the challenge of implementing the Cube operator is in computing these aggregations as efficiently as possible. ...