Abstract
This chapter presents a complete abstract processing plan that captures all the necessary steps in evaluating such queries over hierarchically clustered fact tables. Data warehousing (DW) has evolved into a major trend in database technology through the last decade. Furthermore, the multidimensional paradigm seems to be the undisputed winner as a design choice for such databases. Regardless of the underlying physical layer, relational technology or proprietary multidimensional structures, the conceptual model adopted is a data warehouse consisting of facts (or measures) organized into a set of dimensions, which in turn are organized into levels of different aggregation (that is, detail) that comprise one or more hierarchies. In particular, for relational databases, the multidimensional data warehouse consists of one or more star schemata. Star queries are the most prevalent kind of queries in data warehousing, online analytical processing (OLAP), and business intelligence applications. In the context of these new organizations, star query-processing changes radically.
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