Nikos Karayannidis, Aris Tsois, Timos Sellis, Roland Pieringer, Volker Markl, Frank Ramsak, Robert Fenk, Klaus Elhardt, Rudolf Bayer: Processing Star Queries on Hierarchically-Clustered Fact Tables Proceedings of the 28th International Conference on Very Large Databases (VLDB), 2002, Hongkong, China
Abstract:
Star Queries are the most prevalent kind of queries in Data Warehousing, OLAP and Business Intelligence Applications. Thus, there is an impera-tive need for efficiently processing Star Queries. To this end, a new class of fact table organizations has emerged that exploits path-based surrogate keys in order to hierarchically cluster the fact table data of a star schema [DRSN98, MRB99, KS01]. In the context of these new organizations, star query processing changes radically. In this paper, we present a complete abstract processing plan that captures all the necessary steps in evaluating such queries over hierarchically clustered fact tables. Furthermore, we present optimizations for surrogate key processing and a novel early grouping transformation for grouping on the dimension hierarchies. Our algorithms have been already implemented in a commercial Relational Database Management System (RDBMS) and the experimental evaluation, as well as customer feedback, indicates speed-ups of orders of magnitude for typical star queries in real world applications.
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