Processing star queries on hierarchically-clustered fact tables

  • Authors:

  • Nikos Karayannidis;Aris Tsois;Timos Sellis;Roland Pieringer;Volker Markl;Frank Ramsak;Robert Fenk;Klaus Elhardt;Rudolf Bayer

  • Affiliations:

  • Institute of Communication and Computer Systems and Department of Electrical and Computer Engineering, National Technical University of Athens, Zographou, Athens, Hellas;Institute of Communication and Computer Systems and Department of Electrical and Computer Engineering, National Technical University of Athens, Zographou, Athens, Hellas;Institute of Communication and Computer Systems and Department of Electrical and Computer Engineering, National Technical University of Athens, Zographou, Athens, Hellas;TransAction Software GmbH Gustav-Heinemann-Ring, München, Germany;IBM Almaden Research Center, San Jose, CA;Bayerisches Forschungszentrum für Wissensbasierte Systeme, Orleansstrá, München, Germany;Bayerisches Forschungszentrum für Wissensbasierte Systeme, Orleansstrá, München, Germany;TransAction Software GmbH Gustav-Heinemann-Ring, München, Germany;Institut förmatik, TU-München, Orleansstraße, München, Germany

  • Venue:
  • VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
  • Year:
  • 2002

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Abstract

Star queries are the most prevalent kind of queries in data warehousing, OLAP and business intelligence applications. Thus, there is an imperative 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 speedups of orders of magnitude for typical star queries in real world applications.