HOBI: Hierarchically Organized Bitmap Index for Indexing Dimensional Data

  • Authors:
  • Jan Chmiel;Tadeusz Morzy;Robert Wrembel

  • Affiliations:
  • QXL Poland (Allegro.pl),;Institute of Computing Science, Poznań University of Technology, Poznań, Poland;Institute of Computing Science, Poznań University of Technology, Poznań, Poland

  • Venue:
  • DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
  • Year:
  • 2009

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Abstract

In this paper we propose a hierarchically organized bitmap index (HOBI) for optimizing star queries that filter data and compute aggregates along a dimension hierarchy. HOBI is created on a dimension hierarchy. The index is composed of hierarchically organized bitmap indexes, one bitmap index for one dimension level. It supports range predicates on dimensional values as well as roll-up operations along a dimension hierarchy. HOBI was implemented on top on Oracle10g and evaluated experimentally. Its performance was compared to a native Oracle bitmap join index. Experiments were run on a real dataset, coming from the biggest East-European Internet auction platform Allegro.pl . The experiments show that HOBI offers better star query performance than the native Oracle bitmap join index.