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.
This work was supported from the Polish Ministry of Science and Higher Education grant No. N N516 365834.
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Chmiel, J., Morzy, T., Wrembel, R. (2009). HOBI: Hierarchically Organized Bitmap Index for Indexing Dimensional Data. In: Pedersen, T.B., Mohania, M.K., Tjoa, A.M. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2009. Lecture Notes in Computer Science, vol 5691. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-03730-6_8
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DOI: https://doi.org/10.1007/978-3-642-03730-6_8
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