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  •   Open Research
  • AUT Faculties
  • Faculty of Design and Creative Technologies (Te Ara Auaha)
  • School of Engineering, Computer and Mathematical Sciences - Te Kura Mātai Pūhanga, Rorohiko, Pāngarau
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HYBRIDJOIN for near-real-time Data Warehousing

Naeem, MA; Dobbie, G; Weber, G
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HYBRIDJOIN-for-Near-Real-Time-Data-Warehousing.pdf (440.8Kb)
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http://hdl.handle.net/10292/4051
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Abstract
An important component of near-real-time data warehouses is the near-real-time integration layer. One important element in near-real-time data integration is the join of a continuous input data stream with a diskbased relation. For high-throughput streams, stream-based algorithms, such as Mesh Join (MESHJOIN), can be used. However, in MESHJOIN the performance of the algorithm is inversely proportional to the size of disk-based relation. The Index Nested Loop Join (INLJ) can be set up so that it processes stream input, and can deal with intermittences in the update stream but it has low throughput. This paper introduces a robust stream-based join algorithm called Hybrid Join (HYBRIDJOIN), which combines the two approaches. A theoretical result shows that HYBRIDJOIN is asymptotically as fast as the fastest of both algorithms. The authors present performance measurements of the implementation. In experiments using synthetic data based on a Zipfian distribution, HYBRIDJOIN performs significantly better for typical parameters of the Zipfian distribution, and in general performs in accordance with the theoretical model while the other two algorithms are unacceptably slow under different settings.
Keywords
Data transformation; Data Warehousing; Near-real-time; Performance and tuning
Date
2011
Source
International Journal of Data Warehousing and Mining, vol.7(4), pp.21 - 42
Item Type
Journal Article
Publisher
IGI Publishers
DOI
10.4018/jdwm.2011100102
Publisher's Version
http://dx.doi.org/10.4018/jdwm.2011100102
Rights Statement
Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.

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