Abstract
The developing enthusiasm inside of the field of information warehousing is transforming more pivotally for decision makers to take a faster and effective decision. The online decision needs a terribly short response time. There are a few calculations and algorithms which are utilized for different indexing strategies and are available for bringing this objective. In multi-dimensional databases, the clammy indexing systems that have pulled in consideration are cube indexing and bitmap indexing. In this research paper, our basic focus is on an approach to enhance the existing cube indexing and storage engine, which will permit us to improve the query resolution and optimization for getting a faster response. For that, we will enforce the Hilbert R-tree algorithm rules with the integration of Berkeley DB and the existing Sidera server cube indexing.
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Kothari, B.K., Patel, B.M., Patel, A.R. (2016). Enforcing Indexing Techniques in Berkeley DB Using Implementation of Hilbert Tree Algorithm. In: Satapathy, S., Joshi, A., Modi, N., Pathak, N. (eds) Proceedings of International Conference on ICT for Sustainable Development. Advances in Intelligent Systems and Computing, vol 408. Springer, Singapore. https://doi.org/10.1007/978-981-10-0129-1_8
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DOI: https://doi.org/10.1007/978-981-10-0129-1_8
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