Abstract
Query processing at runtime is an important issue for data-centric applications. A faster query execution is highly required which means searching and returning the appropriate data of database. Different techniques have been proposed over the time and materialized view construction is one of them. The efficiency of a materialized view (MV) is measured based on hit ratio, which indicates the ratio of number of successful search to total numbers of accesses. Literature survey shows that few research works has been carried out to analyze the relationship between the attributes based on nonlinear equations for materialized view creation. However, as nonlinear regression is slower, in this research work they are mapped into linear equations to keep the benefit of both the approaches. This approach is applied to recently executed query set to analyze the attribute affinity and then the materialized view is formed based on the result of attribute affinity.
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Sen, S., Ghosh, P., Cortesi, A. (2016). Materialized View Construction Using Linearizable Nonlinear Regression. In: Chaki, R., Cortesi, A., Saeed, K., Chaki, N. (eds) Advanced Computing and Systems for Security. Advances in Intelligent Systems and Computing, vol 395. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2650-5_17
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DOI: https://doi.org/10.1007/978-81-322-2650-5_17
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