Vijay Tv Gopinath

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Greedy Selection Of Materialized Views Tv Vijay Kumar* Aloke Ghoshal
greedy selection of materialized views tv vijay kumar* aloke ghoshal
Abstract: Greedy based approach for view selection at each step selects a beneficial view that fits within the space available for view materialization. Most of these approaches are focused around the HRU algorithm, which uses a multidimensional lattice framework to determine a good set of views to materialize. The HRU algorithm exhibits high run time complexity as the number of possible views is exponential with respect to the number of dimensions. The PGA algorithm provides a scalable solution to this .

Language: english
PDF pages: 17, PDF size: 0.15 MB
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Greedy Selection Of Materialized Views Tv Vijay Kumar* Aloke Ghoshal
greedy selection of materialized views tv vijay kumar* aloke ghoshal
Consequently for higher dimensional data sets, all possible views cannot be stored due to space constraint. Therefore, there is a need to select optimal subset of views with respect to query response time. However, optimal views selection is an NP-Complete problem [6][8]. An alternative way to select views to materialize is by pruning the search space either empirically or heuristically [20]. The empirical selection makes use of the past querying patterns for selecting views to materialize. Heuristically .

Language: english
PDF pages: 12, PDF size: 0.16 MB
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