An efficient approach for view selection for data warehouse using tree mining and evolutionary computation

• Autorzy: Thakare A. , Deshpande P.

Identyfikatory

DOI

10.7494/csci.2018.19.4.3006

• Języki publikacji: EN

Abstrakty

EN

The selection of a proper set of views to materialize plays an important role in database performance. There are many methods of view selection that use different techniques and frameworks to select an efficient set of views for materialization. In this paper, we present a new efficient scalable method for view selection under the given storage constraints using a tree mining approach and evolutionary optimization. The tree mining algorithm is designed to determine the exact frequency of (sub)queries in the historical SQL dataset. The Query Cost model achieves the objective of maximizing the performance benefits from the final view set that is derived from the frequent view set given by the tree mining algorithm. The performance benefit of a query is defined as a function of query frequency, query creation cost, and query maintenance cost. The experimental results show that the proposed method is successful in recommending a solution that is fairly close to an optimal solution.

Słowa kluczowe

EN

database management systems; data warehousing and data mining; query optimization; graph mining; algorithms for parallel computing; evolutionary computations; genetic algorithms

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Science
• Rocznik: 2018
• Tom: Vol. 19 (4)
• Strony: 431--455
• Opis fizyczny: Bibliogr. 20 poz., rys., tab.

Twórcy

autor

Thakare A.

• Visvesvaraya National Institute of Technology, Computer Science & Engineering Department, South Ambazari Road, Nagpur (Maharashtra) India 440010

autor

Deshpande P.

• Visvesvaraya National Institute of Technology, Computer Science & Engineering Department, South Ambazari Road, Nagpur (Maharashtra) India 440010

Bibliografia

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