Optimization Method of Massive Data Query

Yu Ming Chen

doi:10.4028/www.scientific.net/AMM.602-605.3247

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 602-605Optimization Method of Massive Data Query

Optimization Method of Massive Data Query

Abstract:

Optimization method ofmassive dataquery is researched in this paper.In the modernInternet environment,the datahas the characteristics oflarge amount of information, complexity, disorder, andchaosassociation. Using traditionalqueried methodsoftenrequirea lot oflimitedconditions, witha lot of drawbacks such as time-consuming data query, moreineffective queryand low efficiency.To this end, anoptimizationmethod of massive data query based onparallel Apriori algorithm is proposed in this paper.The massive dataare made simplification processing andredundant data are deleted to providedata foundation for fast and accuratedataquery.Effectiveassociation rulesof the massive data are calculated, in order to obtain the relevantof the target data. Based onAprioriparallel algorithm,massivedata are processedto achieveaccurate query. Experimental results show thatthe use ofoptimization algorithm for massive dataquerycan improvethe query speedof target data and it has a strong superiority.

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Periodical:

Applied Mechanics and Materials (Volumes 602-605)

Pages:

3247-3250

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.602-605.3247

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Online since:

August 2014

Authors:

Yu Ming Chen*

Keywords:

Apriori Algorithm, Data Query, Database, Massive Data

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* - Corresponding Author

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