Extending standard MapReduce algorithms - Archive ouverte HAL
Communication Dans Un Congrès Année : 2016

Extending standard MapReduce algorithms

Résumé

The information rate nowadays is expanding very quickly and contains complex and heterogeneous data types (text, images, videos, GPS data, purchase transactions) that require powerful computing engines, able to easily store and process such complex structures. Gartner's definition of the 3Vs (volume, velocity, variety) describing this expansion of data will then lead to extract the unnamed forth V (value) from BigData. This added value addresses the need for valuation of enterprise data. In this paper, we discuss the existing MapReduce implementation techniques and the need of a different approach based on the pre-processing of the data. The goal is to show interesting results in terms of data processing costs, performance and green computing
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Dates et versions

hal-01471968 , version 1 (20-02-2017)

Identifiants

Citer

Hadi Hashem, Daniel Ranc. Extending standard MapReduce algorithms. BIGMM 2016 : 2nd International Conference on Multimedia Big Data, Apr 2016, Taipeh, Taiwan. pp.159 - 165, ⟨10.1109/BigMM.2016.49⟩. ⟨hal-01471968⟩
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