Extending Standard MapReduce Algorithms

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 (v...

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Bibliographic Details
Published in:2016 IEEE Second International Conference on Multimedia Big Data (BigMM) pp. 159 - 165
Main Authors: Hashem, Hadi, Ranc, Daniel
Format: Conference Proceeding
Language:English
Published: IEEE 01.04.2016
Subjects:
Algorithm design and analysis
BigData Tools
Computational modeling
Data Modeling
Data models
Data processing
Engines
MapReduce Algorithms
Pre-Processing
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Summary: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.
DOI:10.1109/BigMM.2016.49