Analysis of massive industrial data using MapReduce framework for parallel processing

With the emergence of the `Big Data’ paradigm, more and more industrial data are now available for practitioners and professionals.

This data is being generated faster due to the advancement of the new information technologies.

For reliability and maintenance engineers, `Big Data’ is an interesting source of information. If analyzed correctly, it can produce useful knowledge-base to help making decisions in an industrial organization.

The availability of `Big Data’ is now leading to a new area of researches that are dedicated to the analysis of such data.

This paper shows how to analyze massive amount of data generated from an industrial system(s).

Those massive data may range from terabytes to petabytes in size; analyzing such sizes cannot be performed on a single commodity computer due to the possibility of memory leakage as the data may not fit into the computer’s resources, specifically CPUs.

Even if it fits

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