A Review: Big Data Technologies with Hadoop Distributed Filesystem and Implementing M/R

Authors

  • Renas Rajab Asaad Department of Computer Science, Nawroz University, Duhok, Kurdistan Region - Iraq
  • Hawar B. Ahmad Department of Computer Science, Nawroz University, Duhok, Kurdistan Region - Iraq
  • Rasan Ismael Ali Department of Computer Science, Nawroz University, Duhok, Kurdistan Region - Iraq

DOI:

https://doi.org/10.25007/ajnu.v9n1a530

Keywords:

Big Data, Hadoop Ecosystem, Hadoop Distributed File System, NameNode, DataNode

Abstract

Today Big Data, is any set of data that is larger than the capacity to be processed using traditional database tools to capture, share, transfer, store, manage and analyze within an acceptable time frame; from the point of view of service providers, Organizations need to deal with a large amount of data for the purpose of analysis. And IT department are facing tremendous challenge in protecting and analyzing these increased volumes of information. The reason organizations are collecting and storing more data than ever before is because their business depends on it. The type of information being created is no more traditional database-driven data referred to as structured data rather it is data that include documents, images, audio, video, and social media contents known as unstructured data or Big Data. Big Data Analytics is a way of extracting value from these huge volumes of information, and it drives new market opportunities and maximizes customer retention. Moreover, this paper focuses on discussing and  understanding Big Data technologies and Analytics system with Hadoop distributed filesystem (HDFS). This can help predict future, obtain information, take proactive actions and make way for better strategic decision making.

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Published

2020-02-17

How to Cite

Asaad, R. R., Ahmad, H. B., & Ali, R. I. (2020). A Review: Big Data Technologies with Hadoop Distributed Filesystem and Implementing M/R. Academic Journal of Nawroz University, 9(1), 25–33. https://doi.org/10.25007/ajnu.v9n1a530

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Articles