Pragmatic Influence of MapReduce in Big Data using Hadoop A literature review

Muhammad, Kaleem Ullah and Syed, Khuram Shahzad (2018) Pragmatic Influence of MapReduce in Big Data using Hadoop A literature review. In: Seventh International Conference on Advances in Computing, Electronics and Communication-ACEC2018, 18-19 August, 2018, Kuala Lumpur, Malaysia.

20180822_074714.pdf - Published Version

Download (548kB) | Preview
Official URL:


A term Big Data explain innovative technologies and techniques to store, manage, capture, analyze and distribute large size or petabyte data sets with high acceleration and dynamic structures. Big Data is categorized as semi-structured, unstructured, and structured, which results in an inability of traditional data managerial techniques. Data is produced from numerous resources and reached the system at different rates. This immense amount of data is processed in an efficient, and inexpensive manner, a technique of parallelism is practiced. Big Data parameters which include diversity, scale, and complexity required new techniques, architectures, analytics, and algorithms for the purpose of management of data and the knowledge hidden in it. Hadoop is a famous software platform to make data useful for the purpose of analytics to solve problems and structured the Big Data. Distributed processing is enabled by the help of Hadoop for huge datasets across the bunch of servers. It is specially designed to scale from one to thousands of high computing machines, with high fault tolerance degree.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Big Data, Hadoop, Distributed Processing
Depositing User: Mr. John Steve
Date Deposited: 07 Mar 2019 15:36
Last Modified: 07 Mar 2019 15:36

Actions (login required)

View Item View Item