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(2018). Hadoop Framework and Uses and its Challenges. Electronic and Cyber Defense, 9(2), 61-68.
. "Hadoop Framework and Uses and its Challenges". Electronic and Cyber Defense, 9, 2, 2018, 61-68.
(2018). 'Hadoop Framework and Uses and its Challenges', Electronic and Cyber Defense, 9(2), pp. 61-68.
Hadoop Framework and Uses and its Challenges. Electronic and Cyber Defense, 2018; 9(2): 61-68.

Hadoop Framework and Uses and its Challenges

پدافند غیرعامل
Article 6, Volume 9, Issue 2, September 2029, Pages 61-68    PDF (872 K)
Document Type: Original Article
Receive Date: 01 May 2017,  Revise Date: 03 March 2019,  Accept Date: 19 September 2018 
Abstract
In recent years, an ever-increasing trend in mass data production is observed over the recent years. According to IBM, interestingly, around 90% of the existing data in the world is produced only in the last two years. It was in 2007, when the size of data exceeded the available storage resource for the first time. Also a wide range of applications such as search engines, medical research, weather forecasting and scientific programs needed distributed data for the processing and analysis ofbig amounts of data , Big Data, as in other technologies, has numerous opportunities and challenges in front users. The use of opportunities and benefits in the business and proper management challenges is converted into one of the hot topics in the field of IT, So there is a very important mechanism for processing mass at a cost effective, Therefore, one of the best ways to solve the problem of massive information processing is the use of the Apache Hadoop. Gartner's definition of the Hadoop is “Hadoop is a data management system that brings together large volumes of structured and unstructured data that affects almost all organizational layers. this causes the positioning in the heart of data centers”. Hadoop is part of the Apache Software Foundation supported byApache projects , in fact Hadoop is a free Java-based programming framework that allows us to process massive sets of data in a distributed processing environment supports. Therefore, in this article, we have a comparison of structured and unstructured Database and then, we investigate the Apache Hadoop architecture and its wide range of applications in today's Big Data as well as  challenges facing this emerging technology, such as batch processing, real-time processes and bottlenecks.
Keywords
Batch Process; Real-Time Process; Apache Hadoop; Distributed Systems; Big Data; Scalability
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