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Correlated Appraisal of Big Data, Hadoop and MapReduce

عنوان مقاله: Correlated Appraisal of Big Data, Hadoop and MapReduce
شناسه ملی مقاله: JR_ACSIJ-4-4_016
منتشر شده در شماره 4 دوره 4 فصل July در سال 1394
مشخصات نویسندگان مقاله:

Priyaneet Bhatia - Department of Computer Science and Engineering, Galgotias College of Engineering and Technology Uttar Pradesh Technical University Greater Noida, Uttar Pradesh ۲۰۱۳۰۶, India
Siddarth Gupta - Department of Computer Science and Engineering, Galgotias University Greater Noida, Uttar Pradesh ۲۰۳۲۰۸, India

خلاصه مقاله:
Big data has been an imperative quantum globally. Gargantuan data types starting from terabytes to petabytes are used incessantly. But, to cache thesedatabase competencies is an arduous task. Although, conventional database mechanisms were integral elements for reservoir of intricate and immeasurabledatasets, however, it is through the approach of NoSQL that is able to accumulate the prodigious information in aproficient style. Furthermore, the Hadoop framework isused which has numerous components. One of its foremost constituent is the MapReduce. The MapReduceis the programming quintessential on which mining of purposive knowledge is extracted. In this paper, the postulates of big data are discussed. Moreover, theHadoop architecture is shown as a master- slave procedure to distribute the jobs evenly in a parallel style. The MapReduce has been epitomized with the help of analgorithm. It represents WordCount as the criterion for mapping and reducing the datasets

کلمات کلیدی:
Big Data, Hadoop, MapReduce, RDBMS, NoSQL, Wordcount

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/405234/