Correlated Appraisal of Big Data, Hadoop and MapReduce

سال انتشار: 1394
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 792

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شناسه ملی سند علمی:

JR_ACSIJ-4-4_016

تاریخ نمایه سازی: 7 آذر 1394

چکیده 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

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نویسندگان

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