UGC Approved Journal no 63975(19)
New UGC Peer-Reviewed Rules

ISSN: 2349-5162 | ESTD Year : 2014
Volume 13 | Issue 3 | March 2026

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Published in:

Volume 6 Issue 2
February-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR1902C07


Registration ID:
198939

Page Number

32-36

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Title

A SURVEY ON BIG DATA PROCESSING

Abstract

Big data is the data which is not able to store and process by our traditional system. There are many tools now a days to store and process big data each and every device generates the lot of data every seconds nearly data generation is growing like anything past many years lot of data generated but not analyzed and used it now companies like amazon use the analysis on stored data and number one company in the world. So data analysis is very important to grow or development big data is not only about huge data along with that variety and velocity of data the speed at which data generated is also one of the challenges to store and manage the streaming data. And data is not of uniform in nature variety of data like structured whose fields and data types are known, semi structured whose data types are not known but fields are known and unstructured whose data types and fields are not known. to process Hadoop had very important components basically it has main two components like HDFS and Map Reduce to store and process big data on top of that the component YARN added for resource management on top of Hadoop framework many components like H-base, hive, pig, zoo-keeper, Oozie, flume and many are added to make user friendly and improve the performance one of the components which overcome drawbacks of Hadoop is spark and spark itself have many drawbacks to overcome one more framework flink added which also have many drawbacks which will be stated and tried to give solutions Here we ran wordcount for the sample input file with single mapper reducer and multiple reducers with Pig script without orderby and Hive with order by and we achieved enhanced performance with hive with order by along multiple reducers.

Key Words

Hadoop,HDFS,MapReduce,Spark,Flink

Cite This Article

"A SURVEY ON BIG DATA PROCESSING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 2, page no.32-36, February-2019, Available :http://www.jetir.org/papers/JETIR1902C07.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"A SURVEY ON BIG DATA PROCESSING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 2, page no. pp32-36, February-2019, Available at : http://www.jetir.org/papers/JETIR1902C07.pdf

Publication Details

Published Paper ID: JETIR1902C07
Registration ID: 198939
Published In: Volume 6 | Issue 2 | Year February-2019
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.19914
Page No: 32-36
Country: Bengaluru, Karnataka, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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