Beyond Hadoop: Spark and Storm

7 Pages Posted: 6 Oct 2019

See all articles by Ashirwad Philip Samuel

Ashirwad Philip Samuel

GD Goenka University

Nidhi Rathaur

GD Goenka University

Shweta Mongia

GD Goenka University

Date Written: October 2, 2019

Abstract

More than a decade after Hadoop appeared on the scene as an open-source framework for big data analysis, much of its independent benefits has revolutionized fast processing of the data. Its development has triggered a number of improvisations for specific needs of data processing, depending on the nature of the processing techniques at different levels of computation. These upgrades have not only shot up the processing speed but also capable to counter intensive real-time computation requirements. This paper highlights the challenges posed by the basic Hadoop architecture and compares with the remedies as provided by Spark and Storm frameworks.

Keywords: Hadoop, HDFS MapReduce, YARN Spark, Storm, Real-time data processing

Suggested Citation

Samuel, Ashirwad Philip and Rathaur, Nidhi and Mongia, Shweta, Beyond Hadoop: Spark and Storm (October 2, 2019). Proceedings of International Conference on Advancements in Computing & Management (ICACM) 2019. Available at SSRN: https://ssrn.com/abstract=3463331 or http://dx.doi.org/10.2139/ssrn.3463331

Ashirwad Philip Samuel (Contact Author)

GD Goenka University ( email )

Sohna Gurgaon Road
SOHNA GURGAON ROAD
Sohna, HI Haryana 122001
India

Nidhi Rathaur

GD Goenka University ( email )

Sohna Gurgaon Road
SOHNA GURGAON ROAD
Sohna, HI Haryana 122001
India

Shweta Mongia

GD Goenka University ( email )

Sohna Gurgaon Road
SOHNA GURGAON ROAD
Sohna, HI Haryana 122001
India

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