Programming platforms for big data analysis

Cao, Jiannong, Chawla, Shailey, Wang, Yuqi, and Wu, Hanqing (2017) Programming platforms for big data analysis. In: Zomaya, Albert Y., and Sakr, Sherif, (eds.) Handbook of Big Data Technologies. Springer, Cham, Switzerland, pp. 65-99.

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Abstract

Big data analysis imposes new challenges and requirements on programming support. Programming platforms need to provide new abstractions and run time techniques with key features like scalability,fault tolerance, efficient task distribution, usability and processing speed. In this chapter, we first provide a comprehensive survey of the requirements, give an overview and classify existing big data programming platforms based on different dimensions. Then, we present details of the architecture, methodology and features of major programming platforms like MapReduce, Storm, Spark, Pregel, GraphLab, etc. Last, we compare existing big data platforms, discuss the need for a unifying framework, present our proposed framework MatrixMap, and give a vision about future work.

Item ID: 54138
Item Type: Book Chapter (Research - B1)
ISBN: 978-3-319-49339-8
Keywords: big data analysis; programming platforms; unifying framework; data parallel; stream processing
Date Deposited: 22 Jun 2018 00:39
FoR Codes: 46 INFORMATION AND COMPUTING SCIENCES > 4606 Distributed computing and systems software > 460602 Concurrent/parallel systems and technologies @ 50%
46 INFORMATION AND COMPUTING SCIENCES > 4699 Other information and computing sciences > 469999 Other information and computing sciences not elsewhere classified @ 30%
46 INFORMATION AND COMPUTING SCIENCES > 4606 Distributed computing and systems software > 460699 Distributed computing and systems software not elsewhere classified @ 20%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890202 Application Tools and System Utilities @ 50%
89 INFORMATION AND COMMUNICATION SERVICES > 8902 Computer Software and Services > 890299 Computer Software and Services not elsewhere classified @ 50%
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