Survey of Distributed Computing Frameworks for Supporting Big Data Analysis Article Swipe
Xudong Sun
,
Yulin He
,
Dingming Wu
,
Joshua Zhexue Huang
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.26599/bdma.2022.9020014
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.26599/bdma.2022.9020014
Distributed computing frameworks are the fundamental component of distributed computing systems. They provide an essential way to support the efficient processing of big data on clusters or cloud. The size of big data increases at a pace that is faster than the increase in the big data processing capacity of clusters. Thus, distributed computing frameworks based on the MapReduce computing model are not adequate to support big data analysis tasks which often require running complex analytical algorithms on extremely big data sets in terabytes. In performing such tasks, these frameworks face three challenges: computational inefficiency due to high I/O and communication costs, non-scalability to big data due to memory limit, and limited analytical algorithms because many serial algorithms cannot be implemented in the MapReduce programming model. New distributed computing frameworks need to be developed to conquer these challenges. In this paper, we review MapReduce-type distributed computing frameworks that are currently used in handling big data and discuss their problems when conducting big data analysis. In addition, we present a non-MapReduce distributed computing framework that has the potential to overcome big data analysis challenges.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.26599/bdma.2022.9020014
- https://ieeexplore.ieee.org/ielx7/8254253/10026288/10026506.pdf
- OA Status
- diamond
- Cited By
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- References
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- OpenAlex ID
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https://openalex.org/W4320525798Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.26599/bdma.2022.9020014Digital Object Identifier
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Survey of Distributed Computing Frameworks for Supporting Big Data AnalysisWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-01-26Full publication date if available
- Authors
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Xudong Sun, Yulin He, Dingming Wu, Joshua Zhexue HuangList of authors in order
- Landing page
-
https://doi.org/10.26599/bdma.2022.9020014Publisher landing page
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https://ieeexplore.ieee.org/ielx7/8254253/10026288/10026506.pdfDirect link to full text PDF
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YesWhether a free full text is available
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diamondOpen access status per OpenAlex
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https://ieeexplore.ieee.org/ielx7/8254253/10026288/10026506.pdfDirect OA link when available
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Big data, Computer science, Data science, Data miningTop concepts (fields/topics) attached by OpenAlex
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37Total citation count in OpenAlex
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2025: 19, 2024: 10, 2023: 8Per-year citation counts (last 5 years)
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114Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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