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Research on Computing Efficiency of MapReduce in Big Data Environment [PDF]
ITM Web of Conferences, 2019 The emergence of big data has brought a great impact on traditional computing mode, the distributed computing framework represented by MapReduce has become an important solution to this problem.
Gao Tilei +4 more
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Lean MapReduce: A B-tree Inspired MapReduce Framework
, 2016 There is a deluge of unstructured data flowing out from numerous sources, including the devices which make up the Internet-of-Things. This data flow is characterized by sheer volume, variety and velocity, and is expected to double every two years. Organizations perceive hidden value in unstructured data, but are usually constrained by budget and access
Arinze George Akubue
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A Novel Configuration Tuning Method Based on Feature Selection for Hadoop MapReduce
IEEE Access, 2020 Configuration parameter optimization is an important means of improving the performance of the MapReduce model. The existing parameter tuning methods usually optimize all configuration parameters in MapReduce.
Jun Liu +4 more
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Journal of Applied Science and Engineering, 2022 Big data in healthcare defines a massive quantity of healthcare data accumulated from massive sources like electronic health records (EHR), medical imaging, genomic sequence, pharmacological research, wearable, medical gadgets, etc.
T. Gayathri, D. Lalitha Bhaskari
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XRepo 2.0: a Big Data Information System for Education in Prognostics and Health Management
International Journal of Prognostics and Health Management, 2021 Within Industry 4.0, Prognostics and Health Management (PHM) holds great potential due to its ability to bring deep insights into the current state of manufacturing equipment.
Nestor Romero +4 more
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ACM Transactions on Architecture and Code Optimization, 2013 The prevalence of chip multiprocessors opens opportunities of running data-parallel applications originally in clusters on a single machine with many cores. MapReduce, a simple and elegant programming model to program large-scale clusters, has recently been shown a promising alternative to harness the multicore platform.
Rong Chen, Haibo Chen
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High Frequency Rule Synthesis in a Large Scale Multiple Database with MapReduce [PDF]
International Journal of Electronics and Telecommunications, 2022 Increasing development in information and communication technology leads to the generation of large amount of data from various sources. These collected data from multiple sources grows exponentially and may not be structurally uniform. In general, these
Sudhanshu Shekhar Bisoyi +2 more
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The research of social processes at the university using big data [PDF]
MATEC Web of Conferences, 2021 The volume of information in the 21st century is growing at a rapid pace. Big data technologies are used to process modern information. This article discusses the use of big data technologies to implement monitoring of social processes.
Hacimahmud Abdullayev Vugar +2 more
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Evaluation of high-level query languages based on MapReduce in Big Data
Journal of Big Data, 2018 MapReduce (MR) is a criterion of Big Data processing model with parallel and distributed large datasets. This model knows difficult problems related to low-level and batch nature of MR that gives rise to an abstraction layer on the top of MR.
Marouane Birjali +2 more
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Recognizing Indonesian Acronym and Expansion Pairs with Supervised Learning and MapReduce
Information, 2020 During the previous decades, intelligent identification of acronym and expansion pairs from a large corpus has garnered considerable research attention, particularly in the fields of text mining, entity extraction, and information retrieval.
Taufik Fuadi Abidin +4 more
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