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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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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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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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Proving Equivalence Between Imperative and MapReduce Implementations Using Program Transformations [PDF]
Electronic Proceedings in Theoretical Computer Science, 2018 Distributed programs are often formulated in popular functional frameworks like MapReduce, Spark and Thrill, but writing efficient algorithms for such frameworks is usually a non-trivial task.
Bernhard Beckert +5 more
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An alternative C++-based HPC system for Hadoop MapReduce
Open Computer Science, 2022 MapReduce (MR) is a technique used to improve distributed data processing vastly and can massively speed up computation. Hadoop and MR rely on memory-intensive JVM and Java. A MR framework based on High-Performance Computing (HPC) could be used, which is
Srinivasakumar Vignesh +3 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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Algorithms, 2021 Microwave imaging systems are currently being investigated for breast cancer, brain stroke and neurodegenerative disease detection due to their low cost, portable and wearable nature. At present, commonly used radar-based algorithms for microwave imaging
Rahmat Ullah, Tughrul Arslan
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ICTACT Journal on Soft Computing, 2022 Hierarchical Data mining using distributed environment is an imperative in big data analysis. Multilevel association rules can provide more substantial information than single level rules, and it also determines hierarchical knowledge from the dataset ...
Dinesh J. Prajapati
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Cloudgene: A graphical execution platform for MapReduce programs on private and public clouds
BMC Bioinformatics, 2012 Background The MapReduce framework enables a scalable processing and analyzing of large datasets by distributing the computational load on connected computer nodes, referred to as a cluster.
Schönherr Sebastian +5 more
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