A Study on Hadoop Ecosystem and Its Applications in Big Data Analytics
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| Format: | Recurso digital |
| Langue: | anglais |
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Zenodo
2025
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| _version_ | 1866902137919766528 |
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| author | D P, Varshitha |
| author_facet | D P, Varshitha |
| contents | <p>In today’s data-driven world, vast amounts of information are generated every second from sources like social media, sensors, and transactions. Traditional tools are no longer capable of efficiently handling such massive, fast, and complex data. This paper focuses on Hadoop, a powerful open-source framework designed to store and process big data through distributed computing. It highlights the core components of the Hadoop ecosystem—HDFS, MapReduce, YARN—and explores tools like Hive, Pig, HBase, and Sqoop. The paper also discusses various applications of Hadoop in fields like healthcare, finance, and government, while addressing challenges such as scalability, security, and real-time analytics. The study concludes with insights into future trends like AI integration, edge analytics, and privacy-preserving data analysis. This work provides a comprehensive overview for researchers and practitioners interested in Big Data Analytics using Hadoop.</p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_16752980 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | A Study on Hadoop Ecosystem and Its Applications in Big Data Analytics D P, Varshitha Bigdata Hadoop Hadoop Ecosystem Data Analytics Distributed Computing Open Source Framework <p>In today’s data-driven world, vast amounts of information are generated every second from sources like social media, sensors, and transactions. Traditional tools are no longer capable of efficiently handling such massive, fast, and complex data. This paper focuses on Hadoop, a powerful open-source framework designed to store and process big data through distributed computing. It highlights the core components of the Hadoop ecosystem—HDFS, MapReduce, YARN—and explores tools like Hive, Pig, HBase, and Sqoop. The paper also discusses various applications of Hadoop in fields like healthcare, finance, and government, while addressing challenges such as scalability, security, and real-time analytics. The study concludes with insights into future trends like AI integration, edge analytics, and privacy-preserving data analysis. This work provides a comprehensive overview for researchers and practitioners interested in Big Data Analytics using Hadoop.</p> |
| title | A Study on Hadoop Ecosystem and Its Applications in Big Data Analytics |
| topic | Bigdata Hadoop Hadoop Ecosystem Data Analytics Distributed Computing Open Source Framework |
| url | https://doi.org/10.5281/zenodo.16752980 |