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Bigdata Platform Design and Implementation Model


Affiliations
1 Business Administration, Sunmoon University, Asan, 336-708, Korea, Republic of
2 IMCLOUD Corporation, Seoul, 133-070, Korea, Republic of
 

Bigdata software platform technology using Hadoop Ecosystem is the essential element and also underlying technology for application software or service implementation of bigdata analysis. It is required to have bigdata platform technology that can ensure the scalability, reliability and high performance of system for processing and analyzing a variety of bigdata related tasks including structured data, unstructured data, semi-structured data, etc. Bigdata platform can process large amounts of data in parallel unlike those conventional application software solutions and it is an easily scalable system. Its technical components include collection (Flume and Sqoop), storage (Hadoop and NoSQL), search (Solr), analysis (R Analysis), visualization (Node.js), scheduler (Oozie), etc. The purpose of this study is to propose an optimized bigdata platform implementation model through S/W configuration based on open source.

Keywords

Bigdata, Bigdata Visualization, Flume, Hadoop, MAP/REDUCE, Oozie, Platform, R Analysis, Sqoop, SQL on Hadoop
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  • Bigdata Platform Design and Implementation Model

Abstract Views: 149  |  PDF Views: 0

Authors

Noh Kyoo-sung
Business Administration, Sunmoon University, Asan, 336-708, Korea, Republic of
Lee Doo-sik
IMCLOUD Corporation, Seoul, 133-070, Korea, Republic of

Abstract


Bigdata software platform technology using Hadoop Ecosystem is the essential element and also underlying technology for application software or service implementation of bigdata analysis. It is required to have bigdata platform technology that can ensure the scalability, reliability and high performance of system for processing and analyzing a variety of bigdata related tasks including structured data, unstructured data, semi-structured data, etc. Bigdata platform can process large amounts of data in parallel unlike those conventional application software solutions and it is an easily scalable system. Its technical components include collection (Flume and Sqoop), storage (Hadoop and NoSQL), search (Solr), analysis (R Analysis), visualization (Node.js), scheduler (Oozie), etc. The purpose of this study is to propose an optimized bigdata platform implementation model through S/W configuration based on open source.

Keywords


Bigdata, Bigdata Visualization, Flume, Hadoop, MAP/REDUCE, Oozie, Platform, R Analysis, Sqoop, SQL on Hadoop



DOI: https://doi.org/10.17485/ijst%2F2015%2Fv8i18%2F114788