Data Mining with Elastic

Authors

  • Mani Nandhini Sri  Sri Krishna College of Technology Coimbatore, Tamil Nadu, India
  • Mani Nivedhini  Sri Krishna College of Technology Coimbatore, Tamil Nadu, India
  • Dr. A. Balamurugan  Sri Krishna College of Technology Coimbatore, Tamil Nadu, India

Keywords:

Hadoop, NoSQL, Data Mining, Elastic, RESTful API, RDBMS, MySQL

Abstract

Recently, new "big data" technologies and architectures, including Hadoop and NoSQL databases, have evolved to better support the needs of organizations analyzing such data. In particular, Elastic a distributed full-text search engine explicitly addresses issues of scalability, big data search, and performance that relational databases were simply never designed to support. In this paper, we reflect upon our own experience with Elastic and highlight its strengths and weaknesses for performing modern mining software repositories research.

References

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  2. Sematext. Elastic refresh interval vs indexing performance. http://bit.ly/1iZoPGc, July 2013.
  3. Hao Zhang , Gang Chen”In Memory Pattern Mining Data”in IEEE Transactions on Knowledge and Data Engineering  Volume: 27, Issue: 7, July 1 2015.
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  5. Ling Chen ,Xue LI “Mining Health Examination Records-A Graph Based Approach” in IEEE Transactions on Knowledge and Data Engineering  Volume: 28, Issue:9, Sep 1 2016.

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Published

2017-04-30

Issue

Section

Research Articles

How to Cite

[1]
Mani Nandhini Sri, Mani Nivedhini, Dr. A. Balamurugan, " Data Mining with Elastic, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 3, Issue 3, pp.317-321, March-April-2017.