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Implementation of Data Analytics for MongoDB Using Trigger Utility

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Computational Intelligence in Data Mining—Volume 1

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 410))

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Abstract

SQL based traditional databases like Oracle; SQL server offers the capability to develop programs like Trigger. Trigger is a very important feature provided by many databases, especially useful in monitoring, rule enforcement, data validation and data analytics etc. MongoDB is non SQL document oriented database. MongoDB is the fastest growing and most demanding non SQL database. Since MongoDB primarily is operated using its out of box tools like mongo, mongos, bsondump, mongod, mongoexport and Java script function. MongoDB does not provide in-built feature for triggers which is very efficient in data analytics, monitoring and reporting purpose. Paper presents two utility in which one utility is a listener or poller utility which is developed to give similar feature like trigger and after that second utility is developed which gives historical data analytic capability on Mongo database by using the trigger utility. It pulls the data from analytic collection and generates the graph. Data analytic tools plays vital role in decision making in today’s complex business environment where data size is very huge and unstructured by nature.

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Authors and Affiliations

  1. Amity University, Sec-125, Noida, U.P., India

    Kalpana Dwivedi & Sanjay Kumar Dubey

Authors
  1. Kalpana Dwivedi
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  2. Sanjay Kumar Dubey
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Correspondence to Kalpana Dwivedi .

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Editors and Affiliations

  1. Veer Surendra Sai University of Tech., Dept of Computer Sci Eng & IT, Sambalpur, Odisha, India

    Himansu Sekhar Behera

  2. National Institute of Technology, Dept. of Computer Science & Engineering, Rourkela, Odisha, India

    Durga Prasad Mohapatra

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Dwivedi, K., Dubey, S.K. (2016). Implementation of Data Analytics for MongoDB Using Trigger Utility. In: Behera, H., Mohapatra, D. (eds) Computational Intelligence in Data Mining—Volume 1. Advances in Intelligent Systems and Computing, vol 410. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2734-2_5

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  • DOI: https://doi.org/10.1007/978-81-322-2734-2_5

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  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2732-8

  • Online ISBN: 978-81-322-2734-2

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