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An Approach in Big Data Analytics to Improve the Velocity of Unstructured Data Using MapReduce

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  • Sundarakumar M. R.

    (AMC Engineering College, Bengaluru, India)

  • Mahadevan G.

    (AMC Engineering College, Bengaluru, India)

  • Ramasubbareddy Somula

    (VNRVJIET, Secunderabad, India)

  • Sankar Sennan

    (Sona College of Technology, Salem, India)

  • Bharat S. Rawal

    (Gannon University, USA)

Abstract

Big Data Analytics is an innovative approach for extracting the data from a huge volume of data warehouse systems. It reveals the method to compress the high volume of data into clusters by MapReduce and HDFS. However, the data processing has taken more time for extract and store in Hadoop clusters. The proposed system deals with the challenges of time delay in shuffle phase of map-reduce due to scheduling and sequencing. For improving the speed of big data, this proposed work using the Compressed Elastic Search Index (CESI) and MapReduce-Based Next Generation Sequencing Approach (MRBNGSA). This approach helps to increase the speed of data retrieval from HDFS clusters because of the way it is stored in that. this method is stored only the metadata in HDFS which takes less memory during runtime compare to big data due to the volume of data stored in HDFS. This approach is reduces the CPU utilization and memory allocation of the resource manager in Hadoop Framework and imroves data processing speed, such a way that time delay has to be reduced with minimum latency.

Suggested Citation

  • Sundarakumar M. R. & Mahadevan G. & Ramasubbareddy Somula & Sankar Sennan & Bharat S. Rawal, 2021. "An Approach in Big Data Analytics to Improve the Velocity of Unstructured Data Using MapReduce," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 10(4), pages 1-25, October.
    • Handle: RePEc:igg:jsda00:v:10:y:2021:i:4:p:1-25
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    References listed on IDEAS

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    1. Palash Dutta, 2017. "Decision Making in Medical Diagnosis via Distance Measures on Interval Valued Fuzzy Sets," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 6(4), pages 63-83, October.
    2. Fatma H. Elfouly & Rabie A. Ramadan & Mohamed I. Mahmoud & Moawad I. Dessouky, 2017. "Efficient Data Reporting in a Multi-Object Tracking Using WSNs," International Journal of System Dynamics Applications (IJSDA), IGI Global, vol. 6(1), pages 38-57, January.
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