Analyzing Geographical Events Map Reduce

  • Abstract
  • Keywords
  • References
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  • Abstract

    The huge information gathers huge volume of information; it is extraordinary computational test for the huge Hadoop information to keep up and process this information and furthermore removes valuable data in a proficient way. Land occasions will occur far and wide as one of the primary worldwide risks expanding under worldwide environmental change lately. Which raise the significance of avalanche events, with the point of diminishing their results we are utilizing Guide Lesson for dissecting these occasions in various regions in like manner with period.



  • Keywords

    Big data, map reduce.

  • References

      [1] Apache, Hadoop,, 2006.

      [2] Apache, Hive,, 2008.

      [3] Avnur R & Hellerstein JM, “Eddies: Continuously Adaptive Query Processing”, Proc. ACM SIGMOD Int’l Conf. Management of Data, (2000), pp.261-272.

      [4] Babu S, Munagala K, Widom J & Motwani R, “Adaptive Caching for Continuous Queries”, Proc. 21st Int’l Conf. Data Eng, (2005), pp.118-129.

      [5] Babu S & Widom J, “Streamon: An Adaptive Engine for Stream Query Processing”, Proc. ACM SIGMOD Int’l Conf. Management of Data, (2004), pp.931-932.

      [6] Battre D, Ewen S, Hueske F, Kao O, Markl V & Warneke D, “Nephele/Pacts: A Programming Model and Execution Framework for Web-Scale Analytical Processing”, Proc. First ACM Symp. Cloud Computing, (2010), pp.119-130.

      [7] Borkar V, Carey M, Grover R, Onose N & Vernica R, “Hyracks: A Flexible and Extensible Foundation for Data Intensive Computing”, Proc. IEEE 27th Int’l Conf. Data Eng. (ICDE), (2011).

      [8] Brin S & Page L, “The Anatomy of a Large-Scale Hypertextual Web Search Engine”, Computer Networks and ISDN Systems, Vol.30, (1998), pp.107-117.

      [9] Bu Y, Howe B, Balazinska M & Ernst M, “Haloop: Efficient Iterative Data Processing on Large Clusters”, Proc. VLDB Endowment, Vol.3, No.1/2, (2010), pp.285-296.

      [10] Chaiken R, Jenkins B, Larson P, Ramsey B, Shakib D, Weaver S & Zhou J, “Scope: Easy and Efficient Parallel Processing of Massive Data Sets”, Proc. VLDB Endowment, Vol.1, No.2, (2008), pp.1265-1276.




Article ID: 14979
DOI: 10.14419/ijet.v7i3.6.14979

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