Dynamic approach of Range Aggregate queries in Big Data environment

Abstract

Range-aggregate queries are to apply a certain aggregate function on all tuples within given query ranges. Existing approaches to range-aggregate queries are insufficient to quickly provide accurate results in big data environments. In this paper, we propose FastRAQ a fast approach to range-aggregate queries in big data environments. FastRAQ approach on the Linux platform, and evaluate its performance with about 10 billions data records. Experimental results demonstrate that FastRAQ can solve the 1: n format Range aggregate queries problem, i.e., there is one aggregation column and n index columns in a record. We plan to investigate how our solution can be extended to the case of m : n format problem, i.e., there are m aggregation columns and n index columns in a same record. In this range aggregation, insertions of dynamic environments. With the geometric aggregation queries expressions.

Authors and Affiliations

L. Pravin Kumar, Ramesh Krishnan

Keywords

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  • EP ID EP21623
  • DOI -
  • Views 195
  • Downloads 3

How To Cite

L. Pravin Kumar, Ramesh Krishnan (2016). Dynamic approach of Range Aggregate queries in Big Data environment. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 4(2), -. https://europub.co.uk./articles/-A-21623