Efficient Query Handling On Big Data in Network Using Pattern Matching Algorithm: A Review

Prasadkumar Kale, Arti Mohanpurkar

Abstract: Manipulation of Queries on a large amount of data is done with various technologies. Query handling of Big data is a challenging task because of unstructured, real-time data. Efficient Query execution technique usage partition algorithm & pattern match algorithm for handling queries of the user. These techniques provide faster execution of such queries on the Big data in an efficient manner. Various authors propose query execution using DAG, ranges, unification & other methods. Range-aggregate queries are giving better performance with balance partition algorithm and map-reduce technique for handling large amount of queries with pattern matching technique.

Keywords: Big data, Range-Aggregate query, Map-Reduce, Partitioning, Pattern matching

How to Cite?: Prasadkumar Kale, Arti Mohanpurkar, "Efficient Query Handling On Big Data in Network Using Pattern Matching Algorithm: A Review", Volume 3 Issue 11, November 2014, International Journal of Science and Research (IJSR), Pages: 2247-2250, https://www.ijsr.net/getabstract.php?paperid=OCT141282, DOI: https://dx.doi.org/10.21275/OCT141282

Download Citation: APA | MLA | BibTeX | EndNote | RefMan