Join Query Processing in MapReduce Environment

Anwar Shaikh; Rajni Jindal

Third International conference on advances in communication, network and computing

Research Article

Join Query Processing in MapReduce Environment

Download

526 downloads

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1007/978-3-642-35615-5_42,
    author={Anwar Shaikh and Rajni Jindal},
    title={Join Query Processing in MapReduce Environment},
    proceedings={Third International conference on advances in communication, network and computing},
    proceedings_a={CNC},
    year={2012},
    month={12},
    keywords={MapReduce Join processing Hadoop Multiway Join},
    doi={10.1007/978-3-642-35615-5_42}
}

Anwar Shaikh
Rajni Jindal
Year: 2012
Join Query Processing in MapReduce Environment
CNC
Springer
DOI: 10.1007/978-3-642-35615-5_42

Anwar Shaikh¹^,*, Rajni Jindal¹^,*

1: Delhi Technological University

*Contact email: anwardshaikh@gmail.com, rajnijindal@dce.ac.in

Abstract

MapReduce is a framework for processing large data sets, where straightforward computations are performed by hundreds of machines on large input data. Data could be stored and retrieved using structured queries. Join queries are most frequently used and importatnt. So its crucial to find out efficient join processing techniques. This paper provides overview of join query processing techniques & proposes a strategy to find out best suitable join processing algorithm.

Keywords: MapReduce Join processing Hadoop Multiway Join

Published: 2012-12-04

: http://dx.doi.org/10.1007/978-3-642-35615-5_42