Big Data Computing Framework: A Compact Review

  R K Jena

Advances in information technology and its widespread growth in several areas of business, engineering, medical, and scientific studies are resulting in information/data explosion. Knowledge discovery and decision-making from such rapidly growing voluminous data are a challenging task in terms of data organization and processing, which is an emerging trend known as big data computing, a new paradigm that combines large-scale compute, new data-intensive techniques, and mathematical models to build data analytics. Big data computing demands a huge storage and computing for data curation and processing that could be delivered from on-premise or clouds infrastructures. Therefore a new robust architecture is needed to store and process information. Initially new programing approaches developed based on parallel processing and then distributed computing programing models were developed. This is where Hadoop, Spark, Flink and Storm frameworks are developed and deployed for big data processing since last few years. These platforms are showing promising results. This paper discusses the evolution of big data computing platforms and compare Hadoop, Spark, Flink and Storm framework.

Keywords- Big Data, Hadoop, Spark, Flink and Storm

Unique Identification Number - IJEDR1702280
Page Number(s) - 1781-1789
Pubished in - Volume 5 | Issue 2 | June 2017
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  R K Jena,   "Big Data Computing Framework: A Compact Review", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.5, Issue 2, pp.1781-1789, June 2017, Available at :http://www.ijedr.org/papers/IJEDR1702280.pdf