SCDP: Scalable, cost-effective, distributed and parallel computing model for academics
Ratnamala Mantri, Rajesh Ingle, Prachi Patil · 2011
The academic institutes or universities have to maintain the student's record during and even after their completion of studies. This results in a vast amount of data and subsequently increases the cost and response time. In order to process such vast amount of academic data effectively and efficiently, we have proposed use of Hadoop MapReduce programming model. Hadoop is an open source implementation of MapReduce which process vast amount of data in parallel on large clusters of commodity hardware. In this paper we also demonstrated processing of student's attendance with different keys.