Improvising name node performance by aggregator aided HADOOP framework

Abstract

Due to the increased market competition increased data management and analysis has landed as in an era that requires further optimization data management and analysis. Big data technologies like apache HADOOP provide a frame work for parallel data processing and generation of analyzed results. MAPREDUCE method is used for analysis of data using various data analysis algorithms like clustering, fragmentation and aggregation. As per the HADOOP architecture the data received from client is distributed to various data node by the name node and it is the responsibility of name node to track the task being performed by a data nodes through a task-tracker, The presented proposal for “Improvising Name Node Performance By Aggregator Aided HADOOP Framework” aims to reduce the burden on name node in the HADOOP architecture by providing the assistance through aggregator node which act as interface between the name node & data node.