Name node performance enlarging by aggregator based HADOOP framework
Bibhudutta Jena, Mahendra Kumar Gourisaria, Siddharth Swarup Rautaray, Manjusha Pandey · 2017 International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) · 2017
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 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.