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Hadoop Namenode: Single Point of Failure


Snehal U. Vathiyath , SIES College of Management Studies


HDFS, NameNode, Secondary NameNode, ZattaByte, Overcome Single Point of Failure, BigData


Nowadays, Companies generates large amount of unstructured data in the form of logs, comments, chats etc. So there is a need to process Multi Zattabyte datasets efficiently. Here the best solution would be to choose Hadoop, Open Source Apache Software Foundation. Basically, it’s a way of storing enormous datasets across distributed clusters of servers and then running “distributed” analysis applications in each clusters which attracts it the most. Hadoop is a popular open-source implementation of MapReduce for the analysis of large datasets. The problem defined in this paper is that of Single Point of Failure of NameNode which is master of the HDFS cluster. The actual challenge is I/O speed for analysing the data and not the storage capacity. This paper develops a novel for overcoming the Single Point of Failure in NameNode. The optimal solution to this problem is the minimal overhead on NameNode. The novality is in achieving a hierarchical storage of the HDFS system. The conceptual result illustrates the faster and accurate service of proposed framework.

Other Details

Paper ID: IJSRDV4I50402
Published in: Volume : 4, Issue : 5
Publication Date: 01/08/2016
Page(s): 757-759

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