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A Survey of Mapreduce based Optimized Semantic Search in Hadoop Environment

Author(s):

Sejal Dave , Rollwala Computer Centre, Ahmedabad, India; Dr. Chirag S. Thaker, Shantilal Shah Engg. College, Bhavnagar, India

Keywords:

Hadoop, Semantic Search, Map reduce

Abstract

Now-a-days the data has become bigger because of E-commerce and Social Networking sites. So, there is a need to handle such big data and it has to be analyzed in such a way that it can produce some useful information which can be used in some kind of decision making. MapReduce framework has emerged as one of the most widely used parallel computing platforms for processing data on terabyte and petabyte scales. Users specify a map function that processes a key/value pair to generate a set of intermediate key/value pairs, and a reduce function that merges all intermediate values associated with the same intermediate key. Today Map Reduce has been used daily at companies such as Yahoo!, Google, Amazon, and Facebook, and adopted more recently by several universities, it allows for easy parallelization of data intensive computations over many machines. There are many algorithms for retrieving the information using MapReduce like Sorting, Searching, TF-IDF, BFS, and Page-Rank etc Hadoop is a distributed file system where files can be saved with replication. It provides high fault tolerance and reliability. Moreover, it provides an implementation of MapReduce programming model. Hadoop can work directly with any distributed file system which can be mounted by the underlying OS. Hadoop-MapReduce can handle huge amount of data. Scalability is a matter of concern for a long time. Same is true for semantic web data. We can store huge amount of semantic web data in Hadoop clusters built mostly by cheap commodity class hardware and still can answer queries fast enough. The aim of this survey is improving the performance of parallel query processing using MapReduce.

Other Details

Paper ID: IJSRDV2I1349
Published in: Volume : 2, Issue : 1
Publication Date: 01/04/2014
Page(s): 528-531

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