DOCUMENT SELECTION USING MAPREDUCE

Big data is used for structured, unstructured and semi-structured large volume of data which is difficult to manage and costly to store. Using explanatory analysis techniques to understand such raw data, carefully balance the benefits in terms of storage and retrieval techniques is an essential part of the Big Data. The research discusses the MapReduce issues, framework for MapReduce programming model and implementation. The paper includes the analysis of Big Data using MapReduce techniques and identifying a required document from a stream of documents. Identifying a required document is part of the security in a stream of documents in the cyber world. The document may be significant in business, medical, social, or terrorism.