An efficient way of solving Bigdata using Hadoop & Map Reduce

Abstract

Big Data is a collection of data that is huge in volume, yet growing exponentially with time. It is a data with so large size and complexity that none of traditional data management tools can store it or process it efficiently. Big data is also a data but with huge size.Big data is dataset that having the ability to capture, manage & process the data in elapsed time .Managing the data is the big issue. And now days the huge amount of data is produced in the origination so the big data concept is in picture. It is data set that can manage and process the data. For managing the data the big data there are many technique are used .One of this technique is Hadoop. Hadoop can handle the huge amount of data, it is very cost effective, and it can handle huge amount of data so processing speed is very fast, and also it can create a duplicate copy of data in case of system failure or to prevent the loss of data.This paper gives the Introduction of big data and Hadoop, characteristics of big data ,problem associated with big data, architecture of big data and Hadoop, other component of hadoop like pig,hive,HBase and the advantages, disadvantages and applications of Hadoop and also the conclusion.