The final section of this paper compares and concludes both techniques. In part III, a map-reduce job using Hive is discussed. In part II, a map-reduce job using Pig has been explained.
In this paper, first of all, the basic concepts of Pig and Hive are introduced. Apache Pig and Hive are two projects which are layered on top of Hadoop, and provide higher-level language to use Hadoop’s MapReduce library. In this paper, a thorough work has been carried to discuss that how big data analytics can be performed on data stored on Hadoop distributed file system. It provides a framework for storing data in a distributed environment and also has set of tools to retrieve and process. In big data world, Hadoop Distributed File System (HDFS) is very popular. So here we are taking modular analysis, for this we are using hadoop tools. And, coming to analysis there are different types of analysis that can be done on the collected data. And doing analysis on Twitter is also difficult due to language that is used for comments. We can collect the data from the twitter by using BIGDATA eco-system using hadoop. As we see Twitter is an online web application which contains rich amount of data that can be a structured, semi structured and un-structured data. As of now we know present industries and some survey companies are mainly taking decisions by data obtained from web.
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