Analyzing Performance of Apache Pig and Apache Hive with Hadoop

Big Data is the term used for huge datasets which are very complex in nature and difficult to be processed using traditional devices. The current requirement is for a new technology for analyzing these huge datasets. One of the best options is Apache Hadoop as it consists of various components which work simultaneously to provide an efficient and robust Hadoop ecosystem. Apache Pig and Apache Hive are core components of Hadoop ecosystem that facilitate specification and search of processing tasks. Apache Hive facilitates to run queries and manage huge datasets using simple commands similar to SQL. Apache Pig is a scripting platform which creates MapReduce programs utilized with Hadoop. In our previous work, we had analyzed and compared both these components to identify benefits and drawbacks on the basis of some parameters. We have showcased analysis of previously conducted research by various researchers. In this paper, we have carried out the analysis by utilizing both these components installed on Hadoop with large dataset as an input.