Query Execution Performance Analysis of Big Data Using Hive and Pig of Hadoop - Choudhary, Anshu; Satsangi, CS (International Journal of Computer Sciences and Engineering, 2025)
The cloud platform requires an efficient computational infrastructure. On this platform a huge amount of data gets generated in a fraction of a second, therefore, traditional computing techniques are not enough. The Big Data provides an answer for such huge computing and also provides support to scale the storage according to the application’s need. Big Data is a new generation storage infrastructure (hardware and software). In this paper the Big Data environment is investigated and the comparative study is performed among most frequently used data retrieval techniques. In order to perform the comparative study, Pig and Hive of Hadoop technology are selected. These techniques provide efficient data processing ability. In order to perform comparative study Hadoop storage is prepared first and then with the help of MapReduce framework the Pig and Hive are configured. Additionally, for evaluating the efficiency of query execution in terms of processing time, a list of similar queries is prepared and for each query the experiment was performed. The result evaluation is done for both the techniques. It is observed that query processing time of the Hive is less as compared to the Pig for the selected new_songs dataset, but both the data models are working to achieve the different goals thus both the technologies are adaptable for different kinds of computer configuration.