• Prashant Mishra

Although cloud comes with infinite capacity, still optimizing the processes will increase the efficiency of computing infrastructure. In present scenario, enormous data equivalent to the size of peta bytes get induced in micro second, and hence conventional data processing approach will not suffice. For such huge data, big data proves to be a solution. From big consumer stores mining shopper data to Google are using online search through big data. In order to extract information from big data Pig and Hive can be used. The question that arises here is: "What is the need of having both when one can serve the purpose?". In this work, a relative analysis is done between Pig and Hive by utilizing webf visitor data record. For this analysis, web visitor dataset is stored in Hadoop, and later by using MapReduce framework Pig and Hive are configured. Further, for comparing the query execution time, a record of queries is prepared and then experimented on both Pig and Hive. After result analysis it was perceived that query processing time of Hive is less as compared to Pig for the deployed web visitor dataset.

Big Data, Computing Analytics, Hadoop, Hive, Pig.

"A Comparative study of Pig and Hive through Web Visitor Data Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.575-582, June 2019, Available :http://www.jetir.org/papers/JETIR1906K70.pdf

"A Comparative study of Pig and Hive through Web Visitor Data Analytics", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp575-582, June 2019, Available at : http://www.jetir.org/papers/JETIR1906K70.pdf