Empirical Aspect to Analyze Stock Exchange Banking Data using Apache Pig in HDFS environment
Yogesh Kumar Gupta, Shruti Sharma · 2019
In the current era IT enabled world, term "Big Data" is a new concept used to define the collection of data set which is large and complex. There are different sources defined which generates huge amount of data on daily basis like social media, stock exchange, medical science or clinical healthcare data which are elaborated in distributed fashion around the world. In this paper change on data by size may require new tools and storage methods to overcome the problem of storing and processing big data. Hadoop is an open source framework to analyze massive volume of data. One of the precious components of Hadoop is Apache Pig. Pig processes the data in the form of Latin script. We attempt to inspect stock exchange data of banking sector using Pig. In this observation, we worked on yearly data to come across 52 week low, high, average data and perceive the mapper and reducer time with the help of pig latin script for the banking data. All the observed result presented in the graphical form. In the research, we considered data of 6 years of different banks such as AXIS, HDFC, ICICI, and SBI.