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Big Data Analytics Using Apache Hive to Analyze Health Data

Big Data Analytics Using Apache Hive to Analyze Health Data
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Author(s): Pavani Konagala (Vaagdevi College of Engineering, India)
Copyright: 2019
Pages: 15
Source title: Nature-Inspired Algorithms for Big Data Frameworks
Source Author(s)/Editor(s): Hema Banati (Dyal Singh College, India), Shikha Mehta (Jaypee Institute of Information Technology, India) and Parmeet Kaur (Jaypee Institute of Information Technology, India)
DOI: 10.4018/978-1-5225-5852-1.ch015


View Big Data Analytics Using Apache Hive to Analyze Health Data on the publisher's website for pricing and purchasing information.


A large volume of data is stored electronically. It is very difficult to measure the total volume of that data. This large amount of data is coming from various sources such as stock exchange, which may generate terabytes of data every day, Facebook, which may take about one petabyte of storage, and internet archives, which may store up to two petabytes of data, etc. So, it is very difficult to manage that data using relational database management systems. With the massive data, reading and writing from and into the drive takes more time. So, the storage and analysis of this massive data has become a big problem. Big data gives the solution for these problems. It specifies the methods to store and analyze the large data sets. This chapter specifies a brief study of big data techniques to analyze these types of data. It includes a wide study of Hadoop characteristics, Hadoop architecture, advantages of big data and big data eco system. Further, this chapter includes a comprehensive study of Apache Hive for executing health-related data and deaths data of U.S. government.

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