A Contemplating approach for Hive and Map reduce for efficient Big Data Implementation
Journal Title: Annals of Computer Science and Information Systems - Year 2018, Vol 14, Issue
Abstract
In the reference current scenario, data is incremented exponentially and speed of data accruing at the rate of petabytes. Big data defines the available amount of data over the different media or wide communication media internet. Big Data term refers to the explosion in the quantity (and quality) of available and potentially relevant data. On the basis of quantity amount of data are very huge and this quantity has been handled by conventional database systems and data warehouses because the amount of data increases similarly complexity with it also increases. Multiple areas are involved in the production, generation, and implementation of Big Data such as news media, social networking sites, business applications, industrial community, and much more. Some parameters concern with the handling of Big Data like Efficient management, proper storage, availability, scalability, and processing. Thus to handle this big data, new techniques, tools, and architecture are required. In the present paper, we have discussed different technology available in the implementation and management of Big Data. This paper contemplates an approach formal tools and techniques used to solve the major difficulties with Big Data, This evaluate different industries data stock exchange to covariance factor and it tells the significance of data through covariance positive result using hive approach and also how much hive approach is efficient for that in the term of HDFS and hive query. and also evaluates the covariance factors after applying hive and map reduce approaches with stock exchange dataset of around 3500.After process data with the hive approach we have conclude that hive approach is better than map reduce and big table in terms of storage and processing of Big Data.
Authors and Affiliations
Gopinadh Sasubilli, Uday Shankar Sekhar, Ms. Surbhi Sharma, Ms. Swati Sharma
Keywords
Related Articles
- EP ID EP569750
- DOI 10.15439/2017KM20
- Views 31
- Downloads 0
Real Time Risk Monitoring in Fine-art with IoT Technology
This work presents a bespoke system used to monitor inter-modal logistics within the fine arts industry. A custom IoT architecture provides end-to-end capabilities allowing continuous risk assessment during storage, hand...
Proposal for simplified implementation of risk assessment method for measuring instruments
Legal Metrology is the economic sector where measuring instruments subject to legal control (taximeters, electricity meters, etc.) are used. In this field, constant growth of Measuring Instruments using ICT technology is...
Data Compression Measures for Meta-Learning Systems
An important issue in building predictive models is the ability to quickly assess various aspects of the achievable performance of the model to know what outcome we can expect and how to optimally build the model. As ins...
An Innovative B2C E-commerce Websites Selection using the ME-OWA and Fuzzy AHP
Today internet has emerged as a huge marketplace of products and services for meeting needs of more than a million customers worldwide. It provides users a platform to access information globally in electronic form as we...
Static typing and dependency management for SOA
Several problems related to work reliability appear while building service-oriented systems. The first problem consists in lack of static typing and lack of inter-service data type checking. The second one consists in hi...