• Corpus ID: 212599048

Performance Evaluation of BigData Analysis with Hadoop in Various Processing Systems

  title={Performance Evaluation of BigData Analysis with Hadoop in Various Processing Systems},
  author={Ms. Preeti Narooka and S. Choudhary},
In recent years BigData has become most popular area for research and development. In Business, Organizations need to focus towards their data-driven approach for gaining the competitive advantage. When more data is processing, interacting and integrating it provides meaningful data for making good decision. All this happened with the advent of advanced computational and storage system required for BigData . On one side BigData help in giving a panoramic view on decision making, on other side… 

Performance Evaluation Of Application Specific Big Data Systems With Multi-domain Big Data Framework Using Machine Learning

The research presented evaluates the big data platforms with novel muti-domain big data framework using the available techniques for security and other challenges to provide scalable and efficient results as compared to the traditional platforms and techniques.



Big data: Issues, challenges, tools and Good practices

The various challenges and issues in adapting and accepting Big data technology, its tools (Hadoop) are discussed in detail along with the problems Hadoop is facing.

Hadoop: The Definitive Guide

This comprehensive resource demonstrates how to use Hadoop to build reliable, scalable, distributed systems: programmers will find details for analyzing large datasets, and administrators will learn how to set up and run Hadoops clusters.

Media Monitoring Using Social Networks

The solution, BlogCrawler, attempts to use the properties of social networks to narrow the focus of search queries to only those blogs that the user is interested in, while allowing for general keyword queries.

A survey of large-scale analytical query processing in MapReduce

A taxonomy is presented for categorizing existing research on MapReduce improvements according to the specific problem they target, and interesting directions for future parallel data processing systems are outlined.

Survey of Recent Research Progress and Issues in Big Data

Most recent progress on big data networking and big data in cloud computing is revealed and interesting benchmarks and progress in both search engines and mobile networking are introduced.

Improving MapReduce performance through data placement in heterogeneous Hadoop clusters

  • Jiong XieShu Yin X. Qin
  • Computer Science
    2010 IEEE International Symposium on Parallel & Distributed Processing, Workshops and Phd Forum (IPDPSW)
  • 2010
The problem of how to place data across nodes in a way that each node has a balanced data processing load is addressed, and it is shown that ignoring the data-locality issue in heterogeneous environments can noticeably reduce the MapReduce performance.

Evaluating MapReduce for Multi-core and Multiprocessor Systems

It is established that, given a careful implementation, MapReduce is a promising model for scalable performance on shared-memory systems with simple parallel code.

BigData, Bigger Opportunities

  • Available:http://www.meritalk.com/pdfs/bdx/bdx-whitepaper- 090413.pdf
  • 2013

BigData: Issues, Challenges, Tools and Good Practices”, Department of CSE, Graphic Era University, Dehradun

  • 2005

BigData Framework

  • International Conference on Systems, Man, and Cybernetics,
  • 2013