SCALING BEYOND ONE RACK AND SIZING OF HADOOP PLATFORM

Authors: Litke, W. and Budka, M.

http://eprints.bournemouth.ac.uk/22861/

Journal: Scalable Computing: Practice and Experience (Submitted)

Volume: 17

This data was imported from DBLP:

Authors: Litke, W. and Budka, M.

http://eprints.bournemouth.ac.uk/22861/

Journal: Scalable Computing: Practice and Experience

Volume: 16

Pages: 423-436

This data was imported from Scopus:

Authors: Litke, W. and Budka, M.

http://eprints.bournemouth.ac.uk/22861/

Journal: Scalable Computing

Volume: 16

Issue: 4

Pages: 423-436

ISSN: 1895-1767

DOI: 10.12694/scpe.v16i4.1131

© 2015 SCPE. This paper focuses on two aspects of configuration choices of the Hadoop platform. Firstly we are looking to establish performance implications of expanding an existing Hadoop cluster beyond a single rack. In the second part of the testing we are focusing on performance differences when deploying clusters of different sizes. The study also examines constraints of the disk latency found on the test cluster during our experiments and discusses their impact on the overall performance. All testing approaches described in this work offer an insight into understanding of Hadoop environment for the companies looking to either expand their existing Big Data analytics platform or implement it for the first time.

This source preferred by Marcin Budka

This data was imported from Web of Science (Lite):

Authors: Litke, W. and Budka, M.

http://eprints.bournemouth.ac.uk/22861/

Journal: SCALABLE COMPUTING-PRACTICE AND EXPERIENCE

Volume: 16

Issue: 4

Pages: 423-435

ISSN: 1895-1767

The data on this page was last updated at 17:31 on November 21, 2017.