Abstract

n increasing number of Analytics-as-a-Service solutions has recently seen the light, in the landscape of cloud-based services. These services allow flexible composition of compute and storage components, that create powerful data ingestion and processing pipelines. This work is a first attempt at an experimental evaluation of analytic application performance executed using a wide range of storage service configurations. We present an intuitive notion of data locality, that we use as a proxy to rank different service compositions in terms of expected performance. Through an empirical analysis, we dissect the performance achieved by analytic workloads and unveil problems due to the impedance mismatch that arise in some configurations. Our work paves the way to a better understanding of modern cloud-based analytic services and their performance, both for its end-users and their providers.

Comment: Longer version of the paper in Submission at IEEE CLOUD'16


Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.1109/cloud.2016.0035
https://ui.adsabs.harvard.edu/abs/2016arXiv160207919P/abstract,
https://iris.univr.it/handle/11562/961752,
http://www.eurecom.fr/en/publication/4840/detail/experimental-performance-evaluation-of-cloud-based-analytics-as-a-service,
https://academic.microsoft.com/#/detail/2274638528
Back to Top

Document information

Published on 01/01/2016

Volume 2016, 2016
DOI: 10.1109/cloud.2016.0035
Licence: CC BY-NC-SA license

Document Score

0

Views 2
Recommendations 0

Share this document

claim authorship

Are you one of the authors of this document?