Testing framework for big data leveraging Cloud
Abstract
This research aims to cover the following:
- Formulate big data strategy for testing in cloud
- Develop a framework for testing Big Data engagements
- Validating selected scopes for Big Data
- Address sustainability in measuring various test results
Intellectual Merit
This work will involve studying the big data testing strategy and apply key learning to leverage existing testing methodlogies to cloud platfrom. This can bring us to a very clear alternative to traditional approach. In traditional approach, there are several challenges in terms of validation of data traversal and load testing. Big data involves distrbuted nosql databases instance. For this we leverage Hadoop. With the combination of Talend (open source Big data tool) and Hadoop, we can explore list of big data tasks work flow. Following this, we will develop a framework to validate and verify the workflow, tasks and tasks complete. We will also identify the testing tool to be used for this operation
Broader Impact
The main key features that leverage Bigdata test framework in cloud are
• On demand hadoop testbed to test Big data
• Virtualized application / service availability that need to be tested
• Virtualized testing tool suite-Talend and jmeter
• Managed test life cycle in Cloud
• Different types of Big Data test metrics in cloud
• Operations like import / export configurations and test artifacts in / out of the testbed
Use of FutureGrid
This course will offer Big data testing framework delivered from to support metrics aroung big data . Students will get to know the latest research topics of big data testing including (in-memory hadoop fundamentals) and have the opportunity to understand this framework along with some open source cloud testbed through projects using FutureGrid resources.
Scale Of Use
Modest resources for each student
Futuregrid is a resource provider for