Physical Sciences and Mathematics Commons^™

Hadoop And Hive As Scalable Alternatives To Rdbms: A Case Study, Marissa Rae Hollingsworth

Computer Science Graduate Projects and Theses

While high-performance, cost-effective data management solutions, such as Hadoop, exist for Big Data analysis, small and medium businesses with moderate-sized data sets would also like to implement low budget data management systems that will perform well on existing data and scale as the amount of accumulated data increases. Parallel database management systems may provide a high-performance solution, but are expensive and complex to implement. The purpose of this project was to compare the scalability of open-source relational database management systems and distributed data management systems for small and medium data sets. To make this comparison, a business intelligence case study …

Clayui: A Framework For Delivering Object Properties To Native Mobile Application Components, Andrew Lize

Master's Theses (2009 -)

As technology advances in the field of mobile computing with smartphones and tablet computers becoming less expensive, people are adopting these devices into their daily lives. Due to this adoption, many developers are finding opportunities to develop apps that target this growing form factor. One of the issues that developers come across when developing for these multiple platforms is that there is a need to redesign common elements of their applications for each of their platforms. They are also challenged with the decision of breaking the prescribed design guidelines for each of the platforms they are developing for so that …

An Extensible And Scalable Pilot-Mapreduce Framework For Data Intensive Applications On Distributed Cyberinfrastructure, Pradeep Kumar Mantha

LSU Master's Theses

The volume and complexity of data that must be analyzed in scientific applications is increasing exponentially. Often, this data is distributed; thus, the ability to analyze data by localizing it will yield limited returns. Therefore, an efficient processing of large distributed datasets is required, whilst ideally not introducing fundamentally new programming models or methods. For example, extending MapReduce - a proven effective programming model for processing large datasets, to work more effectively on distributed data and on different infrastructure (such as non-Hadoop, general-purpose clusters) is desirable. We posit that this can be achieved with an effective and efficient runtime environment …

Semantically-Aware Data Discovery And Placement In Collaborative Computing Environments, Xinqi Wang

LSU Doctoral Dissertations

As the size of scientific datasets and the demand for interdisciplinary collaboration grow in modern science, it becomes imperative that better ways of discovering and placing datasets generated across multiple disciplines be developed to facilitate interdisciplinary scientific research.

For discovering relevant data out of large-scale interdisciplinary datasets. The development and integration of cross-domain metadata is critical as metadata serves as the key guideline for organizing data. To develop and integrate cross-domain metadata management systems in interdisciplinary collaborative computing environment, three key issues need to be addressed: the development of a cross-domain metadata schema; the implementation of a metadata management system …