Huge amount of data is being generated in almost every field and it cannot be avoided, rather is essential for the advancement of the field. Analysis of this data requires intensive computing power. Molecular Simulation is a powerful tool for understanding the behavior of natural systems. The simulation generates large amount data while observing the spatial and temporal relationships. The challenge is to handle the analytical queries that are often compute intensive.
Although various tools exist to tackle this problem, but in this paper we have tried an alternate approach that uses Apache Spark- a modern big data platform – to parallelize the computation of analytical queries. MsSpark consists of three layers: Apache Spark layer, MS RDD layer and MS Query Processing layer. MS RDD layers supports data that is specific to Molecular Simulation. MS Query Processing layer provides functionality of executing analytical queries. Caching is used to improve the performance. The system can be further extended to cover more analytical queries.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-7468 |
| Date | 24 June 2016 |
| Creators | Kaur, Parneet |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
| Rights | default |
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