Ophidia: Toward Big Data Analytics for eScience

详细信息    查看全文

• 作者：S. Fiore^a ; ^b ; ^{sandro.fiore@unisalento.it} ; A. D&rsquo ; Anca^a ; C. Palazzo^a ; ^b ; I. Foster^c ; D.N. Williams^d ; G. Aloisio^a ; ^b
• 关键词：data warehouse ; OLAP framework ; parallel computing ; scientific data management ; big data
• 刊名：Procedia Computer Science
• 出版年：2013
• 出版时间：2013
• 年：2013
• 卷：18
• 期：Complete
• 页码：2376-2385
• 全文大小：724 K

文摘

This work introduces Ophidia, a big data analytics research effort aiming at supporting the access, analysis and mining of scientific (n-dimensional array based) data. The Ophidia platform extends, in terms of both primitives and data types, current relational database system implementations (in particular MySQL) to enable efficient data analysis tasks on scientific array-based data. To enable big data analytics it exploits well-known scientific numerical libraries, a distributed and hierarchical storage model and a parallel software framework based on the Message Passing Interface to run from single tasks to more complex dataflows. The current version of the Ophidia platform is being tested on NetCDF data produced by CMCC climate scientists in the context of the international Coupled Model Intercomparison Project Phase 5 (CMIP5).