A high performance query analytical framework for supporting data-intensive climate studies

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• 作者：Zhenlong Li^a ; ^{zhenlong@sc.edu} ; Qunying Huang^b ; ^{qhuang46@wisc.edu} ; Gregory J. Carbone^a ; ^{carbone@mailbox.sc.edu} ; Fei Hu^c ; ^fhu@gmu.edu
• 关键词：Big data ; Cyberinfrastructure ; Climate analysis ; Query analytics ; Cloud computing ; Hive
• 刊名：Computers, Environment and Urban Systems
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：62
• 期：Complete
• 页码：210-221
• 全文大小：1641 K
• 卷排序：62

文摘

We propose a high performance query analytical framework to support data-intensive climate applications. We introduce a new perspective for complex climate data analysis that applies a series of grid transformations to terabytes of climate data. Four types of grid transformations (temporal, spatial, local, and arithmetic) are introduced to support a broad range of climate analyses.