MHBase: A Distributed Real-Time Query Scheme for Meteorological Data Based on HBase

Tinghuai Ma, Xichao Xu, Meili Tang, Yuanfeng Jin and Wenhai Shen
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Tinghuai Ma: Jiangsu Engineering Centre of Network Monitoring, Nanjing University of information Science and Technology, Nanjing 210044, Jiangsu, China
Xichao Xu: School of Computer Software, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China
Meili Tang: School of Public Administration, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China
Yuanfeng Jin: Departmet of Mathmatics, YanBian University, Yanji 133002, Jilin, China
Wenhai Shen: National Meteorological Information Center, Beijing 100080, China

Future Internet, 2016, vol. 8, issue 1, 1-14

Abstract: Meteorological technology has evolved rapidly in recent years to provide enormous, accurate and personalized advantages in the public service. Large volumes of observational data are generated gradually by technologies such as geographical remote sensing, meteorological radar satellite, etc. that makes data analysis in weather forecasting more precise but also poses a threat to the traditional method of data storage. In this paper, we present MHBase, (Meteorological data based on HBase (Hadoop Database), a distributed real-time query scheme for meteorological data based on HBase. The calibrated data obtained from terminal devices will be partitioned into HBase and persisted to HDFS (the Hadoop Distributed File System). We propose two algorithms ( the Indexed Store and the Indexed Retrieve Algorithms ) to implement a secondary index using HBase Coprocessors, which allow MHbase to provide high performance data querying on columns other than rowkey. Experimental results show that the performance of MHBase can satisfy the basic demands of meteorological business services.

Keywords: meteorological data; distributed storage; HBase; secondary index (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2016
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