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大数据环境下地震观测数据存储方案研究 被引量:7

Storage Solution of Earthquake Observation Data in Big Data Environment
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摘要 大数据技术为处理海量地震观测数据提供了一种新的数据存储与计算模式。为了解决现有基于关系数据库存储方案的读写速度低、用户并发度低和可扩展性差等问题,以地震前兆观测数据为例,在详细分析业务需求的基础上,提出了基于HBase和Open TSDB的地震大数据存储方案,搭建了大数据测试平台,完成了不同存储方案下查询、插入性能实验和并发性实验。实验结果表明,与关系数据库存储方案相比,基于HBase和Open TSDB的存储方案具有很好的可扩展性和并发性,经过优化后的HBase存储方案具有更高的读取和存储性能。 The big data technology provides a new data storage solution and computing model for processing massive seismic observation data. In order to solve the problems of low read/write speed,low concurrency performance and poor scalability of existing storage schemes based on relational database,we take earthquake precursor observation data as an example,and analysis of the business requirements in detail,and then propose the two earthquake big data storage solutions based on HBase and OpenTSDB. We also construct a test platform to compare the query,insertion and concurrency performance under different storage schemes. The experimental results show that HBase and OpenTSDB-based storage schemes have better scalability and concurrency performance than relational database storage scheme,and HBase-based storage schemes have the best read and storage performance.
作者 单维锋 滕云田 刘海军 杨冠泽 Shan Weifeng;Teng Yuntian;Liu Haijun;Yang Guanze(Institute of Geophysics,China Earthquake Administration,Beijing 100081,China;Institute of Disaster Prevention,Sanhe 065201,Hebei,China)
出处 《中国地震》 北大核心 2019年第3期558-564,共7页 Earthquake Research in China
基金 地震科技星火计划项目(XH16059) 河北省重点研发计划(16210126) 中央高校基本科研业务费项目(ZY20160106) 国家重点研发计划(2018YFC1503806)共同资助
关键词 大数据 地震 HADOOP HBASE OpenTSDB 并发 Big data Earthquake Hadoop HBase OpenTSDB Concurrency
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