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大数据环境下地震观测数据存储方案研究
单维锋1,2, 滕云田1, 刘海军2, 杨冠泽2
1.中国地震局地球物理研究所, 北京 100081;2.防灾科技学院, 河北三河 065201
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OpenTSDB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OpenTSDB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。
关键词:  大数据  地震  Hadoop  HBase  OpenTSDB  并发
DOI:
分类号:P315
基金项目: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
Storage Solution of Earthquake Observation Data in Big Data Environment
Shan Weifeng1,2, Teng Yuntian1, Liu Haijun2, Yang Guanze2
1.Institute of Geophysics, China Earthquake Administration, Beijing 100081, China;2.Institute of Disaster Prevention, Sanhe 065201, Hebei, China
Abstract:
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.
Key words:  Big data  Earthquake  Hadoop  HBase  OpenTSDB  Concurrency