{"title":"基于Amazon EC2集群和Hadoop的地震大数据公有云存储","authors":"Jie Xiong, Song Zhang","doi":"10.14257/ijdta.2017.10.5.01","DOIUrl":null,"url":null,"abstract":"The seismic data expanded rapidly in recent years, whose size could be up to hundreds TBs, as modern seismic aquisition technologies were employed. How to store and access the seismic big data efficiently is an emergency problem for the oil industry and scientific research. A public cloud storage scheme for the seismic big data is proposed based on the Amazon EC2 and Hadoop. The IO performance evaluation results show that the proposed public cloud storage scheme has advantages of high IO performance and good scalability. It is suitable for the seismic big data storage and access.","PeriodicalId":13926,"journal":{"name":"International journal of database theory and application","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Public Cloud Storage for the Seismic Big Data Based on Amazon EC2 Cluster and Hadoop\",\"authors\":\"Jie Xiong, Song Zhang\",\"doi\":\"10.14257/ijdta.2017.10.5.01\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The seismic data expanded rapidly in recent years, whose size could be up to hundreds TBs, as modern seismic aquisition technologies were employed. How to store and access the seismic big data efficiently is an emergency problem for the oil industry and scientific research. A public cloud storage scheme for the seismic big data is proposed based on the Amazon EC2 and Hadoop. The IO performance evaluation results show that the proposed public cloud storage scheme has advantages of high IO performance and good scalability. It is suitable for the seismic big data storage and access.\",\"PeriodicalId\":13926,\"journal\":{\"name\":\"International journal of database theory and application\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of database theory and application\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.14257/ijdta.2017.10.5.01\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of database theory and application","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14257/ijdta.2017.10.5.01","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Public Cloud Storage for the Seismic Big Data Based on Amazon EC2 Cluster and Hadoop
The seismic data expanded rapidly in recent years, whose size could be up to hundreds TBs, as modern seismic aquisition technologies were employed. How to store and access the seismic big data efficiently is an emergency problem for the oil industry and scientific research. A public cloud storage scheme for the seismic big data is proposed based on the Amazon EC2 and Hadoop. The IO performance evaluation results show that the proposed public cloud storage scheme has advantages of high IO performance and good scalability. It is suitable for the seismic big data storage and access.
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