Article(id=1242136457398268876, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242136426431718263, articleNumber=null, orderNo=19, doi=10.3981/j.issn.1000-7857.2017.20.014, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1506268800000, receivedDateStr=2017-09-25, revisedDate=1507564800000, revisedDateStr=2017-10-10, acceptedDate=null, acceptedDateStr=null, onlineDate=1509418036843, onlineDateStr=2017-10-31, pubDate=1509120000000, pubDateStr=2017-10-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1509418036843, onlineIssueDateStr=2017-10-31, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774078009217, creator=sys-migrate, updateTime=1774078009217, updator=sys-migrate, issue=Issue{id=1242136426431718263, tenantId=1146029695717560320, journalId=1146031591421210625, year='2017', volume='35', issue='20', pageStart='1', pageEnd='140', issueExtLink='null', onlineDate='null', pubDate='1509120000000', pubDateStr='2017-10-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774078001837, creator='sys-migrate', updateTime=1774078001837, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=126, endPage=133, ext={EN=ArticleExt(id=1242136462951527392, articleId=1242136457398268876, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Open source big data framework in marine information processing, columnId=1242135221613703813, journalTitle=Science & Technology Review, columnName=Special lssues, runingTitle=null, highlight=null, articleAbstract=With the rapid development of China's sea observation technologies and data collection methods, we have an ever expanding amount of observed data with more and more complexity. Therefore, the traditional data storage and processing techniques cannot effectively manage and analyze the big ocean data. Meanwhile, the regionalization and the distribution of these data become an challenge for a unified data management, during the data mining process. From the perspective of the big data life cycle, this paper reviews the technical principles of the existing open source big data framework in areas of data acquisition, storage, processing, intelligent analysis, security protection and data governance, focusing on their applications for the big ocean data., authors=FAN Luyao¹, ZHANG Jing¹, CHEN Xiaolong², LIU Chi¹, authorsList=FAN Luyao, ZHANG Jing, CHEN Xiaolong, LIU Chi, authorCompany=1. School of Software, Beijing Institute of Technology, Beijing 100081, China;
2. Department of Electronic and Information Engineering, Naval Aeronautical and Astronautical University, Yantai 264001, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=0mf05JHy6DbnOHmQzEZhhQ==, pdfFileSize=2820206, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242136460577551316, articleId=1242136457398268876, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=开源大数据框架在海洋信息处理中的应用, columnId=1242116902361830275, journalTitle=科技导报, columnName=专题论文, runingTitle=null, highlight=null, articleAbstract=随着中国海洋观测技术和数据收集手段的发展，海洋观测数据量日益庞大、数据复杂程度逐渐增多，传统的数据存储方式和处理方法无法有效地对海洋数据进行管理和分析，同时，数据的区域化和分布化成为海洋数据统一管理的一个障碍，对海洋数据挖掘造成一定困难。本文从大数据生命周期的维度，介绍了主流开源大数据框架在海洋大数据获取、存储、处理、智能分析、安全保护和治理方面的技术原理和应用。, authors=樊路遥¹, 张晶¹, 陈小龙², 刘驰¹, authorsList=樊路遥, 张晶, 陈小龙, 刘驰, authorCompany=1. 北京理工大学软件学院, 北京 100081;
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