Article(id=1242138061589520997, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1242138028983005327, articleNumber=null, orderNo=10, doi=10.3981/j.issn.1000-7857.2020.03.007, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1573142400000, receivedDateStr=2019-11-08, revisedDate=1580400000000, revisedDateStr=2020-01-31, acceptedDate=null, acceptedDateStr=null, onlineDate=1585714926537, onlineDateStr=2020-04-01, pubDate=1581523200000, pubDateStr=2020-02-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1585714926537, onlineIssueDateStr=2020-04-01, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774078391688, creator=sys-migrate, updateTime=1774078391688, updator=sys-migrate, issue=Issue{id=1242138028983005327, tenantId=1146029695717560320, journalId=1146031591421210625, year='2020', volume='38', issue='3', pageStart='1', pageEnd='216', issueExtLink='null', onlineDate='null', pubDate='1581523200000', pubDateStr='2020-02-13', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=3, issueType=-1, specialIssue=null, createTime=1774078383914, creator='sys-migrate', updateTime=1774078383914, updator='sys-migrate', preIssue=null, nextIssue=null, articleTotal=null, ext=null, issueFiles=null, downloadFileDto=null}, startPage=103, endPage=114, ext={EN=ArticleExt(id=1242138067021148424, articleId=1242138061589520997, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Big data technologies in open source software: A survey, columnId=1242138034179747997, journalTitle=Science & Technology Review, columnName=Exclusive: Big data strategy, runingTitle=null, highlight=null, articleAbstract=The Google's GFS and Big Table have broken the limitations of the technology of having to use the relational databases to manage the big data in the past decade. A number of open source big data management systems, such as the Apache Hadoop, carry the technology further by developing more matured technologies and applications. This paper reviews the big data management systems in addressing the usage scenarios of the OLTP and the OLAP based on the Apache software, and the state of art of the data storage engine, the data partition, the data replication, the distributed system protocol, together with a comparison of the pros and the cons of the current distributed file system, the key value store, and the time series database., authors=JIANG Tian, QIAO Jialin, HUANG Xiangdong, WANG Jianmin, authorsList=JIANG Tian, QIAO Jialin, HUANG Xiangdong, WANG Jianmin, authorCompany=School of Software, Research Center for Big Data, Tsinghua University;National Engineering Laboratory for Big Data Software, Beijing 100084, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=av3zeGQ11tx/v93nFubrxA==, pdfFileSize=617592, 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=1242138064466813544, articleId=1242138061589520997, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=开源软件中的大数据管理技术, columnId=1242138033248612506, journalTitle=科技导报, columnName=专题：大数据战略, runingTitle=null, highlight=null, articleAbstract=随着谷歌文件系统和宽表结构为代表的技术打破依赖关系数据库管理海量数据的限制，以Apache Hadoop为代表的开源大数据管理系统软件新技术与系统不断涌现，并快速成熟应用。针对Apache开源社区中面向在线事务处理和在线分析处理场景的大数据管理软件，介绍了大数据管理中的数据存储、数据分区、副本机制、分布式协议等，并比较分析了分布式文件系统、键值库、时序数据库等典型分布式数据管理系统的优缺点。, authors=江天, 乔嘉林, 黄向东, 王建民, authorsList=江天, 乔嘉林, 黄向东, 王建民, authorCompany=清华大学软件学院, 大数据研究中心;大数据系统软件国家工程实验室, 北京 100084, correspAuthors=null, authorNote=江天,博士研究生,研究方向为大数据系统,电子信箱:jiangtia18@mails.tsinghua.edu.cn;黄向东,助理研究员,研究方向为分布式系统及时序数据库,电子信箱:huangxdong@tsinghua.edu.cn, correspAuthorsNote=null, copyrightStatement=null, 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