{"title":"Hadoop分布式文件系统","authors":"K. Shvachko, Hairong Kuang, S. Radia, R. Chansler","doi":"10.1109/MSST.2010.5496972","DOIUrl":null,"url":null,"abstract":"The Hadoop Distributed File System (HDFS) is designed to store very large data sets reliably, and to stream those data sets at high bandwidth to user applications. In a large cluster, thousands of servers both host directly attached storage and execute user application tasks. By distributing storage and computation across many servers, the resource can grow with demand while remaining economical at every size. We describe the architecture of HDFS and report on experience using HDFS to manage 25 petabytes of enterprise data at Yahoo!.","PeriodicalId":350968,"journal":{"name":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5169","resultStr":"{\"title\":\"The Hadoop Distributed File System\",\"authors\":\"K. Shvachko, Hairong Kuang, S. Radia, R. Chansler\",\"doi\":\"10.1109/MSST.2010.5496972\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Hadoop Distributed File System (HDFS) is designed to store very large data sets reliably, and to stream those data sets at high bandwidth to user applications. In a large cluster, thousands of servers both host directly attached storage and execute user application tasks. By distributing storage and computation across many servers, the resource can grow with demand while remaining economical at every size. We describe the architecture of HDFS and report on experience using HDFS to manage 25 petabytes of enterprise data at Yahoo!.\",\"PeriodicalId\":350968,\"journal\":{\"name\":\"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)\",\"volume\":\"36 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-05-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5169\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MSST.2010.5496972\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MSST.2010.5496972","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Hadoop Distributed File System (HDFS) is designed to store very large data sets reliably, and to stream those data sets at high bandwidth to user applications. In a large cluster, thousands of servers both host directly attached storage and execute user application tasks. By distributing storage and computation across many servers, the resource can grow with demand while remaining economical at every size. We describe the architecture of HDFS and report on experience using HDFS to manage 25 petabytes of enterprise data at Yahoo!.
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