{"title":"HDFSbench:了解云文件系统的效率和瓶颈","authors":"J. Dai, T. Xie, Shengsheng Huang, Jie Huang","doi":"10.1109/OCS.2012.31","DOIUrl":null,"url":null,"abstract":"We have conducted intensive experiments on an in-house Hadoop cluster using HDFSbench (a file system benchmark tool we build for HDFS). Our experimental results provide valuable insights into the performance characteristics (e.g., general efficiency and potential bottlenecks) of cloud file systems for different application usages (e.g., MapReduce and Bigtable access patterns), and on how these traits change with new storage technologies (e.g., SSD vs. HDD).","PeriodicalId":244833,"journal":{"name":"2012 7th Open Cirrus Summit","volume":"77 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"HDFSbench: Understanding the Efficiency and Bottlenecks of Cloud File Systems\",\"authors\":\"J. Dai, T. Xie, Shengsheng Huang, Jie Huang\",\"doi\":\"10.1109/OCS.2012.31\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have conducted intensive experiments on an in-house Hadoop cluster using HDFSbench (a file system benchmark tool we build for HDFS). Our experimental results provide valuable insights into the performance characteristics (e.g., general efficiency and potential bottlenecks) of cloud file systems for different application usages (e.g., MapReduce and Bigtable access patterns), and on how these traits change with new storage technologies (e.g., SSD vs. HDD).\",\"PeriodicalId\":244833,\"journal\":{\"name\":\"2012 7th Open Cirrus Summit\",\"volume\":\"77 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 7th Open Cirrus Summit\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/OCS.2012.31\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 7th Open Cirrus Summit","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/OCS.2012.31","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
HDFSbench: Understanding the Efficiency and Bottlenecks of Cloud File Systems
We have conducted intensive experiments on an in-house Hadoop cluster using HDFSbench (a file system benchmark tool we build for HDFS). Our experimental results provide valuable insights into the performance characteristics (e.g., general efficiency and potential bottlenecks) of cloud file systems for different application usages (e.g., MapReduce and Bigtable access patterns), and on how these traits change with new storage technologies (e.g., SSD vs. HDD).