{"title":"使用Hadoop, HDFS和c++创建分布式高维索引","authors":"G. Gudmundsson, L. Amsaleg, B. Jónsson","doi":"10.1109/CBMI.2012.6269848","DOIUrl":null,"url":null,"abstract":"This paper describes an initial study where the open-source Hadoop parallel and distributed run-time environment is used to speedup the construction phase of a large high-dimensional index. This paper first discusses the typical practical problems developers may run into when porting their code to Hadoop. It then presents early experimental results showing that the performance gains are substantial when indexing large data sets.","PeriodicalId":120769,"journal":{"name":"2012 10th International Workshop on Content-Based Multimedia Indexing (CBMI)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Distributed high-dimensional index creation using Hadoop, HDFS and C++\",\"authors\":\"G. Gudmundsson, L. Amsaleg, B. Jónsson\",\"doi\":\"10.1109/CBMI.2012.6269848\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes an initial study where the open-source Hadoop parallel and distributed run-time environment is used to speedup the construction phase of a large high-dimensional index. This paper first discusses the typical practical problems developers may run into when porting their code to Hadoop. It then presents early experimental results showing that the performance gains are substantial when indexing large data sets.\",\"PeriodicalId\":120769,\"journal\":{\"name\":\"2012 10th International Workshop on Content-Based Multimedia Indexing (CBMI)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-06-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 10th International Workshop on Content-Based Multimedia Indexing (CBMI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBMI.2012.6269848\",\"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 10th International Workshop on Content-Based Multimedia Indexing (CBMI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMI.2012.6269848","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Distributed high-dimensional index creation using Hadoop, HDFS and C++
This paper describes an initial study where the open-source Hadoop parallel and distributed run-time environment is used to speedup the construction phase of a large high-dimensional index. This paper first discusses the typical practical problems developers may run into when porting their code to Hadoop. It then presents early experimental results showing that the performance gains are substantial when indexing large data sets.
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