Comparing Hadoop and Fat-Btree based access method for Small File I/O Applications
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概要
- 論文の詳細を見る
Hadoop has been widely used in various clusters to build scalable and high performance distributed file systems. However, Hadoop distributed file system (HDFS) is designed for large file management. In case of small files applications, those metadata requests will flood the network and consume most of the memory in Namenode thus sharply hinders its performance. Therefore, many web applications do not benefit from clusters with centered metanode, like Hadoop. In this paper, we compare our Fat-Btree based data access method, which excludes center node in clusters, with Hadoop. We show their different performance in different file I/O applications.
- 2010-07-28
著者
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Min Luo
Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Instit
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Haruo Yokota
Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Instit
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Min Luo
Department Of Computer Science Graduate School Of Information Science And Engineering Tokyo Institut
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Luo Min
Department Of Computer Science Graduate School Of Information Science And Engineering Tokyo Institut
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Haruo Yokota
Department Of Computer Science Graduate School Of Information Science And Engineering Tokyo Institut
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Yokota Haruo
Department Of Computer Science Graduate School Of Information Science And Engineering Tokyo Institut
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Yokota Haruo
Tokyo Inst. Of Technol.
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Haruo Yokota
Department Of Computer Science Graduate School Of Information Engineering And Science Tokyo Institut
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Min Luo
Department Of Computer Science Graduate School Of Information Science And Engineering Tokyo Institut
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