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首页> 外文期刊>IEICE transactions on information and systems >NDCouplingHDFS: A Coupling Architecture for a Power-Proportional Hadoop Distributed File System
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NDCouplingHDFS: A Coupling Architecture for a Power-Proportional Hadoop Distributed File System

机译:ndcouplinghdfs:用于功率比例Hadoop分布式文件系统的耦合架构

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摘要

Energy-aware distributed file systems are increasingly moving toward power-proportional designs. However, current works have not considered the cost of updating data sets that were modified in a low-power mode, where a subset of nodes were powered off. In detail, when the system moves to a high-power mode, it must internally replicate the updated data to the reactivated nodes. Effectively reflecting the updated data is vital in making a distributed file system, such as the Hadoop Distributed File System (HDFS), power proportional. In the current HDFS design, when the system changes power mode, the block replication process is ineffectively restrained by a single NameNode because of access congestion of the metadata information of blocks. This paper presents a novel architecture, a NameNode and DataNode Coupling Hadoop Distributed File System (NDCouplingHDFS), which effectively reflects the updated blocks when the system goes into high-power mode. This is achieved by coupling metadata management and data management at each node to efficiently localize the range of blocks maintained by the metadata. Experiments using actual machines show that NDCouplingHDFS is able to significantly reduce the execution time required to move updated blocks by 46% relative to the normal HDFS. Moreover, NDCouplingHDFS is capable of increasing the throughput of the system supporting MapReduce by applying an index in metadata management.
机译:能量感知分布式文件系统越来越朝着电力比例设计迁移。然而,当前的作品没有考虑更新以低功耗模式修改的数据集的成本,其中节点的子集被电源关闭。详细地,当系统移动到高功率模式时,它必须内部将更新的数据内部复制到重新激活的节点。有效地反映更新的数据对于制作分布式文件系统至关重要,例如Hadoop分布式文件系统(HDFS),功率比例。在当前的HDFS设计中,当系统改变电源模式时,由于块元数据信息的访问拥塞,块复制过程无效地受到单个NameNode的。本文提出了一种新颖的架构,NameNode和DataNode耦合Hadoop分布式文件系统(ndcouplinghdfs),它有效地反映了系统进入高功率模式时的更新块。这是通过在每个节点处的元数据管理和数据管理耦合以有效地本地化由元数据维护的块的范围来实现的。使用实际机器的实验表明,NDCouplingHDFS能够显着降低相对于正常HDF将更新块移动46%所需的执行时间。此外,NDCouplingHDFS能够通过在元数据管理中应用索引来提高支持MapReduce的系统的吞吐量。

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