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Metadata Replication with Synchronous OpCodes Writing for Namenode Multiplexing in Hadoop

机译:与Hadoop中的NameNode多路复用的同步操作码编写的元数据复制

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A single Active Namenode (ANN) of Hadoop Distributed File System (HDFS) become a bottleneck when we require high-throughput read operations such as large-scale data analysis. Recently, various kinds of namenode schemes are proposed including asynchronous check pointing schemes to address the ANN bottleneck issue. Even if asynchronous schemes offers high throughput reading operations, they suffers in stale read problem where the latest data return is not guaranteed. In this paper, we propose a novel metadata replication scheme with synchronous OpCodes writing to achieve namenode multiplexing, where we can avoid the stale read problem. To reduce synchronization overhead, our proposed scheme conducts reduced replication only for metadata updates such as a write request, using quasi byte-level metadata operation codes. We conducted the empirical experiment to verify the effectiveness of our proposed schemes. The results show that our method reduces by 50.95% in the average required number of NNs when the number of NNs for read-only operation is 100.
机译:当我们需要大规模数据分析等高吞吐量读取操作时,Hadoop分布式文件系统(HDFS)的单个活动NameNode(HDF)成为瓶颈。最近,提出了各种NameNode方案,包括异步检查指向方案来解决ANN瓶颈问题。即使异步方案提供高吞吐量读取操作,它们也会遇到陈旧的读取问题,其中无法保证最新的数据返回。在本文中,我们提出了一种新颖的元数据复制方案,具有同步操作码写入以实现NameNode复用,我们可以避免陈旧的读取问题。为了减少同步开销,我们所提出的方案仅使用准字节级元数据操作代码对诸如写请求的元数据更新进行减少的复制。我们进行了实证实验,以验证我们提出的计划的有效性。结果表明,当只读操作的NN的数量为100时,我们的方法在NNS的数量时,NNS的平均所需数量为50.95%。

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