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Placement Scheduling for Replication in HDFS Based on Probabilistic Approach

机译:基于概率方法的HDFS中复制的位置调度

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Along with the rapid evolution in Big Data analysis, Apache Hadoop keeps the important role to deliver the high availability on top of computing clusters. Also, to maintain the high throughput access for computation, the Apache Hadoop is equipped with the Hadoop File System (HDFS) for managing the file operations. Besides, HDFS is ensured the reliability and high availability by using a specific replication mechanism. However, because the workload on each computing node is various, keeping the same replication strategy might result in imbalance. Targeting to solve this drawbacks of HDFS architecture, we proposes an approach to adaptively choose the placement for replicas. To do that, the network status and system utilization can be used to create the individual replication placement strategy for each file. Eventually, the proposed approach can provide the suitable destination for replicas to improve the performance. Subsequently, the availability of the system is enhanced while still keeping the reliability of data storage.
机译:随着大数据分析的快速发展,Apache Hadoop扮演着重要角色,可在计算集群之上提供高可用性。此外,为了保持对计算的高吞吐量访问,Apache Hadoop配备了用于管理文件操作的Hadoop文件系统(HDFS)。此外,通过使用特定的复制机制确保HDFS的可靠性和高可用性。但是,由于每个计算节点上的工作负载各不相同,因此,保持相同的复制策略可能会导致不平衡。为了解决HDFS体系结构的这一缺点,我们提出了一种自适应选择副本位置的方法。为此,可以使用网络状态和系统利用率为每个文件创建单独的复制放置策略。最终,所提出的方法可以为副本提供合适的目的地,以提高性能。随后,在保持数据存储可靠性的同时提高了系统的可用性。

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