Hadoop的带宽感知数据放置方案

T. P. Shabeera, S. D. Madhu Kumar
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引用次数: 15

摘要

我们生活在一个数据丰富的时代。数据量呈指数级增长。社交网络应用、科学实验等是大数据的主要贡献者。数据可以是结构化、半结构化或非结构化的。大数据管理解决方案可以在组织内部实施,也可以存储在云中。无论是存储在内部还是存储在云中,数据的放置都非常重要。一般来说,用户在请求数据时都需要数据的可用性。在Hadoop中,有许多参数会影响数据检索时间。其中,本文关注的是可用带宽。为了减少数据检索时间,必须将数据放在带宽最大的DataNode中。我们提出了一个Hadoop中带宽感知数据放置的解决方案,通过定期测量客户端和datanode之间的带宽,并将数据块放置在具有最大端到端带宽的datanode中。
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Bandwidth-aware data placement scheme for Hadoop
We are living in a data rich era. The size of the data is increasing exponentially. Social networking applications, Scientific experiments, etc. are the major contributors of Big Data. The data can be structured, semi-structured or unstructured. Big Data management solutions can be implemented in-house in the organization or it can be stored in cloud. Whether it is stored in-house or in cloud, the placement of data is very important. In general, users demand the availability of data whenever they request for it. There are many parameters that effect the data retrieval time in Hadoop. Among them, this paper pays attention to the available bandwidth. To minimize the data retrieval time, the data must be placed in a DataNode which has the maximum bandwidth. We have proposed a solution for bandwidth-aware data placement in Hadoop by periodically measuring the bandwidth between clients and DataNodes and placing the data blocks in DataNodes that have maximum end-to-end bandwidth.
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