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Memory-Efficient Query Processing over XML Fragment Stream with Fragment Labeling

机译:具有片段标签的XML片段流上的内存高效查询处理

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The portable/hand-held devices deployed in mobile computing environment are mostly limited in memory. To make it possible for them to locally process queries over a large volume of XML data, the data needs to be streamed in fragments of manageable size and the queries need to be processed over the stream with as little memory as possible. In this paper, we report a considerable improvement of the state-of-the-art techniques of query processing over XML fragment stream in memory efficiency. We use XML fragment labeling (XFL) as a method of representing XML fragmentation, and show that XFL is much more effective than the popular hole-filler (HF) model employed in the state-of-the-art in reducing the amount of memory required for query processing. The state-of-the-art with the HF model requires more memory as the stream size increases. With XFL, we overcome this fundamental limitation, proposing the techniques to make query processing scalable in the sense that memory requirement is not affected by the size of the stream as long as the stream is bounded. The improvement is verified through implementation and a detailed set of experiments.
机译:部署在移动计算环境中的便携式/手持设备的内存大多受到限制。为了使他们能够对大量XML数据进行本地处理查询,需要以可管理大小的片段流式传输数据,并且需要在流上以尽可能少的内存处理查询。在本文中,我们报告了在内存效率上对XML片段流进行查询处理的最新技术的显着改进。我们使用XML片段标签(XFL)作为表示XML片段的方法,并表明XFL在减少内存量方面比最新技术中使用的流行的空穴填充程序(HF)模型有效得多。查询处理所需。随着流大小的增加,最新的HF模型需要更多的内存。使用XFL,我们克服了这一基本限制,提出了使查询处理具有可伸缩性的技术,即只要流有界,内存需求就不受流大小的影响。通过实施和一组详细的实验来验证改进。

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