ITR: Querying Sequentially Accessed XML Data

ITR：查询按顺序访问的 XML 数据

• 批准号: 0313384
• 负责人: Yannis Papakonstantinou
• 金额: $ 37.5万
• 依托单位: University of California-San Diego
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-08-01 至 2007-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0313384&HistoricalAwards=false
• 关键词: ITR; Querying; Sequentially; Accessed; XML

High-volume data streams exchanged in XML form are becoming crucial to a wide range of applications in the scientific, government and business domains. However, taking advantage of them raises significant technical challenges and opportunities. First, stream queries require computations to be performed in memory that is limited with comparison to the arbitrarily large data stream. Second, the rapid increase of network bandwidths surpasses the increase of CPU-to-memory and CPU-to-disk transfer rates. The result is that high bandwidth networks will be delivering stream data faster than they can be processed by conventional approaches. Efficient on-the-fly data stream processing is necessary. This project will develop a comprehensive approach to querying data streams in XML form, covering the spectrum from formal foundations all the way to systems. The expected outcome of the project will be a qualitatively new architecture, technology and query processor for XML data streams, with impact on a wide range of applications. The approach will be tested on seismic data provided by the ROADNet project. However, we expect that the research will have broader impact on voluminous XML data streams.

以XML格式交换的大容量数据流对于科学、政府和商业领域的广泛应用正变得至关重要。然而，利用它们带来了重大的技术挑战和机遇。首先，流查询需要在内存中执行计算，与任意大的数据流相比，内存是有限的。其次，网络带宽的快速增长超过了CPU到内存和CPU到磁盘传输速率的增长。结果是，高带宽网络将比传统方法更快地传递流数据。高效的实时数据流处理是必要的。这个项目将开发一个全面的方法来查询XML形式的数据流，涵盖了从正式基础一直到系统的范围。该项目的预期成果将是XML数据流的全新结构、技术和查询处理器，对广泛的应用产生影响。将在ROADNet项目提供的地震数据上测试这一方法。然而，我们期望该研究将对海量XML数据流产生更广泛的影响。