CAREER: New Technologies for Approximate Query Processing

职业：近似查询处理的新技术

• 批准号: 0448264
• 负责人: Alin Dobra
• 金额: --
• 依托单位: University of Florida
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-01 至 2011-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0448264&HistoricalAwards=false
• 关键词: CAREER; New; Technologies; Approximate; Query

One of the two goals of the project is to advance the state-of-the art in approximate query processing (AQP), a critical component of analytical processing -- a 3.5 billion dollar segment of the software industry. The need for approximate query processing arises from the growing discrepancy between the volume of information that has to be processed and the computational resources or communication capabilities available. Using two computational models, data-streaming and distributed computation, the project addresses fundamental problems in AQP such as development of new approximation techniques for data-stream computation, extensions of data-stream algorithms to distributed algorithms that can efficiently query sensor and peer-to-peer networks, and theoretical aspects of AQP that allow the design of AQP techniques to be accelerated and better understood. Part of the project's research goal is the design and implementation of a approximate query processing engine that uses the developed AQP techniques and the rigorous benchmarking of the software produced. The second goal of the project is educational and consists in, on one hand, motivating students to study and pursue carers in databases through bonus points for extra activities and integration of the database curricula and other CS disciplines, and, on the other hand, integration of approximate query processing into both undergraduate and graduate curricula. The project will have broad impact by developing techniques for efficient processing of large volumes of data -- crucial for scientific data processing and home-land security -- and by increasing the quality of database education with a direct impact on nation's technological leadership.http://www.cise.ufl.edu/~adobra/AQP

该项目的两个目标之一是推进近似查询处理（AQP）的最新技术，这是分析处理的关键组成部分——软件行业中价值35亿美元的部分。由于需要处理的信息量与可用的计算资源或通信能力之间的差异越来越大，因此需要进行近似查询处理。使用两种计算模型，数据流和分布式计算，该项目解决了AQP中的基本问题，如开发新的数据流计算近似技术，将数据流算法扩展到分布式算法，可以有效地查询传感器和点对点网络，以及AQP的理论方面，使AQP技术的设计得以加速和更好地理解。该项目的部分研究目标是设计和实现一个近似查询处理引擎，该引擎使用已开发的AQP技术和所生成软件的严格基准测试。该项目的第二个目标是教育性的，一方面，通过额外的活动和数据库课程与其他CS学科的整合来激励学生学习和从事数据库方面的职业，另一方面，将近似查询处理整合到本科和研究生课程中。该项目将通过开发有效处理大量数据的技术——这对科学数据处理和国土安全至关重要——以及通过提高数据库教育的质量，对国家的技术领先地位产生直接影响，从而产生广泛的影响。http://www.cise.ufl.edu/~adobra/AQP