Collaborative Research: Query Optimization Engineering

合作研究：查询优化工程

• 批准号: 9610013
• 负责人: Leonard Shapiro
• 金额: $ 18.68万
• 依托单位: Portland State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-09-01 至 2001-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9610013&HistoricalAwards=false
• 关键词: Collaborative; Research; Query; Optimization; Engineering

This is an interinstitutional collaborative project between Oregon Graduate Institute of Science and Technology (OGI) and Portland State University (PSU). Query optimizers are one of the main means by which modern database systems achieve their performance advantages. Given a request for data manipulation or retrieval, an optimizer will choose an optimal plan for evaluating the request from among the manifold alternative strategies. Optimization for the basic relational model is considered a solved problem by many. However, new application areas such as knowledge discovery, on-line analytical processing, and complex multimedia objects, have kindled renewed research in optimization. Current optimizers have often proved inadequate to the needs of these new application areas. Researchers have developed optimization techniques, and several prototype optimizers, to support new applications. This research addresses engineering questions related to the use of new optimizers for new applications: which operators to use; which search strategies to employ; and which transforms to utilize. These investigations use the Columbia query optimizer framework and visualization environment developed at PSU and OGI. The project interacts closely with companies which produce database management systems and the hardware on which they run. The research results will help database optimizer implementors make better choices in the design of their systems, leading to better performance and more expressive query languages for commercial database systems.

这是俄勒冈州科学与技术研究生院(OGI)和波特兰州立大学(PSU)之间的一个跨机构合作项目。查询优化器是现代数据库系统实现其性能优势的主要手段之一。在给定数据操作或检索请求的情况下，优化器将从多种替代策略中选择一个最佳计划来评估该请求。对基本关系模型的优化被许多人认为是一个已解决的问题。然而，知识发现、在线分析处理和复杂多媒体对象等新的应用领域引发了优化领域的新研究。事实证明，当前的优化器常常不能满足这些新应用领域的需求。研究人员已经开发了优化技术和几个原型优化器，以支持新的应用程序。这项研究解决了与为新应用程序使用新优化器相关的工程问题：使用哪些运算符；使用哪些搜索策略；以及使用哪些转换。这些研究使用了在PSU和OGI开发的哥伦比亚查询优化器框架和可视化环境。该项目与生产数据库管理系统及其运行硬件的公司密切互动。研究结果将帮助数据库优化器实现者在系统设计中做出更好的选择，从而为商业数据库系统带来更好的性能和更具表现力的查询语言。