SGER: Query Optimization to Meet Performance Targets in a Wide Area Environment

本研究项目的目标是开发一个性能目标（PT）敏感的优化器。性能目标与嘈杂的广域环境有关，在这种环境中，访问Internet可访问的WebSources的成本表现为瞬态行为，并且最好以访问成本的分布为特征。PT敏感的优化器将能够区分多个备选的WebSources，并选择WebSources的组合，以便最好地满足某些查询（及其查询评估计划）的性能目标。实现目标的能力通过效用函数来量化。现有的优化器及其成本模型考虑访问成本的特定值或期望值，并且对性能目标不敏感。这种方法用计划成本的期望值和延迟来描述每个计划的特征；延迟是超出期望值的偏差。成本-延迟度量（CDM）使用成本因子和延迟因子将这两个值结合起来。对于WebSources上的一组查询和一组远程关系，基于优化器聚合行为的模拟研究将用于将PT优化器对计划和WebSources的选择与它在最大化效用或满足性能目标方面的成功联系起来。该项目的结果将为嘈杂的环境提供一个可调的优化器，使应用程序能够对性能目标敏感，并更好地利用Internet资源。

The goal of this research project is to develop a performance target (PT) sensitive optimizer. Performance targets are relevant in the noisy wide area environment where access costs to Internet accessible WebSources exhibit transient behavior, and are best characterized by a distribution of access costs. A PT sensitive optimizer will have the ability to differentiate among multiple alternate WebSources, and to choose a combination of WebSources so as to best meet a performance target for some query (and its query evaluation plan). The ability to meet a target is quantified by a utility function. Existing optimizers and their cost model consider either specific values or expected values for access costs, and are not sensitive to performance targets. This approach characterizes each plan with the expected value of the cost of the plan, as well as the delay; delay is the deviation above the expected value. A Cost-Delay measure (CDM) combines these two values using a cost factor and a delay factor. A simulation based study of the optimizer's aggregate behavior, for a set of queries and a set of remote relations on WebSources will be used to correlate the PT optimizer's selection of plans and WebSources with its success in maximizing utility or meeting a performance target. The results of this project will provide a tunable optimizer for noisy environments that allow applications to be sensitive to performance targets and to better utilize Internet resources.