III: Small: Query Mesh - A Novel Paradigm for Query Processing

定位、传感器和监控技术的进步推动了数据采集设备产生海量数据流。这项研究的目标是开发一类新的高性能流数据管理系统，能够应对海量数据到达的无限场景，并满足近实时的响应要求。所提出的查询处理范例称为多路径查询网格模型(QM)，它克服了当前查询优化器中的一个主要限制，即为所有输入数据分配一个“最佳”查询执行计划。这种方法基于数据一致性这一强有力的假设，可能会导致所有数据项的性能都不达标。取而代之的是，查询网格采用由数据分类器和多路由规划基础设施组成的处理结构。不同的学习模型可以作为分类器逻辑插入到QM模型中。考虑到QM解空间的复杂性，基于代价的搜索启发式算法被设计来高效地找到高质量的查询网格。QM自适应地支持对QM分类器及其路径的检测和增量修改。这个项目的智力价值在于设计、开发和评估了一种用于流查询处理的新的多路由范例--当前单一计划和无路线解决方案的两个极端之间的完美中间地带。实验研究将查询网格与最先进的解决方案进行了比较。QM通过促进广泛的以流为中心的应用程序，包括医疗门诊监控、应急管理和商业智能处理，以及通过将项目活动与教育相结合来影响社会。有关该项目的更多信息，请访问项目网页：http://dsrgweb.cs.wpi.edu:8180/DSRG/

Technological advances in positioning, sensor and monitoringtechnology drive data acquisition devices to generate massive streamsof data. The goal of this research is to develop a new class ofhigh-performance stream data management systems capable of coping withscenarios with infinite data arriving in large volumes, and withnear-real time response requirements. The proposed query processing paradigm, termed the multi-route query mesh model (QM), overcomes amajor limitation in current query optimizers, both static and streamones alike, namely the assignment of a single `best' query executionplan for all input data. This approach, being based on the strongassumption of data uniformity, results in substandard performance forpossibly all data items. Instead, query mesh adopts a processingstructure composed of a data classifier and a multiple route planinfrastructure. Different learning models can be plugged asclassifier logic into the QM model. Given the complexity of the QMsolution space, cost-based search heuristics are designed toefficiently find high-quality query meshes. QM is adaptive supportingthe detection and incremental modification of the QM classifier andits routes. The intellectual merit of this project lies in the design, development andevaluation of a novel multi-route paradigm for stream queryprocessing, -- a perfect middle ground between the two currentextremes of single-plan versus route-less solutions. Experimentalstudies compare query mesh to state-of-the-art solutions. QM impactssociety by facilitating a wide range of stream-centric applications,including medical out-patient monitoring, emergency management, andbusiness intelligence processing, and by integrating projectactivities with education.Further information on this project can be found at the projectweb page: http://dsrgweb.cs.wpi.edu:8180/DSRG/