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数据采集设备产生大量数据流。本研究的目标是开发一种新型的高性能流数据管理系统，能够应对大量无限数据到达的场景，并具有近实时的响应要求。所提出的查询处理范例，称为多路由查询网格模型（QM），克服了当前查询优化器的主要限制，无论是静态的还是流的，即为所有输入数据分配一个单一的“最佳”查询执行计划。这种方法基于数据一致性的强假设，可能会导致所有数据项的性能不合格。相反，查询网格采用由数据分类器和多路由规划基础结构组成的处理结构。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，设计了基于成本的搜索启发式算法来高效地找到高质量的查询网格。QM是自适应的，支持QM分类器及其路由的检测和增量修改。这个项目的智力价值在于为流查询处理设计、开发和简化了一种新的多路由范式，这是目前单计划和无路由解决方案两种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比较。质量管理通过促进广泛的以流为中心的应用程序（包括医疗门诊病人监控、紧急情况管理和商业智能处理）以及通过将项目活动与教育相集成来影响社会。关于这个项目的更多信息可以在项目网页上找到：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/