CAREER: Extensible Personalization of Spatial and Spatio-temporal Database Management Systems

该研究项目的目标是让数据库用户享受高质量的个性化回答他们的空间和时空查询，而不牺牲查询执行效率。由于个性化的概念是主观的，有很多方法可以定义高质量个性化答案的含义和内容。该项目的目的不是提供更多的个性化定义，而是提供一种面向系统的方法，可以在一个高效的数据库引擎中容纳大多数现有和未来的定义。为了实现其目标，该项目采用了可扩展的方法，其中用于个性化查询的核心数据库模块仅在数据库引擎中实现一次，并以不同的方式多次使用，以支持各种个性化查询。该项目提供了这样的可扩展核心模块：（a）单表操作，例如，选择和聚合，（B）多表操作，例如，连接，（c）只能在线计算的自适应成本操作，以及（d）处理不确定数据。有了这些可扩展的模块，注册新的个性化定义就像在一个易于使用的界面中插入几个模块一样简单。一旦插入，新的个性化定义就存在于数据库引擎中，并享受查询处理器、优化器和索引的可扩展模块的强大功能。这种可扩展的方法是非常有吸引力的行业，因为它给出了最小的变化，在数据库引擎，以支持各种各样的个性化查询，以及数量级的性能超过现有的方法，建立在数据库系统的顶部。除了对行业的影响外，该项目还将对社会的多个领域产生更广泛的影响，包括提高生产力，研究生和本科生教育，K-12学生的推广，课程开发和教程演示。本研究的出版物、技术报告、开放源代码软件和实验数据通过项目网站（http：//www.cs.umn.edu/mokbel/career）传播。

The goal of this research project is to allow database users to enjoy high quality personalized answers for their spatial and spatio-temporal queries, without sacrificing the query execution efficiency. As the concept of personalization is subjective, there are plethora of approaches that define the meaning and contents of a high quality personalized answer. This project does not aim to provide more definitions of personalization, instead, it provides a system-oriented approach that can accommodate most of the existing and future definitions in one highly efficient database engine. To achieve its goal, this project employs an extensible approach where core database modules for personalized queries are realized only once inside the database engine, and used many times in different ways to support a wide variety of personalized queries. The project provides such extensible core modules for:(a) single-table operations, e.g., selection and aggregations,(b) multi-table operations, e.g., join, (c) operations with adaptive cost that can only be computed online, and (d) handling uncertain data. With these extensible modules, registering a new personalization definition becomes as easy as plugging few modules in an easy-to-use interface. Once plugged in, the new personalized definition lives in the database engine, and enjoys the power of the extensible modules for query processor, optimizer, and indexing. Such extensible approach is highly attractive to industry as it gives minimal changes in the database engine to support wide variety of personalized queries, as well as orders of magnitude performance over existing approaches that are built on top of database systems. Besides its impact on industry, this project will have significant broader impact across multiple segments of society that include enhancing productivity, graduate and undergraduate student education, outreach to K-12 students, curriculum development, and tutorial presentations. Publications, technical reports, open-source software, and experimental data from this research are disseminated via the project web site (http://www.cs.umn.edu/~mokbel/career).