摘要
数据流窗口主要采用了基于时间、元组和分组的3种驱动形式,如果仅采用一种驱动形式难以正确表达数据流查询语义,因此,针对数据流查询语义的不完备性,从窗口的查询级、数据级和系统级定义了一个完整的窗口语义框架来解决语义差异,并提出了基于主存数据库的分组窗口驱动的实现,最后通过实验验证了该方法.
Windows of data stream had three driven models of time-based, tuple-based and batch-driven, each of which did not express the correct semantic of querying data stream. In order to solve the incompleteness of query semantics in data stream, the authors defined the full window semantic framework from three aspect of query-level, data-level and system-level in order to eliminate the semantic differences, and batch-driven model was implemented based on memory database. Finally the method was verified by experiments.
出处
《北京工业大学学报》
CAS
CSCD
北大核心
2014年第7期1114-1120,共7页
Journal of Beijing University of Technology
基金
国家自然科学基金资助项目(61300227)
广东省自然科学基金资助项目(s2012010008831)
武汉大学软件工程国家重点实验室开放基金资助项目(SKLSE2012-09-37)
关键词
窗口语义框架
分组驱动
主存数据库
window semantics framework
batch-driven
memory database
