语义缓存的聚集查询匹配研究

为提高海量数据库系统的查询效率，围绕海量数据库系统中的聚集查询技术，把通常应用于小型数据库查询的语义缓存技术拓展到海量数据库的聚集查询中．首先研究了面向聚集查询的语义缓存形式化描述，在此基础上讨论了利用缓存处理查询的条件并对查询匹配进行了分类，提出并实现了包含匹配判定算法和相交匹配判定算法，最后给出了相应的实验结果．在某大型实际工程中的应用表明上述判定算法是有效的．

Research on Aggregate Query Matching in Semantic Cache

queries are pervasive in massive database applications, whose execution tends to be time consuming and costly. Therefore promotion of their efficiency will largely improve the performance of the system. Semantic cache is a novel scheme for aiding query evaluation that reuses the results of previously answered queries. But little work has been done on semantic cache involving aggregate queries. This is a limiting factor in its applicability and it is mostly used in small scale database applications. In order to utilize semantic cache in massive database applications, it is necessary to extend semantic cache to support aggregate query, in this paper, query matching is identified as a foundation for answering query using semantic caches. First, a formal semantic cache model is proposed, which supports aggregate query and provides the basis for the whole research. Then the condition of query matching is presented and query matching is classified. Next, two algorithms are proposed for aggregate query matching. These two algorithms are applied to a massive database application project. Its result proves the efficiency of the algorithms.