Queries On Distributed Heterogeneous Sources And Optimization

The aim of information integration is to build sophisticated systems by making use of available information sources to fullest extent and by pushing costly operations to these sources as much as possible. Queries integration systems are of this kind. What the queries integration systems do is to create a unified query interface, including query languages and schema that queries built on, and users can query multi-sources through the unified query interface.There are some shortages in current implements of query integration systems. Firstly, the organization of data sources cann't meet the requirement of some applications. Secondly, although some implements use XQuery as query language, which can define queries of multi-sources, there also needs a middle language to express the definition with multi-sources queries characteristics, with which we can do some optimization reasoning expediently. Thirdly, current implements work little reseach in distributed factors.In this thesis, we organize data sources with the structure of virtual sources, which is flexible to used in some sinario that current implements cann't be used in. Based on this architecture, we research in some aspect of query integration system to a quite deep extent and implement a prototype of query integration system, named XQuery Enabled Query Integration System (XEQIS).With virtual sources, we use XQuery and XML Schema as the common query interface of distributed heterogeneous sources. So we can define a common query to these sources without knowing the real type and data organization of them. Also, we define a middle language, XQuery Middle Language (XQML), which can hold characteristices of multi-source query during the translation for XQuery to middle language. So we can use these characteristices in optimization reasoning.One more reseach in the analysis and optimization strategy of distributed factor is also refered in this thesis. We get some evaluation functions in this thesis and give a optimization algorithm based on these evaluation functions.Furthermore, as an example, we focus to the issues of the evaluation of queries on relational sources, and give some solutions to the issues in the architecture of XEQIS.