Abstract: XML is an important standard of data exchange and
representation. As a mature database system, using relational database
to support XML data may bring some advantages. But storing XML in
relational database has obvious redundancy that wastes disk space,
bandwidth and disk I/O when querying XML data. For the efficiency
of storage and query XML, it is necessary to use compressed XML
data in relational database. In this paper, a compressed relational
database technology supporting XML data is presented. Original
relational storage structure is adaptive to XPath query process. The
compression method keeps this feature. Besides traditional relational
database techniques, additional query process technologies on
compressed relations and for special structure for XML are presented.
In this paper, technologies for XQuery process in compressed
relational database are presented..
Abstract: In many applications, data is in graph structure, which
can be naturally represented as graph-structured XML. Existing
queries defined on tree-structured and graph-structured XML data
mainly focus on subgraph matching, which can not cover all the
requirements of querying on graph. In this paper, a new kind of
queries, topological query on graph-structured XML is presented.
This kind of queries consider not only the structure of subgraph but
also the topological relationship between subgraphs. With existing
subgraph query processing algorithms, efficient algorithms for topological
query processing are designed. Experimental results show the
efficiency of implementation algorithms.