Deductive Databases

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subsection{Deductive Databases} In the field of deductive databases there has been extensive research on the optimization of queries for Datalog (and its variants). The major interest has been the optimization of recursive queries. Ceri et al~cite{ceri-gottlob-tanca-1989} provide an excellent summary of the field. The evaluation or comparison of optimization strategies is typified by Bancilhon and Ramakrishnan~cite{br1986,br1988} who develop analytical cost models for the optimization strategies when applied to four queries (related to the parent and ancestor relations) and then generate numerical data from the analytical models using synthetic data driven by three shapes -- tree, inverted tree, and cylinder -- for the ``family tree''. The state--of--the--art is perhaps best summarized in a quote~cite{seshadri1991}: {em ``Related work on the performance of recursive queries and their evaluation algorithms has considered either worst case performance, or performance over structured synthetic databases, or empirically measured performance over randomly generated relations.''} The community has not developed extensive benchmarks nor carried out extensive performance comparisons. section{Contribution} This thesis work contributes in the following aspects: egin{itemize} item A graph database system with a visual graph query user interface where a query can be expressed intuitively as a diagram is constructed. egin{itemize} item The research group of Alberto Mendelzon at the University of Toronto developed the GraphLog graph query languagecite{graphlog:consens} based on hygraphs and a visual interface {sc Hy+} for expressing queries and browsing the result. It has nodes that represent objects, an... ... middle of paper ... ...ual query language and facilitate a visual query language implementation based on this algebra. A database architecture using a visual query language based on this algebra is proposed. end{itemize} section{Thesis Organization} The rest of this thesis is organized as follows. Chapter 2 illustrates the background knowledge that is related to this thesis work. Chapter 3 describes the implemented visual graph database system. A query benchmark in genomics domain that is used to test the performance of our graph database system are described in Chapter 4. Chapter 5 describes the query optimization experiments and discusses the findings of the experiments. A visual query language for gene feature topological relationships based on the genome browser visual metaphor is introduced in Chapter 6. Chapter 7 provides a conclusion and discusses the future work.

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