Deductive Databases Essay

891 words - 4 pages

\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.


This thesis work contributes in the following aspects:


\item A graph database system with a visual graph query user interface where a query can be expressed intuitively as a diagram is constructed.


\item The research group of Alberto Mendelzon at the University of Toronto developed the GraphLog graph query language\cite{graphlog:consens} based on hygraphs and a visual interface {\sc Hy+} for expressing queries and browsing the result. It has nodes that represent objects, and has both edges and blobs to represent relationships among the objects. Blobs help to modularize queries with hierarchical relationships and layout the results in the orthogonal shape. The capabilities of our graph database system implemented all features of the graph query language GraphLog.

\item The graph database system user interface is based on the paradigm of a graph drawing editor. It is a hybrid of a query graph pattern editor for drawing queries and a query operator graph editor for defining re--usable new views on the existential database.

\item This graph database system is capable of handling selection queries, projection queries, union queries, queries with negation, queries with aggregation, and queries involving recursive paths such as transitive closure, and path existence queries.

\item The query result is visualized as a diagram based on the intrinsic relationship among the returned query result set. The result visualization component is scalable to large result data sets.

\item The strengths of our graph database are the visual nature of the query process, the variety of visual query modes supported, the scalability to visualize large result data sets, and a visual query language with...

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