Management of Sequence Data

One of the challenges facing today's database systems is the need to support complex data types, which are of growing importance in new application areas. The thesis addresses this problem, with a speciic focus on supporting sequence data. A large part of the thesis deals with the details of sequences. Issues covered include the model for sequence data, an algebra of operators to query the data, a query language to express the queries, optimization techniques and query processing algorithms. Performance results are presented from an implementation of these ideas, demonstrating the eeects of the various optimizations. This detailed exploration of sequence data is one contribution of the thesis. The second contribution is a solution to the problem of integrating diierent data types, including sequences and relations, in a general-purpose database system. The thesis discusses the drawbacks of existing solutions, and then proposes a solution based on a novel E-ADT paradigm. This paradigm has been used in the development of the PREDATOR database system, and the implementation brings to light several advantages as well as limitations of this paradigm. The support for sequences has been implemented as a component of this larger system. The conclusion drawn from the sequence implementation is that it is important to provide specialized support for queries over sequences. By extrapolation, similar conclusions may be drawn about support for other complex data types like matrixes and images. The E-ADT paradigm provides a mechanism to integrate all these types within a single general-purpose database system. The conclusion of the thesis is that database systems should adopt some of the E-ADT ideas so as to provide more eecient support for complex data types like sequences. ii Acknowledgements

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