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dc.contributor.authorSeshadri, Praveenen_US
dc.date.accessioned2007-04-23T18:13:43Z
dc.date.available2007-04-23T18:13:43Z
dc.date.issued1998-07en_US
dc.identifier.citationhttp://techreports.library.cornell.edu:8081/Dienst/UI/1.0/Display/cul.cs/TR98-1693en_US
dc.identifier.urihttps://hdl.handle.net/1813/7347
dc.description.abstractObject-relational queries access large complex data types and expensive methods of those data types. In earlier work, we modeled complex types as "Enhanced ADTs" (E-ADTs) and demonstrated the resulting performance improvements when implemented in the PREDATOR system. This paper explores the opportunities for further improvements through interactions between relational query optimization and E-ADT optimization. We identify four broad categories of optimization opportunities and study specific examples in each of these categories. These examples span query rewrite, indexing, aggregation and join optimization. Our conclusion is that non-trivial interactions exist between E-ADTs and relational queries, and that special optimization techniques are necessary to achieve good performance. These techniques have been prototyped in PREDATOR, and we present experimental results that demonstrate their effect.en_US
dc.format.extent155654 bytes
dc.format.extent849631 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/postscript
dc.language.isoen_USen_US
dc.publisherCornell Universityen_US
dc.subjectcomputer scienceen_US
dc.subjecttechnical reporten_US
dc.titleRelational Query Optimization with Enhanced ADTsen_US
dc.typetechnical reporten_US


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