Date of Award:

8-2024

Document Type:

Thesis

Degree Name:

Master of Science (MS)

Department:

Computer Science

Committee Chair(s)

Curtis Dyreson

Committee

Curtis Dyreson

Committee

Shuhan Yuan

Committee

Steve Petruzza

Abstract

In data management and modeling, the value of the hierarchical model is that it does not require expensive JOIN operations at runtime; once the hierarchy is built, the relationships among data are embedded in the tree-like hierarchical structure, and thus querying data could be much faster than using a relational database. Today most data is stored in relational databases, but if the data were stored in hierarchies, what would these hierarchies look like? And more importantly, would this transition lead to a more efficient database? This thesis explores these questions by introducing a set of algorithms to convert a relational schema to a hierarchy, that is, a tree-like structure. We show that our algorithms minimize space cost for creating tree nodes while preserving all the relationships and constraints in the schema. Finally, we evaluate the hierarchies on a native XML DBMS with a set of queries.

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