Douglas M. Flewelling, Ph.D.
Fang Ren, Ph.D.
Large datasets pose unique problems for certain statistical operations. This is caused by the requirement for each row to be evaluated one or more times in order to generate the result. In the situation where the client application is on a separate system, or not utilizing metadata to its full potential, this requirement may lead to degradation in performance and efficiency. By generating the results of data intensive operations at the source and returning only the result, these performance problems can be eliminated. Creation of a statistical metadata index on these datasets further increases efficiency by caching partial results for multiple clients to access. This project implements an Oracle package that will employ a user defined domain index with associated descriptive operators and functions for point populations. Using these packages, statistical information can be generated more efficiently for large spatial point datasets stored in Oracle databases, or more quickly using estimates and confidence intervals.
Val, T. (2014). Optimizing Oracle Centrography (Master's thesis, University of Redlands). Retrieved from https://inspire.redlands.edu/gis_gradproj/203