A process allowing for the intuitive use of SQL queries on dense multidimensional data stored in Network Common Data Format (netCDF) files is developed using advanced bitmap indexing provided by the FastBit bitmap indexing tool. A method for netCDF data extraction and FastBit index creation is presented and a geospatial Range and pseudo-KNN search based on the haversine function is implemented via SQL. A two step filtering algorithm is shown to greatly enhance the speed of these geospatial queries, allowing for extremely efficient processing of the netCDF data in bitmap indexed form.
Identifer | oai:union.ndltd.org:uno.edu/oai:scholarworks.uno.edu:td-1965 |
Date | 06 August 2009 |
Creators | Marks, David |
Publisher | ScholarWorks@UNO |
Source Sets | University of New Orleans |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | University of New Orleans Theses and Dissertations |
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