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Improving Query Efficiency Of Multiresolution Data Aggregation For Analytical Exploration Of Large Relational Dataset, Yu-Ting Huang
Improving Query Efficiency Of Multiresolution Data Aggregation For Analytical Exploration Of Large Relational Dataset, Yu-Ting Huang
Masters Theses
Tree structures are developed to organize the data more efficiently by using fewer resources for searching records. This thesis investigates the tree's actual structure on the hard disk to see the influence of different kinds of structures on the tree building time and query execution time. In order to improve efficiency, one multi-file structure and two reorganization structures, BFS and DFS, are examined to achieve this goal. The results indicate that two reorganization structures on KDB-tree structure can significantly improve the query execution time in large data sets and multi-file structure can slightly improve the TPIE lover level building time.