|
Abstract : |
quantification, storage overhead quantification. Dynamic Queries is a querying technique for doing range search on multi-key data sets. It is a direct manipulation mechanism where the query is formulated using graphical widgets and the results are displayed graphically in real time. This paper evaluates four data structures, the multilist, the grid file, k-d tree and the quad tree used to organize data in high speed storage for dynamic queries. The effect of factors like size, distribution and dimensionality of data on the storage overhead and the speed of search is explored. A way of estimating the storage and the search overheads using analytical models is presented. These models are verified to be correct by empirical data. Results indicate that multilists are suitable for small (few thousand points) data sets irrespective of the data distribution. For large data sets the grid files are excellent for uniformly distributed data, and trees are good for skewed data distributions. There was no significant difference in performance between the tree structures. 1, |
