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Bulk-Insertions into R-Trees (1998)
| Venue: | In Proceedings of ACM International Workshop on Advances in Geographic Information Systems |
| Citations: | 3 - 1 self |
BibTeX
@TECHREPORT{Chen98bulk-insertionsinto,
author = {Li Chen and Rupesh Choubey and Elke A. Rundensteiner},
title = {Bulk-Insertions into R-Trees},
institution = {In Proceedings of ACM International Workshop on Advances in Geographic Information Systems},
year = {1998}
}
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Abstract
A lot of recent work has focussed on bulk loading of data into multidimensional index structures in order to efficiently construct such structures for large datasets. Previous work on bulk loading data focussed at building index structures from scratch, while the problem of bulk insertions into existing index structures has been largely overlooked. In this paper, we address this new problem with particular focus on R-trees -- which are an important class of index structures used widely in commercial database systems. We propose a new technique, which as opposed to the current technique of inserting data one by one, bulk-inserts entire new datasets into an active R-tree. This technique, called STLT (for Small-Tree-Large-Tree), considers the new dataset as an R-tree itself (small tree), identifies and prepares a suitable location in the original R-tree (large tree) for insertion, and lastly performs the insert of the small tree into the large tree. In this paper, we present an analytic...
Keyphrases
index structure large tree small tree new technique multidimensional index structure bulk insertion important class new problem commercial database system original r-tree current technique new dataset previous work large datasets bulk loading bulk-inserts entire new datasets recent work particular focus suitable location
