An Evaluation of Generic Bulk Loading Techniques
Summary: Introduces two simple, low-parameter generic bulk-loaders that recursively partition data using an in-memory index matching the target structure. A shared implementation across R-trees and Slim-trees outperforms worst-case-optimal methods and improves search quality. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Jochen van den Bercken (IXOS Software AG)
- 2. Bernhard Seeger (Philipps University Marburg)
BibTeX Citation
@article{bercken_vldb01,
title = {{An Evaluation of Generic Bulk Loading Techniques}},
author = {van den Bercken, Jochen and Seeger, Bernhard},
journal = {PVLDB},
series = {{VLDB} '01},
year = {2001}
}
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 1,067 | Hadoop-GIS: A High Performance Spatial Data Warehousing System over MapReduce | 2013 | VLDB | 0.00012327784 |
| 7,768 | The next 50 Years in Database Indexing or: The Case for Automatically Generated Index Structures | 2022 | VLDB | 5.5475685e-05 |
| 9,324 | Main-Memory Operation Buffering for Efficient R-Tree Update | 2007 | VLDB | 5.289545e-05 |
| 12,605 | Towards Efficient Main-Memory Use For Optimum Tree Index Update | 2008 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 16 of 16 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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