A Heuristic Approach to Attribute Partitioning
Summary: Attribute partitioning splits a logical file into subrecords of attribute subsets to cut I/O; gains when transactions use fields together, with potential costs otherwise. A precise partition evaluator assigns a cost metric, and a heuristic search surfaces a small set of promising partitions for detailed analysis; implemented in a model DB and shown to be accurate and efficient. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Michael Hammer (Massachusetts Institute of Technology)
- 2. Bahram Niamir (Massachusetts Institute of Technology)
BibTeX Citation
@inproceedings{hammer_sigmod79,
title = {{A Heuristic Approach to Attribute Partitioning}},
author = {Hammer, Michael and Niamir, Bahram},
series = {{SIGMOD} '79},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/582095.582110},
url = {https://dl.acm.org/doi/10.1145/582095.582110},
year = {1979}
}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 854 | Index Selection in a Self-Adaptive Data Base Management System | 1976 | SIGMOD | 0.00013581028 |
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