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Optimal Histograms for Hierarchical Range Queries (Extended Abstract)

Summary: Shows equality-optimized histograms are suboptimal for hierarchical range queries in OLAP and casts histogram design as expected-error minimization under a space budget. Presents polynomial-time DP algorithms for one-sided (V-Optimal runtime), balanced-tree, and general hierarchies with provable optimality and empirical error reductions. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1209
Venue
PODS
Year
2000
Pagerank
7.2946291e-05
Overall Rank
3,575 | 75.48%
DOI
10.1145/335168.335223

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{koudas_pods00,
        address = {New York, NY, USA},
        series = {{PODS} '00},
        title = {{Optimal Histograms for Hierarchical Range Queries (Extended Abstract)}},
        url = {https://dl.acm.org/doi/10.1145/335168.335223},
        doi = {10.1145/335168.335223},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Koudas, Nick and Muthukrishnan, S. and Srivastava, Divesh},
        year = {2000}
}

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