Compact Histograms for Hierarchical Identifiers
Summary: Compact histograms as partitioning functions model hierarchical UIDs (e.g., IPs), enabling bandwidth-efficient group-aggregates over large lookup tables. Three novel partitioning families use single-identifier buckets and distributive-error optimization; they scale to multiple hierarchies and yield higher accuracy per bit on real network data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Frederick Reiss (University of California Berkeley)
- 2. Minos Garofalakis (Intel)
- 3. Joseph M. Hellerstein (University of California Berkeley)
BibTeX Citation
@article{reiss_vldb06,
title = {{Compact Histograms for Hierarchical Identifiers}},
author = {Reiss, Frederick and Garofalakis, Minos and Hellerstein, Joseph M.},
journal = {PVLDB},
series = {{VLDB} '06},
pages = {870--881},
year = {2006}
}
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,595 | Plato: Approximate Analytics over Compressed Time Series with Tight Deterministic Error Guarantees | 2020 | VLDB | 7.2736195e-05 |
| 9,209 | Optimality and Scalability in Lattice Histogram Construction | 2009 | VLDB | 5.3058708e-05 |
| 11,957 | Efficient Haar+ Synopsis Construction for the Maximum Absolute Error Measure | 2018 | VLDB | 5.093636e-05 |
| 12,623 | Public Health for the Internet (phi): Towards A New Grand Challenge for Information Management | 2007 | CIDR | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 15 of 15 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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