Compact Summaries over Large Datasets
Summary: Tutorial on designing and analyzing compact, mergeable summaries that capture essential dataset properties for single‑machine storage and querying after distributed parallel construction. Covers count‑distinct estimators and linear sketches for norms/inner products, space/error tradeoffs, mergeability, and efficient algorithms to compute and combine them. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Graham Cormode (University of Warwick)
BibTeX Citation
@inproceedings{cormode_pods15,
address = {New York, NY, USA},
series = {{PODS} '15},
title = {{Compact Summaries over Large Datasets}},
url = {https://dl.acm.org/doi/10.1145/2745754.2745781},
doi = {10.1145/2745754.2745781},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Cormode, Graham},
year = {2015}
}
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Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 51 | Dremel: Interactive Analysis of Web-Scale Datasets | 2010 | VLDB | 0.0004291425 |
| 82 | Space-Efficient Online Computation of Quantile Summaries | 2001 | SIGMOD | 0.00036378991 |
| 451 | Mergeable Summaries | 2012 | PODS | 0.00018151445 |
| 3,044 | Holistic UDAFs at Streaming Speeds | 2004 | SIGMOD | 7.820774e-05 |
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