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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)

Paper ID
1665
Venue
PODS
Year
2015
Pagerank
5.093636e-05
Overall Rank
12,100 | 16.99%
DOI
10.1145/2745754.2745781

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Authors

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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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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