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Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing

Summary: Introduces PASS, Precomputation-Assisted Stratified Sampling: a partitioned tree of partial aggregates to speed up AQP. Exact answers for partition-aligned predicates via DFS; partial overlaps are approximated by stratified samples with an algorithm for near-optimal partitioning. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6230
Venue
SIGMOD
Year
2021
Pagerank
5.9443409e-05
Overall Rank
6,206 | 57.43%
DOI
10.1145/3448016.3457277

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{liang_sigmod21,
        title = {{Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing}},
        author = {Liang, Xi and Sintos, Stavros and Shang, Zechao and Krishnan, Sanjay},
        series = {{SIGMOD} '21},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3448016.3457277},
        url = {https://dl.acm.org/doi/10.1145/3448016.3457277},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 11 of 11 citing papers.

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Outgoing Citations (Sorted by Pagerank)

Showing 29 of 29 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
9 Online Aggregation 1997 SIGMOD 0.00077458002
173 Simple Random Sampling from Relational Databases 1986 VLDB 0.00027273858
267 Optimal Histograms with Quality Guarantees 1998 VLDB 0.00022798161
323 DeepDB: Learn from Data, not from Queries! 2020 VLDB 0.00021264788
401 Deep Unsupervised Cardinality Estimation 2020 VLDB 0.00019092557
451 Mergeable Summaries 2012 PODS 0.00018151445
553 Congressional Samples for Approximate Answering of Group-By Queries 2000 SIGMOD 0.00016590619
648 Progressive Approximate Aggregate Queries with a Multi-Resolution Tree Structure 2001 SIGMOD 0.00015324657
772 VerdictDB: Universalizing Approximate Query Processing 2018 SIGMOD 0.00014147905
802 Random Sampling over Joins Revisited 2018 SIGMOD 0.00013907725
819 Quickr: Lazily Approximating Complex AdHoc Queries in BigData Clusters 2016 SIGMOD 0.00013815639
909 Dynamic Sample Selection for Approximate Query Processing 2003 SIGMOD 0.00013291205
1,044 Fine-grained Partitioning for Aggressive Data Skipping 2014 SIGMOD 0.0001244236
1,108 Approximate Query Processing: No Silver Bullet 2017 SIGMOD 0.00012145154
1,166 ICICLES: Self-tuning Samples for Approximate Query Answering 2000 VLDB 0.00011850439
1,668 Global Optimization of Histograms 2001 SIGMOD 0.00010057026
1,736 A Sample-and-Clean Framework for Fast and Accurate Query Processing on Dirty Data 2014 SIGMOD 9.8984415e-05
1,962 Sample + Seek: Approximating Aggregates with Distribution Precision Guarantee 2016 SIGMOD 9.3978414e-05
1,995 Database Learning: Toward a Database that Becomes Smarter Every Time 2017 SIGMOD 9.3403665e-05
2,608 A Robust, Optimization-Based Approach for Approximate Answering of Aggregate Queries 2001 SIGMOD 8.347674e-05
3,366 AQP++: Connecting Approximate Query Processing With Aggregate Precomputation for Interactive Analytics 2018 SIGMOD 7.4748604e-05
3,370 Revisiting Reuse for Approximate Query Processing 2017 VLDB 7.4700891e-05
3,575 Optimal Histograms for Hierarchical Range Queries (Extended Abstract) 2000 PODS 7.2946291e-05
6,654 Robust Estimation With Sampling and Approximate Pre-Aggregation 2003 VLDB 5.8131331e-05
7,048 Learning to Sample: Counting with Complex Queries 2020 VLDB 5.7178054e-05
8,002 Fast and Reliable Missing Data Contingency Analysis with Predicate-Constraints 2020 SIGMOD 5.5085906e-05
8,108 Experiences with Approximating Queries in Microsoft’s Production Big-Data Clusters 2019 VLDB 5.4850569e-05
8,616 CoopStore: Optimizing Precomputed Summaries for Aggregation 2020 VLDB 5.4004741e-05
8,714 Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views 2015 VLDB 5.3778009e-05
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