Robust Estimation With Sampling and Approximate Pre-Aggregation
Summary: APA combines random sampling with pre-aggregation for accurate aggregates on categorical and mixed data. It yields SUM/AVG accuracy gains over plain or stratified sampling, boosting practical AQP for categorical data. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
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Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,368 | Online Maintenance of Very Large Random Samples | 2004 | SIGMOD | 8.9501526e-05 |
| 3,944 | AQP++: Connecting Approximate Query Processing With Aggregate Precomputation for Interactive Analytics | 2018 | SIGMOD | 6.6078243e-05 |
| 5,817 | Derby/S: A DBMS for Sample-Based Query Answering | 2006 | SIGMOD | 5.3156799e-05 |
| 6,740 | Combining Aggregation and Sampling (Nearly) Optimally for Approximate Query Processing | 2021 | SIGMOD | 4.944395e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 14 of 14 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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