When Can We Trust Progress Estimators for SQL Queries?
Summary: Worst-case: for SQL progress estimation, no estimator beats the trivial 0–100% bound; they propose an optimal error-bound estimator for that regime. In typical SQL workloads, progress estimates are accurate with small errors; empirical results show such good scenarios are common, and combining estimators improves robustness. (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 13 of 13 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 9 of 9 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 14 | Online Aggregation | 1997 | SIGMOD | 0.0010801504 |
| 18 | On Random Sampling over Joins | 1999 | SIGMOD | 0.00092385438 |
| 99 | On the Propagation of Errors in the Size of Join Results | 1991 | SIGMOD | 0.00050022914 |
| 211 | Join Synopses for Approximate Query Answering | 1999 | SIGMOD | 0.00033981214 |
| 217 | Ripple Joins for Online Aggregation | 1999 | SIGMOD | 0.00033536712 |
| 220 | Efficient Mid-Query Re-Optimization of Sub-Optimal Query Execution Plans | 1998 | SIGMOD | 0.00033194808 |
| 327 | Balancing Histogram Optimality and Practicality for Query Result Size Estimation | 1995 | SIGMOD | 0.00027308479 |
| 650 | Robust Query Processing through Progressive Optimization | 2004 | SIGMOD | 0.00018659177 |
| 1,228 | Toward a Progress Indicator for Database Queries | 2004 | SIGMOD | 0.00013164884 |
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