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CliffGuard: A Principled Framework for Finding Robust Database Designs
Summary: CliffGuard applies robust optimization to select physical designs (indices, materialized views) under workload uncertainty. Users set risk tolerance to trade nominal optimality for robustness, yielding predictable performance amid workload shifts.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 5071
- Venue
- SIGMOD
- Year
- 2015
- Pagerank
- 5.424205e-05
- Overall Rank
- 5,581 | 61.18%
- DOI
-
10.1145/2723372.2749454
Incoming Non-self Citations Over Time
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| 496 |
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| 650 |
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| 1,152 |
Blink and It's Done: Interactive Queries on Very Large Data |
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0.00013645792 |
| 1,236 |
Least Expected Cost Query Optimization: An Exercise in Utility |
1999 |
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| 1,443 |
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| 1,807 |
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| 4,013 |
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6.529956e-05 |
| 4,482 |
Variance Aware Optimization of Parameterized Queries |
2010 |
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6.1482936e-05 |
| 4,506 |
Stochastic Database Cracking: Towards Robust Adaptive Indexing in Main-Memory Column-Stores |
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6.1319277e-05 |
| 5,435 |
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2001 |
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5.5043441e-05 |
| 5,868 |
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| 6,075 |
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