Exploiting Soft and Hard Correlations in Big Data Query Optimization
Summary: EXORD exploits both hard and soft correlations to accelerate big-data query optimization, addressing uncertainty that RDBMS-based methods ignore. A three-phase pipeline validates soft correlations, selects/prepares with violation handling, and deploys them in optimization; a cost-benefit model yields a polynomial-time heuristic; Hive/Hadoop prototype achieves >10x speedup with low overhead. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Hai Liu
- 2. Dongqing Xiao
- 3. Pankaj Didwania
- 4. Mohamed Y. Eltabakh
Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,483 | Discovery of Approximate (and Exact) Denial Constraints | 2020 | VLDB | 8.6864916e-05 |
| 6,498 | Memory-Aware Framework for Efficient Second-Order Random Walk on Large Graphs | 2020 | SIGMOD | 5.0392468e-05 |
| 9,410 | Leveraging Application Data Constraints to Optimize Database-Backed Web Applications | 2023 | VLDB | 4.3441378e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 13 of 13 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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