A Spark Optimizer for Adaptive, Fine-Grained Parameter Tuning
Summary: Controls all per-query tunable parameters in Spark’s Adaptive Query Execution via a hybrid compile-time/runtime, multi-granularity scheme to handle diverse, correlated parameters. Poses tuning as multi-objective (latency vs cost), with models/solvers achieving sub-second solves and much better latency/cost tradeoffs (63–65% latency reduction vs 18–25% for prior MOO methods) and superior adaptability to user preferences. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Chenghao Lyu (University of Massachusetts Amherst)
- 2. Qi Fan (Ecole Polytechnique)
- 3. Philippe Guyard (Ecole Polytechnique)
- 4. Yanlei Diao (Ecole Polytechnique; University of Massachusetts Amherst)
BibTeX Citation
@article{lyu_vldb24,
title = {{A Spark Optimizer for Adaptive, Fine-Grained Parameter Tuning}},
author = {Lyu, Chenghao and Fan, Qi and Guyard, Philippe and Diao, Yanlei},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {11},
pages = {3565--3579},
doi = {10.14778/3681954.3682021},
url = {https://doi.org/10.14778/3681954.3682021},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 3 of 3 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,771 | Rockhopper: A Robust Optimizer for Spark Configuration Tuning in Production Environment | 2025 | SIGMOD | 5.2209769e-05 |
| 10,547 | Scarf: Self-Adaptive Tuning via Multi-Objective Reinforcement Learning for Apache Flink | 2026 | VLDB | 5.093636e-05 |
| 11,083 | Graph Transformers for Query Plan Representation: Potentials and Challenges | 2025 | VLDB | 5.093636e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 39 of 39 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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