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Scalable Multi-Query Execution using Reinforcement Learning
Summary: RouLette uses reinforcement learning to drive adaptive, runtime sharing for multi-query execution, avoiding costly pre-optimization. It delivers 1.6–28.3× throughput gains vs a query-at-a-time engine and up to 6.5× vs sharing prototypes on TPC-DS-like workloads.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 6081
- Venue
- SIGMOD
- Year
- 2021
- Pagerank
- 4.7193668e-05
- Overall Rank
- 7,461 | 48.15%
- DOI
-
10.1145/3448016.3452799
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 7 of 7 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 27 of 27 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank |
Cited Paper |
Year |
Venue |
Pagerank |
| 71 |
How Good Are Query Optimizers, Really? |
2016 |
VLDB |
0.00059446482 |
| 80 |
Weaving Relations for Cache Performance |
2001 |
VLDB |
0.00055735291 |
| 116 |
Eddies: Continuously Adaptive Query Processing |
2000 |
SIGMOD |
0.00046191288 |
| 179 |
Efficient and Extensible Algorithms for Multi Query Optimization |
2000 |
SIGMOD |
0.00037637319 |
| 203 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034868567 |
| 216 |
Ripple Joins for Online Aggregation |
1999 |
SIGMOD |
0.00033560137 |
| 244 |
Continuously Adaptive Continuous Queries over Streams |
2002 |
SIGMOD |
0.00031037999 |
| 329 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00027301488 |
| 515 |
QPipe: A Simultaneously Pipelined Relational Query Engine |
2005 |
SIGMOD |
0.00021209491 |
| 659 |
The Making of TPC-DS |
2006 |
VLDB |
0.00018514913 |
| 752 |
Deep Unsupervised Cardinality Estimation |
2020 |
VLDB |
0.00017138049 |
| 934 |
SharedDB: Killing One Thousand Queries With One Stone |
2012 |
VLDB |
0.00015201246 |
| 977 |
Pipelining in Multi-Query Optimization |
2001 |
PODS |
0.000148774 |
| 1,027 |
Cooperative Scans: Dynamic Bandwidth Sharing in a DBMS |
2007 |
VLDB |
0.0001458537 |
| 1,041 |
Adaptive Ordering of Pipelined Stream Filters |
2004 |
SIGMOD |
0.00014470785 |
| 1,233 |
Maximizing the Output Rate of Multi-Way Join Queries over Streaming Information Sources |
2003 |
VLDB |
0.0001312635 |
| 1,239 |
Selectivity Estimation for Range Predicates using Lightweight Models |
2019 |
VLDB |
0.00013091459 |
| 1,296 |
The DataPath System: A Data-Centric Analytic Processing Engine for Large Data Warehouses |
2010 |
SIGMOD |
0.00012742585 |
| 1,430 |
A Scalable, Predictable Join Operator for Highly Concurrent Data Warehouses |
2009 |
VLDB |
0.0001202506 |
| 1,475 |
Efficient Exploitation of Similar Subexpressions for Query Processing |
2007 |
SIGMOD |
0.00011765071 |
| 1,921 |
Selecting Subexpressions to Materialize at Datacenter Scale |
2018 |
VLDB |
0.00010085899 |
| 1,939 |
Procella: Unifying serving and analytical data at YouTube |
2019 |
VLDB |
0.00010019433 |
| 2,928 |
Shared Workload Optimization |
2014 |
VLDB |
7.881485e-05 |
| 3,236 |
TPC-DS, Taking Decision Support Benchmarking to the Next Level |
2002 |
SIGMOD |
7.3294564e-05 |
| 4,263 |
The Case for Precision Sharing |
2004 |
VLDB |
6.3014952e-05 |
| 4,945 |
Lifting the Burden of History from Adaptive Query Processing |
2004 |
VLDB |
5.8115261e-05 |
| 5,298 |
MQJoin: Efficient Shared Execution of Main-Memory Joins |
2016 |
VLDB |
5.5762694e-05 |
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Year |
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Pagerank |
| 7,220 |
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SIGMOD |
4.7926382e-05 |
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2025 |
VLDB |
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| 5,289 |
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2022 |
SIGMOD |
5.5790771e-05 |
| 6,639 |
Leveraging Query Logs and Machine Learning for Parametric Query Optimization |
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VLDB |
4.976781e-05 |
| 10,574 |
Holistic query Approximation via RL Modeling |
2025 |
VLDB |
4.1905499e-05 |
| 5,524 |
Facilitating SQL Query Composition and Analysis |
2020 |
SIGMOD |
5.4589341e-05 |
| 4,966 |
Releasing Cloud Databases from the Chains of Performance Prediction Models |
2017 |
CIDR |
5.7949047e-05 |
| 5,994 |
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2021 |
SIGMOD |
5.2367998e-05 |
| 5,645 |
Database Workload Characterization with Query Plan Encoders |
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VLDB |
5.3928148e-05 |
| 5,682 |
LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems |
2022 |
SIGMOD |
5.3752251e-05 |