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Learning a Partitioning Advisor for Cloud Databases
Summary: DRL-based partitioning advisor for cloud DBMS automates partitioning decisions for OLAP workloads by learning cost tradeoffs and placement policies. Evaluations show it finds non-trivial partitionings across diverse workloads and outperforms classical automated approaches.
(summarized by gpt-5-nano on Feb 09 2026)
- Paper ID
- 5919
- Venue
- SIGMOD
- Year
- 2020
- Pagerank
- 7.6107677e-05
- Overall Rank
- 3,076 | 78.61%
- DOI
-
10.1145/3318464.3389704
Incoming Non-self Citations Over Time
Incoming Citations (Sorted by Pagerank)
Showing 24 of 24 citing papers.
| Rank |
Citing Paper |
Year |
Venue |
Pagerank |
| 1,407 |
DB-BERT: A Database Tuning Tool that "Reads the Manual" |
2022 |
SIGMOD |
0.00012146739 |
| 2,121 |
Balsa: Learning a Query Optimizer Without Expert Demonstrations |
2022 |
SIGMOD |
9.5017232e-05 |
| 2,320 |
High-Throughput Vector Similarity Search in Knowledge Graphs |
2023 |
SIGMOD |
9.0366225e-05 |
| 3,473 |
AI Meets Database: AI4DB and DB4AI |
2021 |
SIGMOD |
7.062864e-05 |
| 3,779 |
Instance-Optimized Data Layouts for Cloud Analytics Workloads |
2021 |
SIGMOD |
6.7747205e-05 |
| 3,828 |
Zero-Shot Cost Models for Out-of-the-box Learned Cost Prediction |
2022 |
VLDB |
6.7208524e-05 |
| 4,913 |
UDO: Universal Database Optimization using Reinforcement Learning |
2021 |
VLDB |
5.8316231e-05 |
| 5,258 |
One Model to Rule them All: Towards Zero-Shot Learning for Databases |
2022 |
CIDR |
5.5998705e-05 |
| 5,861 |
Machine Learning for Databases |
2021 |
VLDB |
5.298883e-05 |
| 5,924 |
HMAB: Self-Driving Hierarchy of Bandits for Integrated Physical Database Design Tuning |
2023 |
VLDB |
5.2719183e-05 |
| 6,379 |
A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning |
2023 |
SIGMOD |
5.0909479e-05 |
| 6,466 |
Pando: Enhanced Data Skipping with Logical Data Partitioning |
2023 |
VLDB |
5.0528281e-05 |
| 6,803 |
Proteus: Autonomous Adaptive Storage for Mixed Workloads |
2022 |
SIGMOD |
4.9224958e-05 |
| 6,984 |
Replicated Layout for In-Memory Database Systems |
2022 |
VLDB |
4.873081e-05 |
| 7,476 |
Lachesis: Automatic Partitioning for UDF-Centric Analytics |
2021 |
VLDB |
4.7188928e-05 |
| 8,103 |
Grep: A Graph Learning Based Database Partitioning System |
2023 |
SIGMOD |
4.5852201e-05 |
| 8,578 |
Robust and Budget-Constrained Encoding Configurations for In-Memory Database Systems |
2022 |
VLDB |
4.4923477e-05 |
| 8,775 |
SkinnerMT: Parallelizing for Efficiency and Robustness in Adaptive Query Processing on Multicore Platforms |
2023 |
VLDB |
4.4553047e-05 |
| 8,847 |
Towards Foundation Database Models |
2025 |
CIDR |
4.4371897e-05 |
| 9,006 |
Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems |
2024 |
VLDB |
4.4101482e-05 |
| 9,905 |
Progressive Partitioning for Parallelized Query Execution in Google's Napa |
2023 |
VLDB |
4.258022e-05 |
| 10,230 |
Breaking the Isolation-Freshness Trade-off: Joint Adaptive Storage Optimization for HTAP Systems |
2026 |
VLDB |
4.1945683e-05 |
| 10,497 |
PilotDB: Database-Agnostic Online Approximate Query Processing with A Priori Error Guarantees |
2025 |
SIGMOD |
4.1945683e-05 |
| 10,695 |
HAWK: A Workload-driven Hierarchical Deadlock Detection Approach in Distributed Database System |
2025 |
VLDB |
4.1945683e-05 |
Outgoing Citations (Sorted by Pagerank)
Showing 19 of 19 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 |
0.00059038975 |
| 204 |
Learned Cardinalities: Estimating Correlated Joins with Deep Learning |
2019 |
CIDR |
0.00034784455 |
| 209 |
Schism: a Workload-Driven Approach to Database Replication and Partitioning |
2010 |
VLDB |
0.00034468292 |
| 258 |
DB2 Design Advisor: Integrated Automatic Physical Database Design |
2004 |
VLDB |
0.0003022091 |
| 285 |
Automating Physical Database Design in a Parallel Database |
2002 |
SIGMOD |
0.0002899128 |
| 333 |
Neo: A Learned Query Optimizer |
2019 |
VLDB |
0.00027206884 |
| 359 |
Self-Driving Database Management Systems |
2017 |
CIDR |
0.0002592783 |
| 514 |
An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning |
2019 |
SIGMOD |
0.0002124895 |
| 661 |
Database Tuning Advisor for Microsoft SQL Server 2005 |
2004 |
VLDB |
0.00018481174 |
| 679 |
Skew-Aware Automatic Database Partitioning in Shared-Nothing, Parallel OLTP Systems |
2012 |
SIGMOD |
0.00018215154 |
| 801 |
SageDB: A Learned Database System |
2019 |
CIDR |
0.00016505496 |
| 806 |
An End-to-End Learning-based Cost Estimator |
2020 |
VLDB |
0.00016434274 |
| 2,413 |
Automated Partitioning Design in Parallel Database Systems |
2011 |
SIGMOD |
8.8672223e-05 |
| 2,983 |
Supporting Table Partitioning By Reference in Oracle |
2008 |
SIGMOD |
7.7796493e-05 |
| 3,821 |
Locality-aware Partitioning in Parallel Database Systems |
2015 |
SIGMOD |
6.7281515e-05 |
| 5,118 |
AdaptDB: Adaptive Partitioning for Distributed Joins |
2017 |
VLDB |
5.6820984e-05 |
| 5,451 |
NashDB: An End-to-End Economic Method for Elastic Database Fragmentation, Replication, and Provisioning |
2018 |
SIGMOD |
5.5002949e-05 |
| 7,372 |
Model-Free Control for Distributed Stream Data Processing using Deep Reinforcement Learning |
2018 |
VLDB |
4.7496881e-05 |
| 7,715 |
Query Centric Partitioning and Allocation for Partially Replicated Database Systems |
2017 |
SIGMOD |
4.6699261e-05 |
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