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LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems

Summary: LSched is a fully learned, workload-aware query scheduler for in-memory analytical DBs, enabling inter- and intra-query scheduling under dynamic workloads. It accounts for operator types and pipelining, beating heuristics and prior RL by 35-50% on TPC-H, SSB, and JOB. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
h09c4f883fec04060
Venue
SIGMOD
Year
2022
Pagerank
6.3006152e-05
Overall Rank
5,041 | 66.11%
DOI
10.1145/3514221.3526158

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{sabek_sigmod22,
        title = {{LSched: A Workload-Aware Learned Query Scheduler for Analytical Database Systems}},
        author = {Sabek, Ibrahim and Ukyab, Tenzin Samten and Kraska, Tim},
        series = {{SIGMOD} '22},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3514221.3526158},
        url = {https://dl.acm.org/doi/10.1145/3514221.3526158},
        year = {2022}
}

Incoming Citations (Sorted by Pagerank)

Showing 16 of 16 citing papers.

Rank Citing Paper Year Venue Pagerank
3,487 LOGER: A Learned Optimizer towards Generating Efficient and Robust Query Execution Plans 2023 VLDB 7.263041e-05
3,563 Auto-WLM: Machine Learning Enhanced Workload Management in Amazon Redshift 2023 SIGMOD 7.2042148e-05
4,666 Intelligent Scaling in Amazon Redshift 2024 SIGMOD 6.479878e-05
4,890 Can Learned Models Replace Hash Functions? 2023 VLDB 6.3682031e-05
8,403 The Case for Learned In-Memory Joins 2023 VLDB 5.3389852e-05
9,610 LIMAO: A Framework for Lifelong Modular Learned Query Optimization 2025 VLDB 5.1526493e-05
10,148 Improving DBMS Scheduling Decisions with Accurate Performance Prediction on Concurrent Queries 2025 VLDB 5.0715586e-05
10,168 PLATON: Top-down R-tree Packing with Learned Partition Policy 2023 SIGMOD 5.0682654e-05
10,309 Intra-Query Runtime Elasticity for Cloud-Native Data Analysis 2025 SIGMOD 5.0386264e-05
10,666 P-MOSS: Scheduling Main-Memory Indexes Over NUMA Servers Using Next Token Prediction 2026 SIGMOD 4.9793485e-05
10,735 AQD: Online Adaptive Query Dispatcher for HTAP Databases 2026 VLDB 4.9793485e-05
10,883 QDBO: A Real-time Quantum-augmented Database System Optimizer 2026 VLDB 4.9793485e-05
10,930 Seron: Smart Query Router for Multi-Primary Cloud-Native Databases with Shared Storage 2026 VLDB 4.9793485e-05
11,447 LASER: Buffer-Aware Learned Query Scheduling in Master-Standby Databases 2025 VLDB 4.9793485e-05
11,499 Flux: Decoupled Auto-Scaling for Heterogeneous Query Workload in Alibaba AnalyticDB 2024 SIGMOD 4.9793485e-05
11,714 QaaD (Query-as-a-Data): Scalable Execution of Massive Number of Small Queries in Spark 2023 SIGMOD 4.9793485e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 23 of 23 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
15 How Good Are Query Optimizers, Really? 2016 VLDB 0.00061066921
40 The Case for Learned Index Structures 2018 SIGMOD 0.00046284649
85 Learned Cardinalities: Estimating Correlated Joins with Deep Learning 2019 CIDR 0.00035864347
98 LEO - DB2's LEarning Optimizer 2001 VLDB 0.00034106982
145 Neo: A Learned Query Optimizer 2019 VLDB 0.0002908188
215 Morsel-Driven Parallelism: A NUMA-Aware Query Evaluation Framework for the Many-Core Age 2014 SIGMOD 0.00024598661
362 Bao: Making Learned Query Optimization Practical 2021 SIGMOD 0.00019989474
373 Umbra: A Disk-Based System with In-Memory Performance 2020 CIDR 0.00019711632
430 ALEX: An Updatable Adaptive Learned Index 2020 SIGMOD 0.00018409112
431 HYRISE—A Main Memory Hybrid Storage Engine 2011 VLDB 0.00018403783
436 Optimizing Space Amplification in RocksDB 2017 CIDR 0.00018319035
463 The PGM-index: a fully-dynamic compressed learned index with provable worst-case bounds 2020 VLDB 0.00017804544
868 Learning Multi-dimensional Indexes 2020 SIGMOD 0.00013354403
1,132 Qd-tree: Learning Data Layouts for Big Data Analytics 2020 SIGMOD 0.00011898257
1,191 Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads 2021 VLDB 0.00011590153
1,446 LISA: A Learned Index Structure for Spatial Data 2020 SIGMOD 0.00010629222
1,878 Effectively Learning Spatial Indices 2020 VLDB 9.4451309e-05
2,137 Quickstep: A Data Platform Based on the Scaling-Up Approach 2018 VLDB 8.9777553e-05
3,714 The Case for a Learned Sorting Algorithm 2020 SIGMOD 7.0769061e-05
4,055 Scaling Up Concurrent Main-Memory Column-Store Scans: Towards Adaptive NUMA-aware Data and Task Placement 2015 VLDB 6.8270333e-05
4,388 Self-Tuning Query Scheduling for Analytical Workloads 2021 SIGMOD 6.6228033e-05
5,974 Towards instance-optimized data systems 2021 VLDB 5.9305575e-05
7,341 Scalable Multi-Query Execution using Reinforcement Learning 2021 SIGMOD 5.5481233e-05
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1 6,872 Distribution-Based Query Scheduling 2013 VLDB
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9 11,447 LASER: Buffer-Aware Learned Query Scheduling in Master-Standby Databases 2025 VLDB
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