Date	Topic	Slides	Video
Jan 17, 2022	Martin Luther King Day — No Class
Jan 19, 2022	#01 — Course Introduction and Database Automation Background (Zoom Lecture) S.Chaudhuri et al., Self-Tuning Database Systems: A Decade of Progress, in VLDB, 2007 (Optional) A. Pavlo et al., External vs. Internal: An Essay on Machine Learning Agents for Autonomous Database Management Systems, in IEEE Data Engineering Bulletin, 2019 (Optional)
Jan 24, 2022	#02 — Self-Driving Database Overview (Zoom Lecture) A. Pavlo et al., Self-Driving Database Management Systems, in CIDR, 2017 A. Pavlo et al., Make Your Database System Dream of Electric Sheep: Towards Self-Driving Operation, in VLDB, 2021 (Optional)
Jan 26, 2022	#03 — Index Recommendation I (Zoom Lecture) S.Chaudhuri et al., AutoAdmin “What-if” Index Analysis Utility, in SIGMOD, 1998 S.Chaudhuri et al., An Efficient, Cost-Driven Index Selection Tool for Microsoft SQL Server, in VLDB, 1997 (Optional)
Jan 31, 2022	#04 — Index Recommendation II B.Ding et al., AI Meets AI: Leveraging Query Executions to Improve Index Recommendations, in SIGMOD, 2019
Feb 02, 2022	#05 — Index Recommendation III J. Kossmann et al., Magic mirror in my hand, which is the best in the land? An Experimental Evaluation of Index Selection Algorithms, in VLDB, 2020
Feb 07, 2022	#06 — Knob/Parameter Tuning I D. Van Aken et al., Automatic Database Management System Tuning Through Large-scale Machine Learning, in SIGMOD, 2017 T. Xu et al., Hey, You Have Given Me Too Many Knobs! Understanding and Dealing with Over-Designed Configuration in System Software, in FSE, 2015 (Optional) M. Silva-Muñoz​ et al., Automatic Configuration of the Cassandra Database using iRace, in PeerJ Computer Science (Optional)
Feb 09, 2022	#07 — Knob/Parameter Tuning II J. Zhang et al., An End-to-End Automatic Cloud Database Tuning System Using Deep Reinforcement Learning, in SIGMOD, 2019 D. Van Aken et al., An Inquiry into Machine Learning-based Automatic Configuration Tuning Services on Real-World Database Management Systems, in VLDB, 2021 (Optional) S. Cereda​ et al., CGPTuner: a Contextual Gaussian Process Bandit Approach for the Automatic Tuning of IT Configurations Under Varying Workload Conditions, in VLDB, 2021 (Optional)
Feb 14, 2022	#08 — Knob/Parameter Tuning III Z. Zhang et al., ResTune: Resource Oriented Tuning Boosted by Meta-Learning for Cloud Databases, in SIGMOD, 2021 G. Li et al., QTune: A Query-Aware Database Tuning System with Deep Reinforcement Learning, in VLDB, 2019 (Optional)
Feb 16, 2022	#09 — Knob/Parameter Tuning IV Z. Zhang et al., Facilitating Database Tuning with Hyper-Parameter Optimization: A Comprehensive Experimental Evaluation, in arXiv, 2021
Feb 21, 2022	#10 — Partitioning B. Hilprecht et al., Learning a Partitioning Advisor for Cloud Databases, in SIGMOD, 2020
Feb 23, 2022	#11 — Workload Modeling I L. Ma et al., Query-based Workload Forecasting for Self-Driving Database Management Systems, in SIGMOD, 2018 P. Martin et al., Workload Models for Autonomic Database Management Systems, in ICAS, 2006 (Optional) Z. Yan et al., Workload-Aware Performance Tuning for Autonomous DBMSs, in ICDE, 2021 (Optional)
Feb 28, 2022	#12 — Workload Modeling II D. Paul et al., Database Workload Characterization with Query Plan Encoders, in arXiv, 2021 S. Jain et al., Query2Vec: An Evaluation of NLP Techniques for Generalized Workload Analytics, in arXiv, 2018 (Optional) Z. Zolaktaf et al., Facilitating SQL Query Composition and Analysis, in SIGMOD, 2020 (Optional) S. Chaudhuri et al., Compressing SQL workloads, in SIGMOD, 2002 (Optional)
Mar 02, 2022	#13 — Behavior Modeling I L. Ma et al., MB2: Decomposed Behavior Modeling for Self-Driving Database Management Systems, in SIGMOD, 2021
Mar 07, 2022	Spring Break — No Class
Mar 09, 2022	Spring Break — No Class
Mar 14, 2022	Student Project Proposals	—	—
Mar 16, 2022	#14 — Behavior Modeling II R. Marcus et al., Plan-Structured Deep Neural Network Models for Query Performance Prediction, in VLDB, 2019
Mar 21, 2022	#15 — Training Data Collection F. Ventura et al., Expand your Training Limits! Generating Training Data for ML-based Data Management, in SIGMOD, 2021 L. Ma et al., Active Learning for ML Enhanced Database Systems, in SIGMOD, 2020 (Optional)
Mar 23, 2022	#16 — Automatic SQL Rewriting X. Zhou et al., A Learned Query Rewrite System using Monte Carlo Tree Search, in VLDB, 2022 P. Dintyala et al., SQLCheck: Automated Detection and Diagnosis of SQL Anti-Patterns, in SIGMOD, 2020 (Optional)
Mar 28, 2022	#17 — Query Optimization I R. Marcus et al., Bao: Making Learned Query Optimizers Practical, in SIGMOD, 2021 S. Krishnan et al., Learning to Optimize Join Queries With Deep Reinforcement Learning, in arXiv, 2018 (Optional)
Mar 30, 2022	Student Project Discussions		—
Apr 04, 2022	#18 — Autonomous Systems I J. Wang et al., UDO: Universal Database Optimization using Reinforcement Learning, in VLDB, 2021
Apr 06, 2022	#19 — Autonomous Systems II G. Li et al., openGauss: An Autonomous Database System, in VLDB, 2021
Apr 11, 2022	#20 — Autonomous Systems III Y. Park et al., Database Learning: Toward a Database that Becomes Smarter Every Time, in SIGMOD, 2017 Q. Ma et al., Learned Approximate Query Processing: Make it Light, Accurate and Fast, in CIDR, 2021 (Optional)		—
Apr 13, 2022	#21 — Autonomous Systems IV Z. Wu et al., A Unified Transferable Model for ML-Enhanced DBMS, in CIDR, 2022
Apr 18, 2022	#22 — Autonomous Systems V S.Das et al., Automatically Indexing Millions of Databases in Microsoft Azure SQL Database, in SIGMOD, 2019
Apr 20, 2022	Student Project Presentations	—	—
Apr 25, 2022	Guest Speaker: Bailu Ding (Microsoft Research) (Zoom Lecture)	—	—
Apr 27, 2022	Guest Speaker: Weiwei Gong (Oracle) (Zoom Lecture)	—	—