Andy is an Associate Professor with Indefinite Tenure of Databaseology in the Computer Science Department at Carnegie Mellon University. My research interest is in database management systems, specifically main memory systems, self-driving / autonomous architectures, transaction processing systems, and large-scale data analytics.

00:00 Introduction and Welcome

01:31 Understanding Database Optimization

05:48 Understanding When Database Tuning is Needed

08:45 Understanding Database Optimization Difficulties

16:16 Understanding Default Settings in Databases

22:35 Role of Machine Learning in Database Tuning

22:38 Introduction to Ottertune

28:36 Data Collection for Machine Learning Model

35:25 Deployment and Data Collection Process

38:03 Admitting the Limitations of Current Model

38:53 Challenges in Predicting Performance Improvements

39:28 The Importance of Data Collection Over Time

39:52 Avoiding Weekend and Holiday Tuning

40:05 Introducing New Features for Database Comparison

42:09 Provisioning Recommendations and Performance Predictions

43:03 The Importance of Telemetry in Understanding Database Performance

44:01 Handling Dramatic Changes in Database Workloads

44:48 Preparing for Predictable Traffic Spikes

48:13 The Importance of Testing in Database Optimization

53:33 The Future of Database Optimization

55:50 Common Mistakes in Database Management

01:09:15 The Future of Holistic Database Tuning

Links:

Ottertune: https://ottertune.com/

Andy Pavlo: https://www.cs.cmu.edu/~pavlo/

CMU youtube: https://www.youtube.com/@UCHnBsf2rH-K7pn09rb3qvkA

Resources:

CMU: https://15799.courses.cs.cmu.edu/spring2022/schedule.html

Ottertune blog: https://ottertune.com/blog

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