Lecture 1: SQL Optimization Background (15-799)
53:57Lecture 2: History of Query Optimizers ft. IBM System R (15-799)
1:10:40Lecture 3: IBM Starburst Query Rewriter + Optimizer (15-799)
1:14:08Lecture 4: EXODUS + Volcano Query Optimizer Generators (15-799)
1:23:28Lecture 5: Cascades Query Optimizer (15-799)
1:27:28Lecture 6: Query Plan Transformations (15-799)
1:20:35Lecture 7: Join Ordering: Bottom-up (15-799)
1:08:22Lecture 8: Join Ordering: Top-Down / Transformational (15-799)
1:10:21Lecture 9: Search Parallelization: Bottom-up (15-799)
59:34Lecture 10: Search Parallelization: Top-Down (15-799)
1:11:32Lecture 11: Unnesting Queries (15-799)
1:14:15Lecture 12: Query Cost Models: Statistics (15-799)
1:14:48Lecture 13: Query Cost Models: Cardinality Estimation (15-799)
1:11:38Lecture 14: Query Cost Models: More Cardinality Estimation (15-799)
1:11:53Lecture 9: Search Parallelization: Bottom-up (15-799)
This lecture discusses bottom-up strategies for parallelizing query plan search, focusing on distributing computation across multiple processors to accelerate optimization.
Andy Pavlo (https://www.cs.cmu.edu/~pavlo/)
Slides: https://15799.courses.cs.cmu.edu/spring2025/slides/09-parallelization1.pdf
15-799 Special Topics in Database: Query Optimization (Spring 2025)
Carnegie Mellon University
Lecture 8: Join Ordering: Top-Down / Transformational (15-799)
Next · Lecture 10Lecture 10: Search Parallelization: Top-Down (15-799)
Seminar notes & discussion
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