Skip to content
lectern.tv
CMU 15-799: Query Optimization in Modern Database Systems →0/14
1

Lecture 1: SQL Optimization Background (15-799)

53:57
2

Lecture 2: History of Query Optimizers ft. IBM System R (15-799)

1:10:40
3

Lecture 3: IBM Starburst Query Rewriter + Optimizer (15-799)

1:14:08
4

Lecture 4: EXODUS + Volcano Query Optimizer Generators (15-799)

1:23:28
5

Lecture 5: Cascades Query Optimizer (15-799)

1:27:28
6

Lecture 6: Query Plan Transformations (15-799)

1:20:35
7

Lecture 7: Join Ordering: Bottom-up (15-799)

1:08:22
8

Lecture 8: Join Ordering: Top-Down / Transformational (15-799)

1:10:21
9

Lecture 9: Search Parallelization: Bottom-up (15-799)

59:34
10

Lecture 10: Search Parallelization: Top-Down (15-799)

1:11:32
11

Lecture 11: Unnesting Queries (15-799)

1:14:15
12

Lecture 12: Query Cost Models: Statistics (15-799)

1:14:48
13

Lecture 13: Query Cost Models: Cardinality Estimation (15-799)

1:11:38
14

Lecture 14: Query Cost Models: More Cardinality Estimation (15-799)

1:11:53

Lecture 12: Query Cost Models: Statistics (15-799)

Andy PavloCarnegie Mellon University

Professor

1:14:48·2025·graduate level

This session explores the fundamental role of statistical information in query cost models, discussing how data distributions and metadata inform optimizer decisions.

Systems & CSDatabase SystemsQuery Cost EstimationDatabase StatisticsCost-Based Optimization

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

Slides: https://15799.courses.cs.cmu.edu/spring2025/slides/12-costmodel.pdf

15-799 Special Topics in Database: Query Optimization (Spring 2025)

Carnegie Mellon University

Previous · Lecture 11

Lecture 11: Unnesting Queries (15-799)

Next · Lecture 13

Lecture 13: Query Cost Models: Cardinality Estimation (15-799)

Comments

Add a comment...Sign in