Pluralsight - SQL Server: Common Query Tuning Problems and Solutions - Part 1 [repost]

There are a wide variety of common performance problems that you will encounter when query tuning. Part 1 of this two-part course begins by showing how to validate query execution assumptions around statistics and cardinality in order to ensure you're troubleshooting the true root cause of a query performance issue. You'll then learn about common areas where bad assumptions can occur that negatively impact overall query performance, and about common problems and solutions related to being imprecise when querying a database. The course is very demo-centric, with lots of practical tips and tricks you'll be able to apply in your environment. This course is perfect for developers, DBAs, and anyone responsible for query performance tuning on SQL Server, from SQL Server 2005 onward.

Course Introduction
Course Introduction
Course Scope
Course Structure

Validating Assumptions
Module Introduction
Downstream Impact of Bad Assumptions
Cardinality Estimation and Predicates
Selectivity
Query Cardinality Questions
Cardinality Estimate Inputs
Statistics
Demo: DBCC SHOW_STATISTICS STAT_HEADER
Demo: DBCC SHOW_STATISTICS DENSITY_VECTOR
Demo: DBCC SHOW_STATISTICS HISTOGRAM
Demo: Histogram Direct Step Hit
Demo: Scaling the Estimate
Demo: Histogram Intra-Step Hit
Demo: Density Vector With an Unknown Runtime Value
Demo: Parameter Sniffed Value Estimation
Demo: Distinct Value Estimation
Impact to Query Execution and Performance
Identifying Bad Assumptions - 1
Demo: Viewing Estimated Vs. Actual Row Counts
Identifying Bad Assumptions - 2
Demo: sys.dm_exec_query_profiles
Demo: Root-level Skews via sys.dm_exec_query_stats
What Variance is Problematic?
Module Summary

Troubleshooting Bad Assumptions
Module Introduction
Model Assumptions
Demo: Jagged Distributions
Demo: Correlated Predicates
Demo: Correlated Predicates in SQL Server 2014
Demo: Correlated Join Predicates, Independent Filter Predicates
Demo: Searching for Off-Histogram Values
Demo: Searching for Off-Histogram Values in SQL Server 2014
Troubleshooting Questions - 1
Demo: Missing Statistics
Demo: Selectivity Guesses
Demo: Stale Statistics
Demo: Inadequate Sampling
Demo: Parameter Sensitivity
Demo: Table Variable Usage
Demo: MSTVF Usage - Part 1
Demo: MSTVF Usage - Part 2
Demo: MSTVF Usage - Part 3
Troubleshooting Questions - 2
Demo: Data Type Conversions
Demo: Buried Predicates - Part 1
Demo: Buried Predicates - Part 2
Module Summary

Tuning Imprecision Problems
Module Introduction
Demo: SELECT *
Demo: Unnecessary Sorts
Demo: Needless DISTINCT
Demo: UNION Vs. UNION ALL
Demo: Leading Wildcards
Demo: Hidden Cartesian Products
Demo: Data Type Conversion Issues
Demo: Redundant Logic and Overlapping Object References
Module and Course Summary