Statistics4Performance: Internals, Analysis, Problem Solving

Have you ever wondered why SQL Server did what it did to process your query? Have you wondered if it could have done better? Query estimates/statistics are at the core understanding what’s really going on. This full-day, and fast-paced workshop will explain the what, why, and how about SQL Server statistics!

It’s actually pretty amazing that most of the time SQL Server returns data quickly. However, there are cases when performance is slow and the reason seems a mystery; what SQL Server did to access your data just doesn’t make sense. Part of the issue is that Transact-SQL is a declarative language that details what data you need but without information about how SQL Server go about getting it. And, there are many factors that affect this: join order, predicate analysis, the number of predicates and how they’re written (AND or OR)… With all of these factors, how does SQL Server decide what to do? There are numerous reasons why query performance can suffer and in this full-day workshop, Kimberly will cover a number of critical areas and for each - show you the behavior, the execution plan, the troubleshooting technique, and most importantly, the possible solutions.

This full-day workshop is about solving your query performance problems. Each problem has a different way of handling it and you’ll walk away with a plethora of strategies to troubleshoot and tackle problems related to statistics. Stop with the "sledgehammer" approaches (updating statistics, rebuilding indexes, recompiling, clearing cache, restarting SQL Server) and solve the actual problem. In this full-day workshop, you'll learn much more finessed ways to solve query plan quality problems.

Topics covered include understanding / maintaining statistics, handing skewed data, distribution problems, troubleshooting common and advanced scenarios, and how to best utilize the cardinality estimation models (and trace flags) available in SQL Server versions 2014 and higher. All demos will be shown on SQL Server 2017 and SQL Server 2019.


Wednesday 1 April 2020