There are a few presentations coming up this week.
The first is Grant Fritchey’s presentation on Tuesday 8/11 at 1PM EST: Understanding Execution Plans. Here’s the story:
Attendees will be introduced to the wealth of data contained within the execution plans generated by SQL Server. From the simplest “SELECT *” query to complicated joins, the icons and properties that allow you to understand what is occuring within your query will be explained. You will leave knowing what kinds of execution plans you have available and what they can be used for. You’ll learn about graphical exeuction plans; what do the icons mean and how are they related; how much information is available and how to access and interpret it. All this information will be used to help you understand what’s happening within your queries so that you can identify and fix poor performance in your own environment.
Grant is encouraging questions about execution plans. Also ask him about his robot legs and how they handle sticks. I think you’ll be pleasantly surprised.
Also, Kevin Kline will be presenting, remotely, at CBusPASS (8/13/2009 @ 6:30 PM) on End-to-End Troubleshooting for SQL Server. Kevin will be sharing his wisdom from the devLink conference. Times and LiveMeeting info are on the CBusPASS website. For those in attendance, see if you can spot me. I’ll be in Nashville, stalking Kevin.
Finally on August 26th at noon EST, Janis Griffin will be presenting on Wait-Time Based SQL Server Performance Management for the PASS DBA Virtual Chapter (this is a Live Meeting). Here’s the summary, in case you don’t want to click:
Using Wait Time Analysis and Wait Types is a newer method for tuning SQL Server instances. As a result, there is often confusion on exactly what the data means. The issue typically centers around the fact the wait time data is analyzed at the wrong level or the collected wait time data is not detailed enough. This presentation will focus on these problems and review several real-life case studies of using SQL Server Wait Type data coupled with Wait-Time based performance analysis to solve the most difficult performance related issues.
