Feb 11, 2015: RC, SI, and RCSI, Oh My! – We’re off to see the Wizard – to understand how it all works.

(Download Arnie’s Presentation Slides and Demo Code.) 

Arnie Rowland
RC, SI, and RCSI, Oh My!
–We’re off to see the Wizard -to understand how it all works.

I’m just going to say it straight out. I’m pessimistically optimistic that you really understand transaction concurrency control in SQL Server. There is often significant confusion about SQL Server’s transaction concurrency and contention control options available to Developers -is it ‘pessimistic’, or is it ‘optimistic’, or somewhere in between? Everyone ‘sort of’ understands the legacy READ COMMITTED (RC). But do you sometimes feel ‘dirty’ as you attempt to ‘repeatedly’ read that phantasma? As users and activity increase, and in order to reduce locking and blocking conflicts, some folks adopt SNAPSHOT ISOLATION (SI). And a few hardy stalwarts have ventured into the brave new world of READ COMMITTED SNAPSHOT ISOLATION (RCSI). In this session, we will explore the differences between the three, including a discussion about the positives and negatives of each option. We will discuss the effects of ‘Dirty’, ‘Repeatable’ and ‘Phantom’ reads, and why you may want to know which may be buried in your code. There will be code examples demonstrating the benefits and traps of each option.

Arnie Rowland Arnie [LinkedIn] is a Data Architect, Consultant and Trainer specializing in developer/development issues related to SQL Server. Clients include Fortune 100 enterprises, large scale NGOs, as well as domestic and foreign governments. In addition to facilitating the Oregon SQL –developers user group, he is a SQL Server MVP, a senior moderator for the Microsoft MSDN SQL Server Forums, member of the Microsoft TechNet Wiki Community Council, and co-founder of Portland Code Camp.

Eugene Lyubar
Power of Pivoting and Unpivoting

Eugene will show how SQL pivots can be used to normalize data, how to use normalized data to do relative searches, and how to unpivot normalized data to create user determined column sets.

Eugene Lyubar Eugene (LinkedIn ) is an SQL developer for Interject Data Systems. He has spent the last year and half developing and architecting a relational database cube to out perform OLAP cubes.

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Refreshments graciously provided.

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We wish to acknowledge the OSHU Information Technology Group for supporting Oregon SQL by generously providing the meeting venue.


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