So you heard about the new spatial functionality in SQL Server 2008, rushed back to your database and added geography and geometry columns to all your tables, eager to create the next Google Earth-beating application. After putting the finishing touches to your spatial query, you click the Execute button and wait.
And wait.
And wait some more. (You get the idea).

Spatial data is a rather unique beast, and designing efficient spatial queries requires specific techniques when compared to other, more traditional types of data.
In the first part of this session, we'll start by examining how the SQL Server database engine satisfies spatial queries, the theory behind spatial indexes, and seeing how a spatial index can provide a primary filter to pre-select or discard rows from the need to perform expensive spatial operations.
We'll then move onto the practical application of this knowledge, demonstrating the effects of altering the bounding box and grid resolution of a spatial index, and interpreting the results of the spatial system DMVs and stored procedures to tune a spatial index for effective spatial query performance.