I was recently faced with a difficult performance issue. In an effort to save a client some time and money I convinced them that a view-based dimensional model was the way to go over a table/ETL based solution. I will blog about when this option is an option and the benefits to going this route some time in the near future. Anyhow, based on this decision I ended with a performance issue that I wouldn't have otherwise had.
The view-based dimensional database consisted of 30-40 fact and dimension views. As I created these views I made sure to test them for performance issues and tuned accordingly. I tested each view on its own and I tested individual joins between fact and dimension views.
Everything was working fine until I began creating sample queries to show end-users possible queries they could write against the new database. What I found was that when a particular dimension view was joined to a fact view along with one or more other dimension views I had unexpected performance issues. Queries that should take a few seconds to execute were taking 45-50 seconds.
In looking at the execution plans I saw that the optimizer was not doing what I had expected based on what I had seen for plans for the views executed on their own. I saw weird things like LEFT OUTER joins instead of INNER joins to my views resolving or partially resolving the issue.
I couldn't understand why the optimizer would treat the SQL in my views differently now that it was joined to other tables or views. To be honest, I'm still not sure. What I am sure of is that there is a query hint that forces the optimizer to create a plan for the view portion of the SQL irrespective of any other objects in the statement by forcing the optimizer to preserve the table/join order contained in the view definition. This hint is the FORCE ORDER hint and can be added to the end of the SQL statement using the following syntax.
Below is an example.
FROM table1 t1
INNER JOIN view1 v1 ON t1.col1 = v1.col3