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Understanding the Procedure Cache on SQL Azure

[This article was contributed by the SQL Azure team.]Both SQL Server and SQL Azure have a procedure cache which is used to improve the performance of queries on the server. This blog post will talk…

[This article was contributed by the SQL Azure team.]

Both SQL Server and SQL Azure have a procedure cache which is used to improve the performance of queries on the server. This blog post will talk about how the procedure cache works on SQL Azure.

SQL Azure has a pool of memory that is used to store both execution plans and data buffers. This pool of memory is used for all databases on the physical machine, regardless of owner of the database. Even though the pool is across all databases on the machine, no one can see execution plans that they do not own. The percentage of the pool allocated to either execution plans or data buffers fluctuates dynamically, depending on the state of the system. The part of the memory pool that is used to store execution plans is referred to as the procedure cache.

When any SQL statement is executed in SQL Azure, the relational engine first looks through the procedure cache to verify that an existing execution plan for the same SQL statement exists. SQL Azure reuses any existing plan it finds, saving the overhead of recompiling the SQL statement. If no existing execution plan exists, SQL Azure generates a new execution plan for the query.

Replicas the Procedure Cache and SQL Azure

An instance of a database running on SQL Azure is called a replica; there are three replicas of any one database running at a given time. One replica is considered the primary replica, all the read and write queries go to this replica. The other two replicas are considered secondary, any data written to the primary replica is also written to the secondary replicas. If the primary replica fails, needs to be cycled for updates, or there is a load balancing operation, then a secondary replica is promoted to the primary.

Each replica resides on different physical machines which are on separate fully redundant racks. Because, procedure cache is on a per server basis, if the primary replica fails/cycled, when the secondary is promoted there are no query plans for that database in the procedure cache.

Procedure Cache Statistics

SQL Azure keeps track of performance statistics for every query plan in the cache. You can view these statistics for your database queries using the dynamic managed view (DMV) sys.dm_exec_query_stats like so:

SELECT *  FROM sys.dm_exec_query_stats

For a more details example, see this blog post, I showed how to find queries with poor I/O performance by querying sys.dm_exec_query_stats.

sys.dm_exec_query_stats only reports statistics for the primary replica for your SQL Azure database. If a secondary is promoted to the primary, the results from sys.dm_exec_query_stats might be much different, just seconds later. Queries in the cache might suddenly not be there, or execution counts could be smaller, typically you would see them grow over time.

Removing Execution Plans from the Procedure Cache

Execution plans remain in the procedure cache as long as there is enough memory to store them. When memory pressure exists, SQL Azure uses a cost-based approach to determine which execution plans to remove from the procedure cache.

SQL Azure removes plans from the cache, regardless of the plan owner; all plans across all databases existing on the server are evaluated for removal. There is no a portion of the memory pool set aside for each database. In other words, the procedure plan cache is optimized for the benefit of the machine not that individual database.

SQL Azure currently doesn’t support DBCC FREEPROCCACHE (Transact-SQL), so you cannot manually remove an execution plan from the cache.  However, if you make changes to the to a table or view referenced by the query (ALTER TABLE and ALTER VIEW) the plan will be removed from the cache.


In many ways the procedure cache work much like SQL Server; SQL Azure is built on top of SQL Server. However, there are some differences and I hope you understand them better now. Do you have questions, concerns, comments? Post them below and we will try to address them.