[Windows Azure] Monitoring SQL Database Using Dynamic Management Views

Monitoring Windows Azure SQL Database Using Dynamic Management Views

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Microsoft Windows Azure SQL Database enables a subset of dynamic management views to diagnose the performance problems, which might be caused by blocked or long-running queries, resource bottlenecks, poor query plans, and so on. This topic provides information on how to detect common performance problems by using the dynamic management views in Windows Azure SQL Database.

Windows Azure SQL Database partially supports three categories of dynamic management views:

  • Database-related dynamic management views.

  • Execution-related dynamic management views.

  • Transaction-related dynamic management views.

For a list of fully supported dynamic management views in Windows Azure SQL Database, see System Views (Windows Azure SQL Database). For detailed information on dynamic management views, see Dynamic Management Views and Functions (Transact-SQL) in SQL Server Books Online.

Permissions

In Windows Azure SQL Database, querying a dynamic management view requires VIEW DATABASE STATE permissions. The VIEW DATABASE STATE permission returns information about all objects within the current database.

To grant the VIEW DATABASE STATE permission to a specific database user, run the following query:

 
GRANT VIEW DATABASE STATE TO database_user;

In an instance of on-premise SQL Server, dynamic management views return server state information. In Windows Azure SQL Database, they return information regarding your current logical database only.

noteNote
When executing the sys.dm_exec_requests and sys.dm_exec_sessions views, if the user has VIEW DATABASE STATE permission on the database, the user will see all executing sessions on the database; otherwise, the user will see only the current session.

 

 

Calculating Database Size

You are billed for the edition and the capacity of your SQL Databases. If the size of your database reaches its MAXSIZE you will receive an error code 40544. You cannot insert or update data, or create new objects (such as tables, stored procedures, views, and functions) unless you update the MAXSIZE of your database or delete data. For more information, see Accounts and Billing in Windows Azure SQL Database. The sys.dm_db_partition_stats view returns page and row-count information for every partition in the database, which can be used to calculate database size.

The following query returns the size of your database (in megabytes):

 
-- Calculates the size of the database. 



SELECT SUM(reserved_page_count)*8.0/1024



FROM sys.dm_db_partition_stats; 



GO

The following query returns the size of individual objects (in megabytes) in your database:

 
-- Calculates the size of individual database objects. 



SELECT sys.objects.name, SUM(reserved_page_count) * 8.0 / 1024



FROM sys.dm_db_partition_stats, sys.objects 



WHERE sys.dm_db_partition_stats.object_id = sys.objects.object_id 



GROUP BY sys.objects.name; 



GO

Monitoring Connections

You can use the sys.dm_exec_connections (Windows Azure SQL Database) view to retrieve information about the connections established to a specific SQL Database server and the details of each connection. In addition, the sys.dm_exec_sessions view is helpful when retrieving information about all active user connections and internal tasks.

The following query retrieves information on the current connection:

-- monitor connections

SELECT

      e.connection_id,

      s.session_id,

      s.login_name,

      s.last_request_end_time,

      s.cpu_time

FROM

      sys.dm_exec_sessions s

      INNER JOIN sys.dm_exec_connections e

      ON s.session_id = e.session_id

GO

Monitoring Query Performance

Slow or long running queries can consume significant system resources. This section demonstrates how to use dynamic management views to detect a few common query performance problems. For detailed information, see Troubleshooting Performance Problems in SQL Server 2005 article on Microsoft TechNet.

Finding Top N Queries

The following example returns information about the top five queries ranked by average CPU time. This example aggregates the queries according to their query hash, so that logically equivalent queries are grouped by their cumulative resource consumption.

-- Find top 5queries

SELECT TOP 5 query_stats.query_hash AS "Query Hash", 

    SUM(query_stats.total_worker_time) / SUM(query_stats.execution_count) AS "Avg CPU Time",

    MIN(query_stats.statement_text) AS "Statement Text"

FROM 

    (SELECT QS.*, 

    SUBSTRING(ST.text, (QS.statement_start_offset/2) + 1,

    ((CASE statement_end_offset 

        WHEN -1 THEN DATALENGTH(st.text)

        ELSE QS.statement_end_offset END 

            - QS.statement_start_offset)/2) + 1) AS statement_text

     FROM sys.dm_exec_query_stats AS QS

     CROSS APPLY sys.dm_exec_sql_text(QS.sql_handle) as ST) as query_stats

GROUP BY query_stats.query_hash

ORDER BY 2 DESC;

GO

Monitoring Blocked Queries

Slow or long-running queries can contribute to excessive resource consumption and be the consequence of blocked queries. The cause of the blocking can be poor application design, bad query plans, the lack of useful indexes, and so on. You can use the sys.dm_tran_locks view to get information about the current locking activity in your SQL Database. For example code, see sys.dm_tran_locks (Transact-SQL) in SQL Server Books Online.

Monitoring Query Plans

An inefficient query plan also may increase CPU consumption. The following example uses the sys.dm_exec_query_stats view to determine which query uses the most cumulative CPU.

-- Monitor query plans

SELECT

    highest_cpu_queries.plan_handle,  

    highest_cpu_queries.total_worker_time, 

    q.dbid, 

    q.objectid, 

    q.number, 

    q.encrypted, 

    q.[text] 

FROM 

    (SELECT TOP 50  

        qs.plan_handle,  

        qs.total_worker_time 

     FROM 

        sys.dm_exec_query_stats qs 

     ORDER BY qs.total_worker_time desc) AS highest_cpu_queries 

     CROSS APPLY sys.dm_exec_sql_text(plan_handle) AS q 

ORDER BY highest_cpu_queries.total_worker_time desc

See Also

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